From f81f78bb3b0e530961aeca9ea14da6b77c18e076 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Mon, 10 Jun 2024 18:57:32 -0700 Subject: [PATCH 01/61] added hash sift as interest point --- localization/interest_point/CMakeLists.txt | 3 + .../include/interest_point/BAD.h | 97 +++ .../include/interest_point/HashSIFT.h | 90 +++ .../interest_point/HashSiftWeights256.h | 1 + .../interest_point/HashSiftWeights512.h | 1 + .../include/interest_point/PatchSIFT.h | 138 ++++ localization/interest_point/src/BAD.cpp | 611 ++++++++++++++++++ localization/interest_point/src/HashSIFT.cpp | 101 +++ localization/interest_point/src/PatchSIFT.cpp | 292 +++++++++ localization/interest_point/src/matching.cc | 51 +- 10 files changed, 1383 insertions(+), 2 deletions(-) create mode 100644 localization/interest_point/include/interest_point/BAD.h create mode 100644 localization/interest_point/include/interest_point/HashSIFT.h create mode 100644 localization/interest_point/include/interest_point/HashSiftWeights256.h create mode 100644 localization/interest_point/include/interest_point/HashSiftWeights512.h create mode 100644 localization/interest_point/include/interest_point/PatchSIFT.h create mode 100644 localization/interest_point/src/BAD.cpp create mode 100644 localization/interest_point/src/HashSIFT.cpp create mode 100644 localization/interest_point/src/PatchSIFT.cpp diff --git a/localization/interest_point/CMakeLists.txt b/localization/interest_point/CMakeLists.txt index 8a3cbd43bd..8558c5aa60 100644 --- a/localization/interest_point/CMakeLists.txt +++ b/localization/interest_point/CMakeLists.txt @@ -61,6 +61,9 @@ add_library(interest_point src/brisk.cc src/essential.cc src/matching.cc + src/BAD.cpp + src/HashSIFT.cpp + src/PatchSIFT.cpp ) add_dependencies(interest_point ${catkin_EXPORTED_TARGETS}) target_link_libraries(interest_point ${OPENMVG_LIBRARIES} ${catkin_LIBRARIES} ${OpenCV_LIBRARIES}) diff --git a/localization/interest_point/include/interest_point/BAD.h b/localization/interest_point/include/interest_point/BAD.h new file mode 100644 index 0000000000..434d19a8f5 --- /dev/null +++ b/localization/interest_point/include/interest_point/BAD.h @@ -0,0 +1,97 @@ +/** + * @copyright 2021 Xoan Iago Suarez Canosa. All rights reserved. + * Constact: iago.suarez@thegraffter.com + * Software developed in the PhD: Low-level vision for resource-limited devices + */ +#ifndef EFFICIENT_DESCRIPTORS_BAD_H_ +#define EFFICIENT_DESCRIPTORS_BAD_H_ + +#include +#include + +namespace upm { + +/** + * Implementation of the Box Average Difference (BAD) descriptor. The method uses features + * computed from the difference of the average gray values of two boxes in the patch. + * + * Each pair of boxes is represented with a BoxPairParams struct. After obtaining the feature + * from them, the i'th feature is thresholded with thresholds_[i], producing the binary + * weak-descriptor. + */ +class BAD : public cv::Feature2D { + public: + /** + * @brief Descriptor number of bits, each bit is a weak-descriptor. + * The user can choose between 512 or 256 bits. + */ + enum BadSize { + SIZE_512_BITS = 100, SIZE_256_BITS = 101, + }; + + /** + * @param scale_factor Adjust the sampling window around detected keypoints: + - 1.00f should be the scale for ORB keypoints + - 6.75f should be the scale for SIFT detected keypoints + - 6.25f is default and fits for KAZE, SURF detected keypoints + - 5.00f should be the scale for AKAZE, MSD, AGAST, FAST, BRISK keypoints + * @param n_bits Determine the number of bits in the descriptor. Should be either + BAD::SIZE_512_BITS or BAD::SIZE_256_BITS. + */ + explicit BAD(float scale_factor = 1.0f, BadSize n_bits = SIZE_512_BITS); + + /** + * @brief Creates the BAD descriptor. + * @param scale_factor Adjust the sampling window around detected keypoints: + - 1.00f should be the scale for ORB keypoints + - 6.75f should be the scale for SIFT detected keypoints + - 6.25f is default and fits for KAZE, SURF detected keypoints + - 5.00f should be the scale for AKAZE, MSD, AGAST, FAST, BRISK keypoints + * @param n_bits + * @return + */ + static cv::Ptr create(float scale_factor = 1.0f, BadSize n_bits = SIZE_512_BITS) { + return cv::makePtr(scale_factor, n_bits); + } + + /** @brief Computes the descriptors for a set of keypoints detected in an image (first variant) or image set + (second variant). + + @param image Image. + @param keypoints Input collection of keypoints. Keypoints for which a descriptor cannot be + computed are removed. Sometimes new keypoints can be added, for example: SIFT duplicates keypoint + with several dominant orientations (for each orientation). + @param descriptors Computed descriptors. In the second variant of the method descriptors[i] are + descriptors computed for a keypoints[i]. Row j is the keypoints (or keypoints[i]) is the + descriptor for keypoint j-th keypoint. + */ + void compute(cv::InputArray image, + CV_OUT CV_IN_OUT std::vector &keypoints, + cv::OutputArray descriptors) override; + + int descriptorSize() const override { return box_params_.size() / 8; } + int descriptorType() const override { return CV_8UC1; } + int defaultNorm() const override { return cv::NORM_HAMMING; } + bool empty() const override { return false; } + + cv::String getDefaultName() const override { return std::string("BAD") + std::to_string(box_params_.size()); } + + // Struct representing a pair of boxes in the patch + struct BoxPairParams { + int x1, x2, y1, y2, boxRadius; + }; + + protected: + // Computes the BADdescriptor + void computeBAD(const cv::Mat &integral_img, + const std::vector &keypoints, + cv::Mat &descriptors); + + std::vector thresholds_; + std::vector box_params_; + float scale_factor_ = 1; + cv::Size patch_size_ = {32, 32}; +}; + +} // namespace upm +#endif // EFFICIENT_DESCRIPTORS_BAD_H_ diff --git a/localization/interest_point/include/interest_point/HashSIFT.h b/localization/interest_point/include/interest_point/HashSIFT.h new file mode 100644 index 0000000000..b797a9b5d5 --- /dev/null +++ b/localization/interest_point/include/interest_point/HashSIFT.h @@ -0,0 +1,90 @@ +/** + * @copyright 2021 Xoan Iago Suarez Canosa. All rights reserved. + * Constact: iago.suarez@thegraffter.com + * Software developed in the PhD: Low-level vision for resource-limited devices + */ +#ifndef EFFICIENT_DESCRIPTORS_HASHSIFT_H_ +#define EFFICIENT_DESCRIPTORS_HASHSIFT_H_ + +#include +#include +#include +#include + +namespace upm { +/** + * HashSIFT descriptor described in the article + * "Suarez, I., Buenaposada, J. M., & Baumela, L. (2021). Revisiting Binary Local Image + * Description for Resource Limited Devices. IEEE Robotics and Automation Letters." + * + * The descriptor computes first the SIFT features using the class PatchSIFT and then it hashes + * the floating point SIFT descriptor with a pre-learnt linear projection: b_matrix_ + * The weights b_matrix_ are loaded from the files HashSiftWeights256.i and HashSiftWeights512.i. + */ +class HashSIFT : public cv::Feature2D { + public: + /** + * @brief Descriptor number of bits, each bit is a weak-descriptor. + * The user can choose between 512 or 256 bits. + */ + enum HashSiftSize { + SIZE_512_BITS = 100, SIZE_256_BITS = 101, + }; + + /** + * + * @param cropping_scale Determines the size of the patch cropped for description. + * The diameter of the patch will be: cropping_scale * kp.size + * @param n_bits The number of bits of the descriptor (512 or 256) + * @param sigma The standard deviation of the gaussian smoothing filter applied to the patch + * before description. + */ + explicit HashSIFT(float cropping_scale, + HashSiftSize n_bits = SIZE_256_BITS, + double sigma = 1.6); + + /** + * Creates a pointer to a new instance + * @param cropping_scale Determines the size of the patch cropped for description. + * The diameter of the patch will be: cropping_scale * kp.size + * @param n_bits The number of bits of the descriptor (512 or 256) + * @param sigma The standard deviation of the gaussian smoothing filter applied to the patch + * before description. + * @return A pointer to the new cv::Feature2D descriptor object + */ + static cv::Ptr create(float cropping_scale, + HashSiftSize n_bits = SIZE_256_BITS, + double sigma = 1.6); + + /** + * Computes the descriptors corresponding to the specified Keypoints + * @param image The input grayscale image + * @param keypoints The detected input keypoints + * @param descriptors The output descriptors. The shape of the output cv::Mat will be: + * n_keypoints x (nbits / 8) + */ + void compute(cv::InputArray image, CV_OUT CV_IN_OUT std::vector& keypoints, + cv::OutputArray descriptors) override; + + int descriptorSize() const override { return nbits_ / 8; } + int descriptorType() const override { return CV_8UC1; } + int defaultNorm() const override { return cv::NORM_HAMMING; } + + private: + /** + * @brief Transforms the wlResponses with the B^T matrix and apply the sign operation. + * The matrix multiplication is done using floating point arithmetic from OpenCV + * @param wlResponses A floating point matrix with the WL responses. the shape is: + * (n_descriptors, n_wls) i.e. each descriptor is a row of the matrix + * @param descriptors The Output matrix where we are going to store the resulting binary descriptors. + */ + void matmulAndSign(const cv::Mat &wlResponses, cv::Mat descriptors); + + std::shared_ptr sift_{}; + int nbits_{-1}; + cv::Mat_ b_matrix_; + cv::Mat_ transp_b_matrix_; +}; + +} // namespace upm +#endif // EFFICIENT_DESCRIPTORS_HASHSIFT_H_ diff --git a/localization/interest_point/include/interest_point/HashSiftWeights256.h b/localization/interest_point/include/interest_point/HashSiftWeights256.h new file mode 100644 index 0000000000..f9fa2edf35 --- /dev/null +++ b/localization/interest_point/include/interest_point/HashSiftWeights256.h @@ -0,0 +1 @@ +double 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\ No newline at end of file diff --git a/localization/interest_point/include/interest_point/HashSiftWeights512.h b/localization/interest_point/include/interest_point/HashSiftWeights512.h new file mode 100644 index 0000000000..45a091117d --- /dev/null +++ b/localization/interest_point/include/interest_point/HashSiftWeights512.h @@ -0,0 +1 @@ +double 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\ No newline at end of file diff --git a/localization/interest_point/include/interest_point/PatchSIFT.h b/localization/interest_point/include/interest_point/PatchSIFT.h new file mode 100644 index 0000000000..a60eb8ac80 --- /dev/null +++ b/localization/interest_point/include/interest_point/PatchSIFT.h @@ -0,0 +1,138 @@ +/** + * @copyright 2021 Xoan Iago Suarez Canosa. All rights reserved. + * Constact: iago.suarez@thegraffter.com + * Software developed in the PhD: Low-level vision for resource-limited devices + */ +#ifndef EFFICIENT_DESCRIPTORS_PATCHSIFT_H_ +#define EFFICIENT_DESCRIPTORS_PATCHSIFT_H_ + +#include +#include + +namespace upm { + +/** + * Implementation of the SIFT descriptor: + * Lowe, D. G. (2004). Distinctive image features from scale-invariant keypoints. + * International journal of computer vision, 60(2), 91-110. + * + * This code does not include the detection part. Instead, it is intended to be used with any + */ +class PatchSIFT : public cv::Feature2D { + public: + explicit PatchSIFT(float kp_scale, // Default 1 / 6.0 + float cropping_scale, + double sigma = 1.6, + bool step1_pyramid = true, + bool step4_gaussian_weight = true, + bool step6_trilinear_interp = true, + bool step7_l2_normalization = true, + bool step8_trim_bigvals = true, + bool step9_uchar_scaling = true); + + static cv::Ptr create(float kp_scale, // Default 1 / 6.0 + float cropping_scale, + double sigma = 1.6, + bool step1_pyramid = true, + bool step4_gaussian_weight = true, + bool step6_trilinear_interp = true, + bool step7_l2_normalization = true, + bool step8_trim_bigvals = true, + bool step9_uchar_scaling = true); + + //! returns the descriptor size in floats (128) + int descriptorSize() const override; + int descriptorType() const override { return CV_32FC1; } + int defaultNorm() const override { return cv::NORM_L2; } + + void compute(cv::InputArray image, + CV_OUT CV_IN_OUT std::vector &keypoints, + cv::OutputArray descriptors) override; + + void describeKeypoint(const cv::Mat &image, cv::Mat &descriptor); + + void calcSIFTDescriptor(const cv::Mat &img, cv::Mat descriptor); + + inline const cv::Size &GetPatchSize() const { return patch_size; } + inline const float &GetCroppingScale() const { return cropping_scale; } + + static void rectifyPatch(const cv::Mat &image, + const cv::KeyPoint &kp, + const cv::Size &patchSize, + cv::Mat &patch, + float scale_factor); + + protected: + // The scale of the keypoint relative to the patch size. If will be used to modify the variance + // of the gaussian that give more weight to the pixels in the center + float kp_scale; + double sigma; + // default number of bins per histogram in descriptor array + int ori_bins = 8; + // default width of descriptor histogram array + int r_bins = 4; + // default width of descriptor histogram array + int c_bins = 4; + // threshold on magnitude of elements of descriptor vector + float magnitude_th = 0.2f; + // factor used to convert floating-point descriptor to unsigned char + float int_descr_factor = 512.f; + // Steps of the algorithm we can configure + bool step1_pyramid = true; + bool step4_gaussian_weight = true; + bool step6_trilinear_interp = true; + bool step7_l2_normalization = true; + bool step8_trim_bigvals = true; + bool step9_uchar_scaling = true; + + cv::Size patch_size{32, 32}; + float cropping_scale = 1.0f; +}; + +/******************************* Defs and macros *****************************/ + +// assumed gaussian blur for input image +static const float SIFT_INIT_SIGMA = 0.5f; + +// determines the size of a single descriptor orientation histogram +static const float SIFT_DESCR_SCL_FCTR = 3.f; + +class RootPatchSIFT : public PatchSIFT { + public: + RootPatchSIFT(float kp_scale, // Default 1 / 6.0 + float cropping_scale, double sigma = 1.6, bool step1_pyramid = true, bool step4_gaussian_weight = true, + bool step6_trilinear_interp = true, bool step7_l2_normalization = true, bool step8_trim_bigvals = true, + bool step9_uchar_scaling = true) + : PatchSIFT(kp_scale, cropping_scale, sigma, step1_pyramid, step4_gaussian_weight, step6_trilinear_interp, + step7_l2_normalization, step8_trim_bigvals, step9_uchar_scaling) {} + + void compute(cv::InputArray image, + CV_OUT CV_IN_OUT std::vector &keypoints, + cv::OutputArray _descriptors) override { + PatchSIFT::compute(image, keypoints, _descriptors); + cv::Mat descriptors = _descriptors.getMat(); + for (int i = 0; i < descriptors.rows; i++) { + double norm = cv::norm(descriptors.row(i), cv::NORM_L1); + cv::sqrt(descriptors.row(i) / norm, descriptors.row(i)); + } + } + + static cv::Ptr create(float kp_scale, // Default 1 / 6.0 + float cropping_scale, double sigma = 1.6, bool step1_pyramid = true, + bool step4_gaussian_weight = true, bool step6_trilinear_interp = true, + bool step7_l2_normalization = true, bool step8_trim_bigvals = true, + bool step9_uchar_scaling = true) { + return cv::makePtr(kp_scale, + cropping_scale, + sigma, + step1_pyramid, + step4_gaussian_weight, + step6_trilinear_interp, + step7_l2_normalization, + step8_trim_bigvals, + step9_uchar_scaling); + } +}; + +} // namespace upm +#endif // EFFICIENT_DESCRIPTORS_PATCHSIFT_H_ diff --git a/localization/interest_point/src/BAD.cpp b/localization/interest_point/src/BAD.cpp new file mode 100644 index 0000000000..2d26abeef9 --- /dev/null +++ b/localization/interest_point/src/BAD.cpp @@ -0,0 +1,611 @@ +/** + * @copyright 2021 Xoan Iago Suarez Canosa. All rights reserved. + * Constact: iago.suarez@thegraffter.com + * Software developed in the PhD: Low-level vision for resource-limited devices + */ +#include +#include + +#define UPM_DEGREES_TO_RADS 0.017453292519943295 +#define UPM_ROUNDNUM(x) ((int)(x + 0.5f)) +#define UPM_BAD_EXTRA_RATIO_MARGIN 1.75 + +namespace upm { +/** + * @brief Rectifies the coordinates of the box pairs measurement functions with the keypoint + * location parameters. + * @param boxes_params The input parameters defining the location of each pair of boxes inside + * the normalized (32x32) patch. + * @param out_params The output parameters, now the boxes are located in the full image. + * @param kp The keypoint defining the offset, rotation and scale to be applied + * @param scale_factor A scale factor that magnifies the measurement functions w.r.t. the keypoint. + * @param patch_size The size of the normalized patch where the measurement functions were learnt. + */ +static inline void rectifyBoxes(const std::vector &boxes_params, + std::vector &out_params, + const cv::KeyPoint &kp, + float scale_factor = 1, + const cv::Size &patch_size = cv::Size(32, 32)) { + float m00, m01, m02, m10, m11, m12; + float s, cosine, sine; + + s = scale_factor * kp.size / (0.5f * (patch_size.width + patch_size.height)); + out_params.resize(boxes_params.size()); + + if (kp.angle == -1) { + m00 = s; + m01 = 0.0f; + m02 = -0.5f * s * patch_size.width + kp.pt.x; + m10 = 0.0f; + m11 = s; + m12 = -s * 0.5f * patch_size.height + kp.pt.y; + } else { + cosine = (kp.angle >= 0) ? float(cos(kp.angle * UPM_DEGREES_TO_RADS)) : 1.f; + sine = (kp.angle >= 0) ? float(sin(kp.angle * UPM_DEGREES_TO_RADS)) : 0.f; + + m00 = s * cosine; + m01 = -s * sine; + m02 = (-s * cosine + s * sine) * patch_size.width * 0.5f + kp.pt.x; + m10 = s * sine; + m11 = s * cosine; + m12 = (-s * sine - s * cosine) * patch_size.height * 0.5f + kp.pt.y; + } + + for (size_t i = 0; i < boxes_params.size(); i++) { + out_params[i].x1 = UPM_ROUNDNUM(m00 * boxes_params[i].x1 + m01 * boxes_params[i].y1 + m02); + out_params[i].y1 = UPM_ROUNDNUM(m10 * boxes_params[i].x1 + m11 * boxes_params[i].y1 + m12); + out_params[i].x2 = UPM_ROUNDNUM(m00 * boxes_params[i].x2 + m01 * boxes_params[i].y2 + m02); + out_params[i].y2 = UPM_ROUNDNUM(m10 * boxes_params[i].x2 + m11 * boxes_params[i].y2 + m12); + out_params[i].boxRadius = UPM_ROUNDNUM(s * boxes_params[i].boxRadius); + } +} + +/** + * @brief Computes the Box Average Difference, measuring the difference of gray level in the two + * square regions. + * @param box_params The weak-learner parameter defining the size and locations of each box. + * @param integral_img The integral image used to compute the average gray value in the square regions. + * @return The difference of gray level in the two squares defined by box_params + */ +static inline float computeBadResponse(const BAD::BoxPairParams &box_params, + const cv::Mat &integral_img) { + assert(!integral_img.empty()); + assert(integral_img.type() == CV_32SC1); + + int frame_w, frame_h, box1x1, box1y1, box1x2, box1y2, box2x1, box2y1, box2x2, box2y2; + int A, B, C, D; + int box_area1, box_area2; + float sum1, sum2, average1, average2; + // Since the integral image has one extra row and col, calculate the patch dimensions + frame_w = integral_img.cols; + frame_h = integral_img.rows; + + // For the first box, we calculate its margin coordinates + box1x1 = box_params.x1 - box_params.boxRadius; + if (box1x1 < 0) + box1x1 = 0; + else if (box1x1 >= frame_w - 1) + box1x1 = frame_w - 2; + box1y1 = box_params.y1 - box_params.boxRadius; + if (box1y1 < 0) + box1y1 = 0; + else if (box1y1 >= frame_h - 1) + box1y1 = frame_h - 2; + box1x2 = box_params.x1 + box_params.boxRadius + 1; + if (box1x2 <= 0) + box1x2 = 1; + else if (box1x2 >= frame_w) + box1x2 = frame_w - 1; + box1y2 = box_params.y1 + box_params.boxRadius + 1; + if (box1y2 <= 0) + box1y2 = 1; + else if (box1y2 >= frame_h) + box1y2 = frame_h - 1; + assert((box1x1 < box1x2 && box1y1 < box1y2) && "Box 1 has size 0"); + + // For the second box, we calculate its margin coordinates + box2x1 = box_params.x2 - box_params.boxRadius; + if (box2x1 < 0) + box2x1 = 0; + else if (box2x1 >= frame_w - 1) + box2x1 = frame_w - 2; + box2y1 = box_params.y2 - box_params.boxRadius; + if (box2y1 < 0) + box2y1 = 0; + else if (box2y1 >= frame_h - 1) + box2y1 = frame_h - 2; + box2x2 = box_params.x2 + box_params.boxRadius + 1; + if (box2x2 <= 0) + box2x2 = 1; + else if (box2x2 >= frame_w) + box2x2 = frame_w - 1; + box2y2 = box_params.y2 + box_params.boxRadius + 1; + if (box2y2 <= 0) + box2y2 = 1; + else if (box2y2 >= frame_h) + box2y2 = frame_h - 1; + assert((box2x1 < box2x2 && box2y1 < box2y2) && "Box 2 has size 0"); + + // Read the integral image values for the first box + A = integral_img.at(box1y1, box1x1); + B = integral_img.at(box1y1, box1x2); + C = integral_img.at(box1y2, box1x1); + D = integral_img.at(box1y2, box1x2); + + // Calculate the mean intensity value of the pixels in the box + sum1 = float(A + D - B - C); + box_area1 = (box1y2 - box1y1) * (box1x2 - box1x1); + assert(box_area1 > 0); + average1 = sum1 / box_area1; + + // Calculate the indices on the integral image where the box falls + A = integral_img.at(box2y1, box2x1); + B = integral_img.at(box2y1, box2x2); + C = integral_img.at(box2y2, box2x1); + D = integral_img.at(box2y2, box2x2); + + // Calculate the mean intensity value of the pixels in the box + sum2 = float(A + D - B - C); + box_area2 = (box2y2 - box2y1) * (box2x2 - box2x1); + assert(box_area2 > 0); + average2 = sum2 / box_area2; + + return average1 - average2; +} + +/** + * @brief Function that determines if a keypoint is close to the image border. + * @param kp The detected keypoint + * @param img_size The size of the image + * @param patch_size The size of the normalized patch where the measurement functions were learnt. + * @param scale_factor A scale factor that magnifies the measurement functions w.r.t. the keypoint. + * @return true if the keypoint is in the border, false otherwise + */ +static inline bool isKeypointInTheBorder(const cv::KeyPoint &kp, + const cv::Size &img_size, + const cv::Size &patch_size = {32, 32}, + float scale_factor = 1) { + // This would be the correct measure but since we will compare with half of the size, use this as border size + float s = scale_factor * kp.size / (patch_size.width + patch_size.height); + cv::Size2f border(patch_size.width * s * UPM_BAD_EXTRA_RATIO_MARGIN, + patch_size.height * s * UPM_BAD_EXTRA_RATIO_MARGIN); + + if (kp.pt.x < border.width || kp.pt.x + border.width >= img_size.width) + return true; + + if (kp.pt.y < border.height || kp.pt.y + border.height >= img_size.height) + return true; + + return false; +} + +/////////////////////////////////////////////////////////////////////////////// + +BAD::BAD(float scale_factor, BadSize n_bits) { + scale_factor_ = scale_factor; + + if (n_bits == SIZE_512_BITS) { + // With data augmentation + // box_params_ = {{17,18,12,15,2}, {13,14,5,7,5}, {21,16,16,14,1}, {27,11,18,20,3}, {17,13,16,19,2}, + // {18,24,18,16,5}, {12,11,10,25,6}, {14,17,14,13,1}, {7,4,4,15,4}, {27,27,23,8,4}, {19,13,19,6,6}, {14,15,10,16,1}, + // {13,15,12,22,1}, {8,22,3,27,3}, {13,19,8,13,1}, {18,16,17,12,1}, {27,7,25,11,4}, {24,20,20,15,2}, {16,24,14,3,3}, + // {23,18,7,18,7}, {8,7,2,1,1}, {17,28,17,26,3}, {17,13,17,10,2}, {10,18,10,11,1}, {11,28,7,22,2}, {18,13,15,15,1}, + // {7,14,3,20,3}, {17,19,14,15,1}, {14,12,14,8,2}, {14,12,13,11,1}, {21,9,19,19,2}, {4,28,3,10,3}, {27,27,26,26,4}, + // {19,22,19,19,2}, {12,25,12,20,1}, {19,12,15,12,1}, {28,21,23,21,2}, {10,15,7,18,2}, {12,7,10,3,3}, + // {21,16,19,15,1}, {19,20,18,17,1}, {26,2,19,7,2}, {18,2,15,22,2}, {24,26,24,22,5}, {15,26,15,19,1}, + // {13,19,11,20,1}, {5,14,4,10,4}, {15,7,15,4,2}, {13,16,11,7,1}, {15,22,15,18,1}, {24,8,23,4,4}, {13,11,11,14,1}, + // {4,19,3,19,3}, {22,12,19,10,1}, {24,27,15,22,2}, {12,13,10,10,1}, {11,25,9,29,2}, {15,21,15,10,1}, + // {19,16,18,19,1}, {29,13,24,8,2}, {17,16,16,20,1}, {12,17,12,15,1}, {28,4,2,11,2}, {7,25,5,19,3}, {22,13,20,16,1}, + // {14,16,13,17,1}, {10,3,8,11,3}, {18,7,17,11,2}, {27,11,25,22,2}, {5,26,3,28,3}, {28,13,27,13,3}, {22,20,20,28,3}, + // {12,6,5,2,2}, {14,18,13,16,1}, {17,29,3,25,2}, {20,20,19,19,1}, {15,12,14,15,1}, {12,14,12,13,1}, + // {17,14,10,26,3}, {11,15,6,12,6}, {9,22,9,19,1}, {19,18,19,14,1}, {23,15,12,18,2}, {12,15,11,14,1}, {28,2,27,9,2}, + // {11,19,11,11,7}, {13,29,13,23,2}, {27,19,22,17,3}, {17,3,17,2,2}, {4,6,3,3,3}, {19,15,16,16,1}, {22,5,20,9,2}, + // {14,6,13,9,2}, {17,16,13,16,2}, {24,18,12,6,6}, {20,14,18,15,2}, {20,9,18,13,1}, {18,20,17,8,2}, {10,15,9,15,2}, + // {13,7,12,26,2}, {13,12,11,19,2}, {15,2,2,29,2}, {15,12,14,13,1}, {20,30,19,26,1}, {28,26,28,4,3}, + // {16,13,15,12,1}, {18,11,17,25,2}, {3,17,1,24,1}, {21,18,19,22,1}, {9,13,9,8,2}, {19,18,16,16,1}, {21,22,17,20,1}, + // {13,4,13,3,3}, {24,15,21,9,1}, {24,25,19,17,6}, {4,14,3,14,2}, {17,13,14,19,1}, {7,19,4,16,3}, {4,20,1,5,1}, + // {15,13,12,14,3}, {19,26,19,21,2}, {11,26,10,18,5}, {17,16,17,13,1}, {19,16,19,11,1}, {4,26,4,23,4}, + // {14,19,14,13,5}, {10,13,8,13,2}, {14,12,14,10,1}, {29,24,26,19,2}, {26,9,19,19,5}, {16,23,16,17,1}, {4,13,3,4,3}, + // {13,16,7,21,2}, {17,16,16,17,1}, {29,15,5,18,2}, {29,2,23,5,2}, {9,17,9,14,2}, {25,26,25,22,5}, {13,21,13,20,1}, + // {23,12,7,20,6}, {6,8,6,3,3}, {13,19,13,17,1}, {25,21,22,20,1}, {24,17,23,15,2}, {20,8,17,4,1}, {11,19,10,17,1}, + // {9,11,6,9,1}, {25,9,24,14,1}, {18,20,13,14,3}, {26,23,25,23,5}, {14,20,11,4,4}, {28,7,25,13,3}, {13,13,12,12,1}, + // {7,29,2,2,2}, {16,17,16,8,5}, {20,6,19,12,3}, {19,7,19,6,6}, {20,13,19,14,1}, {19,24,16,29,2}, {8,15,4,13,1}, + // {7,9,2,10,2}, {15,14,14,13,1}, {18,13,18,11,1}, {8,19,5,23,2}, {3,13,1,14,1}, {23,20,16,14,1}, {17,15,13,18,2}, + // {16,16,9,14,5}, {15,28,15,27,3}, {18,20,16,19,1}, {16,17,16,11,2}, {30,1,10,19,1}, {12,19,9,23,2}, + // {25,13,21,13,1}, {9,23,5,24,5}, {13,20,13,18,1}, {13,13,12,13,3}, {29,18,25,2,2}, {30,30,25,26,1}, + // {16,20,15,11,1}, {18,16,18,14,1}, {15,18,5,7,4}, {16,13,15,19,1}, {26,24,16,9,5}, {1,28,1,5,1}, {20,17,20,16,1}, + // {15,19,10,17,4}, {12,9,10,5,1}, {30,29,28,29,1}, {29,17,27,18,2}, {17,29,15,27,2}, {9,29,9,28,2}, + // {23,24,21,22,1}, {22,2,1,1,1}, {20,4,20,1,1}, {5,30,4,25,1}, {20,8,17,12,7}, {10,7,3,17,3}, {21,17,14,15,5}, + // {14,10,13,8,1}, {4,21,4,13,3}, {30,1,24,10,1}, {15,17,14,16,3}, {21,23,20,15,3}, {17,20,17,18,3}, {12,11,12,6,5}, + // {15,15,12,17,1}, {25,9,16,25,6}, {22,28,22,27,3}, {5,8,3,3,3}, {9,5,9,1,1}, {30,12,29,23,1}, {20,21,5,9,5}, + // {15,21,15,20,1}, {11,17,10,23,2}, {16,11,15,13,1}, {16,12,16,10,1}, {15,6,14,3,3}, {2,4,1,1,1}, {15,16,11,15,1}, + // {24,6,24,2,2}, {8,15,6,12,1}, {21,27,1,30,1}, {17,10,14,16,3}, {13,9,7,7,7}, {22,17,19,17,1}, {16,14,14,13,2}, + // {14,21,13,23,1}, {18,2,15,7,2}, {3,25,1,24,1}, {24,20,7,14,7}, {26,25,24,19,2}, {6,25,6,23,6}, {15,24,15,17,7}, + // {22,14,16,15,1}, {17,25,17,23,1}, {12,18,2,26,2}, {30,30,26,11,1}, {22,8,16,14,5}, {9,16,8,20,1}, {4,14,2,13,2}, + // {28,7,27,8,1}, {10,22,9,24,1}, {14,16,13,18,3}, {28,26,3,15,2}, {12,15,10,15,1}, {18,17,17,15,1}, + // {30,10,28,14,1}, {30,14,28,30,1}, {30,18,7,13,1}, {3,19,2,20,1}, {16,19,14,13,2}, {11,9,5,27,4}, {16,19,15,15,2}, + // {24,22,18,19,7}, {12,17,12,12,1}, {28,5,28,1,1}, {4,29,2,30,1}, {27,11,27,8,1}, {8,3,8,1,1}, {15,10,15,8,3}, + // {12,27,11,18,4}, {25,6,22,8,6}, {15,3,15,2,2}, {19,22,17,19,1}, {24,21,24,16,2}, {9,7,6,6,6}, {13,26,11,27,2}, + // {24,10,19,12,4}, {22,17,22,9,2}, {17,14,14,11,1}, {13,4,13,3,1}, {15,18,15,17,1}, {29,30,29,24,1}, + // {29,29,20,17,2}, {6,12,2,27,2}, {18,17,14,13,2}, {11,27,11,26,4}, {22,12,3,18,3}, {15,13,13,9,1}, {12,20,7,18,1}, + // {16,6,15,9,1}, {3,6,1,7,1}, {12,17,11,19,1}, {15,8,8,18,7}, {11,19,11,5,3}, {17,20,16,23,3}, {12,6,9,13,1}, + // {2,1,1,2,1}, {14,26,13,21,3}, {25,16,16,14,3}, {30,14,29,14,1}, {27,25,15,22,4}, {13,10,8,7,2}, {18,19,13,14,1}, + // {28,28,28,22,3}, {8,14,8,11,1}, {23,28,22,24,2}, {8,2,3,18,2}, {22,24,22,23,7}, {20,17,15,16,1}, {8,11,6,4,4}, + // {25,13,23,13,2}, {18,18,16,15,1}, {20,16,16,15,1}, {18,20,14,26,3}, {17,12,17,8,1}, {1,5,1,3,1}, {22,13,13,20,2}, + // {17,16,17,14,3}, {27,17,25,17,2}, {8,23,6,29,2}, {15,4,14,18,1}, {10,24,10,17,4}, {25,30,25,28,1}, {3,22,1,29,1}, + // {24,8,23,17,1}, {26,3,26,1,1}, {18,22,18,17,2}, {9,17,8,10,2}, {29,22,29,2,2}, {19,4,5,10,3}, {3,28,3,27,1}, + // {12,15,11,18,1}, {30,3,28,4,1}, {7,9,7,8,1}, {24,15,8,14,7}, {30,6,20,16,1}, {18,18,1,10,1}, {30,20,28,21,1}, + // {15,15,13,14,1}, {6,3,5,1,1}, {3,8,1,17,1}, {3,2,2,2,2}, {19,28,18,20,1}, {20,20,20,17,2}, {21,30,19,29,1}, + // {12,19,12,13,1}, {29,10,29,4,2}, {20,16,20,14,1}, {15,9,11,16,2}, {8,13,6,26,4}, {13,11,12,8,2}, {17,27,17,26,4}, + // {29,29,14,12,1}, {29,2,28,3,2}, {9,15,7,9,4}, {27,28,12,30,1}, {14,30,2,28,1}, {19,12,18,14,1}, {26,5,24,15,5}, + // {2,24,2,2,2}, {6,21,5,21,1}, {22,16,9,17,2}, {16,19,15,17,1}, {2,29,2,28,2}, {25,11,24,1,1}, {16,30,16,29,1}, + // {14,20,14,17,3}, {15,14,11,17,3}, {18,17,16,21,1}, {17,8,17,4,2}, {11,4,11,3,3}, {25,16,9,17,6}, {18,8,18,6,6}, + // {17,22,17,19,1}, {8,20,3,11,3}, {20,17,4,17,1}, {29,12,12,19,2}, {14,29,14,28,2}, {12,18,10,18,1}, + // {13,15,13,11,2}, {18,15,14,15,2}, {19,17,17,19,1}, {22,17,12,16,6}, {30,22,29,18,1}, {30,2,29,20,1}, + // {12,3,1,1,1}, {4,7,1,7,1}, {27,10,21,13,4}, {18,21,18,13,3}, {12,4,3,6,2}, {12,10,9,3,2}, {3,28,2,29,2}, + // {22,2,20,5,2}, {27,18,20,3,3}, {6,24,6,23,1}, {27,26,9,16,4}, {5,18,5,11,5}, {20,14,15,12,3}, {19,16,19,15,1}, + // {27,4,21,9,4}, {3,19,2,29,1}, {20,24,18,22,1}, {18,7,18,2,1}, {28,30,28,28,1}, {11,24,10,9,1}, {21,18,21,14,3}, + // {27,19,26,18,2}, {16,18,10,6,6}, {11,18,5,19,1}, {24,16,22,16,1}, {17,15,17,9,5}, {27,29,20,11,2}, + // {29,25,28,22,1}, {21,11,21,5,1}, {12,15,8,16,2}, {2,29,1,30,1}, {18,12,4,21,3}, {18,9,11,13,3}, {18,3,10,21,3}, + // {17,11,16,16,1}, {15,17,13,14,1}, {7,7,7,5,5}, {9,29,5,18,2}, {10,11,10,6,6}, {28,26,25,26,1}, {19,30,8,20,1}, + // {8,15,7,29,2}, {21,18,19,17,1}, {2,22,1,22,1}, {12,20,4,17,1}, {27,8,4,14,2}, {26,10,25,13,1}, {19,13,19,8,3}, + // {12,16,7,18,7}, {20,26,12,3,3}, {6,10,3,10,2}, {25,25,25,21,2}, {12,3,7,16,2}, {8,4,4,17,4}, {12,20,5,8,5}, + // {22,15,8,13,7}, {12,13,12,8,2}, {20,15,19,13,1}, {30,5,29,8,1}, {14,29,13,23,2}, {18,19,9,10,7}, {2,11,1,10,1}, + // {12,13,12,11,1}, {27,15,9,5,4}, {13,12,7,17,2}, {8,17,1,26,1}, {20,24,11,12,4}, {12,24,10,22,6}, {19,29,14,20,1}, + // {20,27,20,25,2}, {9,25,8,27,1}, {7,11,5,11,1}, {20,11,11,8,1}, {9,8,9,5,1}, {27,9,25,10,1}, {30,20,22,20,1}, + // {26,21,26,20,1}, {30,14,27,16,1}, {12,16,11,19,3}, {7,28,6,29,1}, {17,23,17,22,2}, {12,17,2,2,1}, + // {17,14,17,13,1}, {18,12,16,16,1}, {7,23,7,17,1}, {25,12,9,15,4}, {16,6,16,5,5}, {8,16,7,16,7}, {6,7,5,7,5}, + // {15,13,15,12,2}, {13,15,13,13,3}, {16,12,16,11,1}, {18,15,15,14,3}, {17,8,14,5,4}, {9,26,6,22,5}, + // {17,16,14,17,3}, {25,1,24,2,1}, {14,16,14,15,1}, {24,22,4,23,4}, {30,29,27,29,1}, {17,18,17,17,1}, + // {19,30,19,28,1}, {21,27,21,23,3}, {16,18,15,20,1}, {27,27,13,12,4}, {30,25,27,26,1}, {4,21,3,7,1}, {10,5,10,4,4}, + // {14,14,5,3,1}, {23,6,21,3,3}, {9,20,2,15,2}, {23,9,20,13,1}, {15,14,12,3,3}, {19,25,19,18,4}, {27,25,24,22,4}, + // {15,15,15,11,1}, {17,16,14,13,1}, {12,18,12,17,1}, {30,3,30,2,1}, {21,20,18,28,3}, {25,25,7,14,5}, {3,11,2,3,2}, + // {25,5,9,21,4}, {6,15,4,28,3}, {9,9,3,3,3}, {16,19,14,16,2}, {10,25,10,20,1}, {2,17,2,15,1}, {17,15,15,16,1}, + // {20,15,19,15,1}, {22,2,22,1,1}, {15,19,15,18,1}, {15,16,10,12,1}, {28,2,23,14,2}, {11,3,9,2,1}}; thresholds_ = + // 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+ + // Without data augmentation + box_params_ = { + {17, 12, 18, 15, 2}, {13, 5, 14, 7, 5}, {21, 16, 16, 14, 1}, {27, 18, 11, 20, 3}, {17, 16, 13, 19, 2}, + {18, 18, 24, 16, 5}, {12, 10, 11, 25, 6}, {14, 14, 17, 13, 1}, {7, 4, 4, 15, 4}, {27, 23, 27, 8, 4}, + {19, 19, 13, 6, 6}, {14, 10, 15, 16, 1}, {13, 12, 15, 22, 1}, {8, 3, 22, 27, 3}, {13, 8, 19, 13, 1}, + {18, 17, 16, 12, 1}, {27, 25, 7, 11, 4}, {24, 20, 20, 15, 2}, {16, 14, 24, 3, 3}, {23, 7, 18, 18, 7}, + {8, 2, 7, 1, 1}, {17, 17, 28, 26, 3}, {17, 17, 13, 10, 2}, {10, 10, 18, 11, 1}, {11, 7, 28, 22, 2}, + {18, 15, 13, 15, 1}, {7, 3, 14, 20, 3}, {17, 14, 19, 15, 1}, {14, 14, 12, 8, 2}, {14, 13, 12, 11, 1}, + {21, 19, 9, 19, 2}, {4, 3, 28, 10, 3}, {27, 26, 27, 26, 4}, {19, 19, 22, 19, 2}, {12, 12, 25, 20, 1}, + {19, 15, 12, 12, 1}, {28, 23, 21, 21, 2}, {10, 7, 15, 18, 2}, {12, 10, 7, 3, 3}, {21, 19, 16, 15, 1}, + {19, 18, 20, 17, 1}, {26, 19, 2, 7, 2}, {18, 15, 2, 22, 2}, {24, 24, 26, 22, 5}, {15, 15, 26, 19, 1}, + {13, 11, 19, 20, 1}, {5, 4, 14, 10, 4}, {15, 15, 7, 4, 2}, {13, 11, 16, 7, 1}, {15, 15, 22, 18, 1}, + {24, 23, 8, 4, 4}, {13, 11, 11, 14, 1}, {4, 3, 19, 19, 3}, {22, 19, 12, 10, 1}, {24, 15, 27, 22, 2}, + {12, 10, 13, 10, 1}, {11, 9, 25, 29, 2}, {15, 15, 21, 10, 1}, {19, 18, 16, 19, 1}, {29, 24, 13, 8, 2}, + {17, 16, 16, 20, 1}, {12, 12, 17, 15, 1}, {28, 2, 4, 11, 2}, {7, 5, 25, 19, 3}, {22, 20, 13, 16, 1}, + {14, 13, 16, 17, 1}, {10, 8, 3, 11, 3}, {18, 17, 7, 11, 2}, {27, 25, 11, 22, 2}, {5, 3, 26, 28, 3}, + {28, 27, 13, 13, 3}, {22, 20, 20, 28, 3}, {12, 5, 6, 2, 2}, {14, 13, 18, 16, 1}, {17, 3, 29, 25, 2}, + {20, 19, 20, 19, 1}, {15, 14, 12, 15, 1}, {12, 12, 14, 13, 1}, {17, 10, 14, 26, 3}, {11, 6, 15, 12, 6}, + {9, 9, 22, 19, 1}, {19, 19, 18, 14, 1}, {23, 12, 15, 18, 2}, {12, 11, 15, 14, 1}, {28, 27, 2, 9, 2}, + {11, 11, 19, 11, 7}, {13, 13, 29, 23, 2}, {27, 22, 19, 17, 3}, {17, 17, 3, 2, 2}, {4, 3, 6, 3, 3}, + {19, 16, 15, 16, 1}, {22, 20, 5, 9, 2}, {14, 13, 6, 9, 2}, {17, 13, 16, 16, 2}, {24, 12, 18, 6, 6}, + {20, 18, 14, 15, 2}, {20, 18, 9, 13, 1}, {18, 17, 20, 8, 2}, {10, 9, 15, 15, 2}, {13, 12, 7, 26, 2}, + {13, 11, 12, 19, 2}, {15, 2, 2, 29, 2}, {15, 14, 12, 13, 1}, {20, 19, 30, 26, 1}, {28, 28, 26, 4, 3}, + {16, 15, 13, 12, 1}, {18, 17, 11, 25, 2}, {3, 1, 17, 24, 1}, {21, 19, 18, 22, 1}, {9, 9, 13, 8, 2}, + {19, 16, 18, 16, 1}, {21, 17, 22, 20, 1}, {13, 13, 4, 3, 3}, {24, 21, 15, 9, 1}, {24, 19, 25, 17, 6}, + {4, 3, 14, 14, 2}, {17, 14, 13, 19, 1}, {7, 4, 19, 16, 3}, {4, 1, 20, 5, 1}, {15, 12, 13, 14, 3}, + {19, 19, 26, 21, 2}, {11, 10, 26, 18, 5}, {17, 17, 16, 13, 1}, {19, 19, 16, 11, 1}, {4, 4, 26, 23, 4}, + {14, 14, 19, 13, 5}, {10, 8, 13, 13, 2}, {14, 14, 12, 10, 1}, {29, 26, 24, 19, 2}, {26, 19, 9, 19, 5}, + {16, 16, 23, 17, 1}, {4, 3, 13, 4, 3}, {13, 7, 16, 21, 2}, {17, 16, 16, 17, 1}, {29, 5, 15, 18, 2}, + {29, 23, 2, 5, 2}, {9, 9, 17, 14, 2}, {25, 25, 26, 22, 5}, {13, 13, 21, 20, 1}, {23, 7, 12, 20, 6}, + {6, 6, 8, 3, 3}, {13, 13, 19, 17, 1}, {25, 22, 21, 20, 1}, {24, 23, 17, 15, 2}, {20, 17, 8, 4, 1}, + {11, 10, 19, 17, 1}, {9, 6, 11, 9, 1}, {25, 24, 9, 14, 1}, {18, 13, 20, 14, 3}, {26, 25, 23, 23, 5}, + {14, 11, 20, 4, 4}, {28, 25, 7, 13, 3}, {13, 12, 13, 12, 1}, {7, 2, 29, 2, 2}, {16, 16, 17, 8, 5}, + {20, 19, 6, 12, 3}, {19, 19, 7, 6, 6}, {20, 19, 13, 14, 1}, {19, 16, 24, 29, 2}, {8, 4, 15, 13, 1}, + {7, 2, 9, 10, 2}, {15, 14, 14, 13, 1}, {18, 18, 13, 11, 1}, {8, 5, 19, 23, 2}, {3, 1, 13, 14, 1}, + {23, 16, 20, 14, 1}, {17, 13, 15, 18, 2}, {16, 9, 16, 14, 5}, {15, 15, 28, 27, 3}, {18, 16, 20, 19, 1}, + {16, 16, 17, 11, 2}, {30, 10, 1, 19, 1}, {12, 9, 19, 23, 2}, {25, 21, 13, 13, 1}, {9, 5, 23, 24, 5}, + {13, 13, 20, 18, 1}, {13, 12, 13, 13, 3}, {29, 25, 18, 2, 2}, {30, 25, 30, 26, 1}, {16, 15, 20, 11, 1}, + {18, 18, 16, 14, 1}, {15, 5, 18, 7, 4}, {16, 15, 13, 19, 1}, {26, 16, 24, 9, 5}, {1, 1, 28, 5, 1}, + {20, 20, 17, 16, 1}, {15, 10, 19, 17, 4}, {12, 10, 9, 5, 1}, {30, 28, 29, 29, 1}, {29, 27, 17, 18, 2}, + {17, 15, 29, 27, 2}, {9, 9, 29, 28, 2}, {23, 21, 24, 22, 1}, {22, 1, 2, 1, 1}, {20, 20, 4, 1, 1}, + {5, 4, 30, 25, 1}, {20, 17, 8, 12, 7}, {10, 3, 7, 17, 3}, {21, 14, 17, 15, 5}, {14, 13, 10, 8, 1}, + {4, 4, 21, 13, 3}, {30, 24, 1, 10, 1}, {15, 14, 17, 16, 3}, {21, 20, 23, 15, 3}, {17, 17, 20, 18, 3}, + {12, 12, 11, 6, 5}, {15, 12, 15, 17, 1}, {25, 16, 9, 25, 6}, {22, 22, 28, 27, 3}, {5, 3, 8, 3, 3}, + {9, 9, 5, 1, 1}, {30, 29, 12, 23, 1}, {20, 5, 21, 9, 5}, {15, 15, 21, 20, 1}, {11, 10, 17, 23, 2}, + {16, 15, 11, 13, 1}, {16, 16, 12, 10, 1}, {15, 14, 6, 3, 3}, {2, 1, 4, 1, 1}, {15, 11, 16, 15, 1}, + {24, 24, 6, 2, 2}, {8, 6, 15, 12, 1}, {21, 1, 27, 30, 1}, {17, 14, 10, 16, 3}, {13, 7, 9, 7, 7}, + {22, 19, 17, 17, 1}, {16, 14, 14, 13, 2}, {14, 13, 21, 23, 1}, {18, 15, 2, 7, 2}, {3, 1, 25, 24, 1}, + {24, 7, 20, 14, 7}, {26, 24, 25, 19, 2}, {6, 6, 25, 23, 6}, {15, 15, 24, 17, 7}, {22, 16, 14, 15, 1}, + {17, 17, 25, 23, 1}, {12, 2, 18, 26, 2}, {30, 26, 30, 11, 1}, {22, 16, 8, 14, 5}, {9, 8, 16, 20, 1}, + {4, 2, 14, 13, 2}, {28, 27, 7, 8, 1}, {10, 9, 22, 24, 1}, {14, 13, 16, 18, 3}, {28, 3, 26, 15, 2}, + {12, 10, 15, 15, 1}, {18, 17, 17, 15, 1}, {30, 28, 10, 14, 1}, {30, 28, 14, 30, 1}, {30, 7, 18, 13, 1}, + {3, 2, 19, 20, 1}, {16, 14, 19, 13, 2}, {11, 5, 9, 27, 4}, {16, 15, 19, 15, 2}, {24, 18, 22, 19, 7}, + {12, 12, 17, 12, 1}, {28, 28, 5, 1, 1}, {4, 2, 29, 30, 1}, {27, 27, 11, 8, 1}, {8, 8, 3, 1, 1}, + {15, 15, 10, 8, 3}, {12, 11, 27, 18, 4}, {25, 22, 6, 8, 6}, {15, 15, 3, 2, 2}, {19, 17, 22, 19, 1}, + {24, 24, 21, 16, 2}, {9, 6, 7, 6, 6}, {13, 11, 26, 27, 2}, {24, 19, 10, 12, 4}, {22, 22, 17, 9, 2}, + {17, 14, 14, 11, 1}, {13, 13, 4, 3, 1}, {15, 15, 18, 17, 1}, {29, 29, 30, 24, 1}, {29, 20, 29, 17, 2}, + {6, 2, 12, 27, 2}, {18, 14, 17, 13, 2}, {11, 11, 27, 26, 4}, {22, 3, 12, 18, 3}, {15, 13, 13, 9, 1}, + {12, 7, 20, 18, 1}, {16, 15, 6, 9, 1}, {3, 1, 6, 7, 1}, {12, 11, 17, 19, 1}, {15, 8, 8, 18, 7}, + {11, 11, 19, 5, 3}, {17, 16, 20, 23, 3}, {12, 9, 6, 13, 1}, {2, 1, 1, 2, 1}, {14, 13, 26, 21, 3}, + {25, 16, 16, 14, 3}, {30, 29, 14, 14, 1}, {27, 15, 25, 22, 4}, {13, 8, 10, 7, 2}, {18, 13, 19, 14, 1}, + {28, 28, 28, 22, 3}, {8, 8, 14, 11, 1}, {23, 22, 28, 24, 2}, {8, 3, 2, 18, 2}, {22, 22, 24, 23, 7}, + {20, 15, 17, 16, 1}, {8, 6, 11, 4, 4}, {25, 23, 13, 13, 2}, {18, 16, 18, 15, 1}, {20, 16, 16, 15, 1}, + {18, 14, 20, 26, 3}, {17, 17, 12, 8, 1}, {1, 1, 5, 3, 1}, {22, 13, 13, 20, 2}, {17, 17, 16, 14, 3}, + {27, 25, 17, 17, 2}, {8, 6, 23, 29, 2}, {15, 14, 4, 18, 1}, {10, 10, 24, 17, 4}, {25, 25, 30, 28, 1}, + {3, 1, 22, 29, 1}, {24, 23, 8, 17, 1}, {26, 26, 3, 1, 1}, {18, 18, 22, 17, 2}, {9, 8, 17, 10, 2}, + {29, 29, 22, 2, 2}, {19, 5, 4, 10, 3}, {3, 3, 28, 27, 1}, {12, 11, 15, 18, 1}, {30, 28, 3, 4, 1}, + {7, 7, 9, 8, 1}, {24, 8, 15, 14, 7}, {30, 20, 6, 16, 1}, {18, 1, 18, 10, 1}, {30, 28, 20, 21, 1}, + {15, 13, 15, 14, 1}, {6, 5, 3, 1, 1}, {3, 1, 8, 17, 1}, {3, 2, 2, 2, 2}, {19, 18, 28, 20, 1}, + {20, 20, 20, 17, 2}, {21, 19, 30, 29, 1}, {12, 12, 19, 13, 1}, {29, 29, 10, 4, 2}, {20, 20, 16, 14, 1}, + {15, 11, 9, 16, 2}, {8, 6, 13, 26, 4}, {13, 12, 11, 8, 2}, {17, 17, 27, 26, 4}, {29, 14, 29, 12, 1}, + {29, 28, 2, 3, 2}, {9, 7, 15, 9, 4}, {27, 12, 28, 30, 1}, {14, 2, 30, 28, 1}, {19, 18, 12, 14, 1}, + {26, 24, 5, 15, 5}, {2, 2, 24, 2, 2}, {6, 5, 21, 21, 1}, {22, 9, 16, 17, 2}, {16, 15, 19, 17, 1}, + {2, 2, 29, 28, 2}, {25, 24, 11, 1, 1}, {16, 16, 30, 29, 1}, {14, 14, 20, 17, 3}, {15, 11, 14, 17, 3}, + {18, 16, 17, 21, 1}, {17, 17, 8, 4, 2}, {11, 11, 4, 3, 3}, {25, 9, 16, 17, 6}, {18, 18, 8, 6, 6}, + {17, 17, 22, 19, 1}, {8, 3, 20, 11, 3}, {20, 4, 17, 17, 1}, {29, 12, 12, 19, 2}, {14, 14, 29, 28, 2}, + {12, 10, 18, 18, 1}, {13, 13, 15, 11, 2}, {18, 14, 15, 15, 2}, {19, 17, 17, 19, 1}, {22, 12, 17, 16, 6}, + {30, 29, 22, 18, 1}, {30, 29, 2, 20, 1}, {12, 1, 3, 1, 1}, {4, 1, 7, 7, 1}, {27, 21, 10, 13, 4}, + {18, 18, 21, 13, 3}, {12, 3, 4, 6, 2}, {12, 9, 10, 3, 2}, {3, 2, 28, 29, 2}, {22, 20, 2, 5, 2}, + {27, 20, 18, 3, 3}, {6, 6, 24, 23, 1}, {27, 9, 26, 16, 4}, {5, 5, 18, 11, 5}, {20, 15, 14, 12, 3}, + {19, 19, 16, 15, 1}, {27, 21, 4, 9, 4}, {3, 2, 19, 29, 1}, {20, 18, 24, 22, 1}, {18, 18, 7, 2, 1}, + {28, 28, 30, 28, 1}, {11, 10, 24, 9, 1}, {21, 21, 18, 14, 3}, {27, 26, 19, 18, 2}, {16, 10, 18, 6, 6}, + {11, 5, 18, 19, 1}, {24, 22, 16, 16, 1}, {17, 17, 15, 9, 5}, {27, 20, 29, 11, 2}, {29, 28, 25, 22, 1}, + {21, 21, 11, 5, 1}, {12, 8, 15, 16, 2}, {2, 1, 29, 30, 1}, {18, 4, 12, 21, 3}, {18, 11, 9, 13, 3}, + {18, 10, 3, 21, 3}, {17, 16, 11, 16, 1}, {15, 13, 17, 14, 1}, {7, 7, 7, 5, 5}, {9, 5, 29, 18, 2}, + {10, 10, 11, 6, 6}, {28, 25, 26, 26, 1}, {19, 8, 30, 20, 1}, {8, 7, 15, 29, 2}, {21, 19, 18, 17, 1}, + {2, 1, 22, 22, 1}, {12, 4, 20, 17, 1}, {27, 4, 8, 14, 2}, {26, 25, 10, 13, 1}, {19, 19, 13, 8, 3}, + {12, 7, 16, 18, 7}, {20, 12, 26, 3, 3}, {6, 3, 10, 10, 2}, {25, 25, 25, 21, 2}, {12, 7, 3, 16, 2}, + {8, 4, 4, 17, 4}, {12, 5, 20, 8, 5}, {22, 8, 15, 13, 7}, {12, 12, 13, 8, 2}, {20, 19, 15, 13, 1}, + {30, 29, 5, 8, 1}, {14, 13, 29, 23, 2}, {18, 9, 19, 10, 7}, {2, 1, 11, 10, 1}, {12, 12, 13, 11, 1}, + {27, 9, 15, 5, 4}, {13, 7, 12, 17, 2}, {8, 1, 17, 26, 1}, {20, 11, 24, 12, 4}, {12, 10, 24, 22, 6}, + {19, 14, 29, 20, 1}, {20, 20, 27, 25, 2}, {9, 8, 25, 27, 1}, {7, 5, 11, 11, 1}, {20, 11, 11, 8, 1}, + {9, 9, 8, 5, 1}, {27, 25, 9, 10, 1}, {30, 22, 20, 20, 1}, {26, 26, 21, 20, 1}, {30, 27, 14, 16, 1}, + {12, 11, 16, 19, 3}, {7, 6, 28, 29, 1}, {17, 17, 23, 22, 2}, {12, 2, 17, 2, 1}, {17, 17, 14, 13, 1}, + {18, 16, 12, 16, 1}, {7, 7, 23, 17, 1}, {25, 9, 12, 15, 4}, {16, 16, 6, 5, 5}, {8, 7, 16, 16, 7}, + {6, 5, 7, 7, 5}, {15, 15, 13, 12, 2}, {13, 13, 15, 13, 3}, {16, 16, 12, 11, 1}, {18, 15, 15, 14, 3}, + {17, 14, 8, 5, 4}, {9, 6, 26, 22, 5}, {17, 14, 16, 17, 3}, {25, 24, 1, 2, 1}, {14, 14, 16, 15, 1}, + {24, 4, 22, 23, 4}, {30, 27, 29, 29, 1}, {17, 17, 18, 17, 1}, {19, 19, 30, 28, 1}, {21, 21, 27, 23, 3}, + {16, 15, 18, 20, 1}, {27, 13, 27, 12, 4}, {30, 27, 25, 26, 1}, {4, 3, 21, 7, 1}, {10, 10, 5, 4, 4}, + {14, 5, 14, 3, 1}, {23, 21, 6, 3, 3}, {9, 2, 20, 15, 2}, {23, 20, 9, 13, 1}, {15, 12, 14, 3, 3}, + {19, 19, 25, 18, 4}, {27, 24, 25, 22, 4}, {15, 15, 15, 11, 1}, {17, 14, 16, 13, 1}, {12, 12, 18, 17, 1}, + {30, 30, 3, 2, 1}, {21, 18, 20, 28, 3}, {25, 7, 25, 14, 5}, {3, 2, 11, 3, 2}, {25, 9, 5, 21, 4}, + {6, 4, 15, 28, 3}, {9, 3, 9, 3, 3}, {16, 14, 19, 16, 2}, {10, 10, 25, 20, 1}, {2, 2, 17, 15, 1}, + {17, 15, 15, 16, 1}, {20, 19, 15, 15, 1}, {22, 22, 2, 1, 1}, {15, 15, 19, 18, 1}, {15, 10, 16, 12, 1}, + {28, 23, 2, 14, 2}, {11, 9, 3, 2, 1}, + }; + thresholds_ = { + 14.45, 4.15, 7.75, 9.65, 2.25, 0.15, 0.45, -0.95, 3.65, -1.75, 1.05, 5.45, -0.05, -2.65, + 3.35, 1.65, -1.55, 2.85, 3.05, 22.05, -3.65, -0.15, -0.55, -0.05, 3.25, -2.85, -1.25, 10.45, + -1.05, 1.25, 3.15, 2.05, -0.55, -1.25, 3.45, 4.35, 2.45, 2.55, 1.35, 1.25, 2.75, -0.15, + 8.35, 0.35, -1.25, 0.75, -0.45, -0.05, 0.85, 3.65, 1.55, 1.75, -0.35, 1.35, 4.85, -2.25, + 0.25, -2.15, 3.35, 1.95, 6.25, 0.35, 24.45, -1.15, 0.85, -1.95, 5.15, 1.35, 0.85, 0.35, + -0.45, 4.95, -0.25, 2.45, 11.75, 0.85, -1.65, 0.05, 4.05, -0.35, -0.95, -0.25, 49.35, 0.85, + 1.95, 0.25, 1.15, -2.65, -0.25, 0.85, -5.65, 1.15, 3.05, 4.05, 7.35, 9.05, 0.35, 1.65, + 1.65, 2.55, 6.95, 1.75, 0.85, -1.15, 1.35, 5.45, 1.35, -2.35, -0.15, 0.85, -3.05, 0.05, + -0.35, -0.65, 11.65, -0.85, 1.15, 2.35, -9.25, 16.05, -1.45, 1.95, 0.35, -0.35, 0.15, 0.25, + -1.35, 0.65, -4.05, -2.25, 1.05, -0.05, -1.55, 0.25, 69.45, 0.15, -1.25, -1.85, -0.65, 8.75, + -0.95, 1.95, 1.05, -1.45, 2.15, -1.85, -1.75, -2.95, 2.65, 0.65, -1.05, 4.35, 0.25, 19.65, + 0.35, 1.65, 0.65, 2.75, 2.85, -10.95, 3.65, -4.15, 0.25, -0.65, -2.25, 3.75, 35.75, 3.15, + -0.55, 1.95, -6.55, 88.35, 7.25, 1.75, -4.15, 0.25, 0.25, 0.65, 3.75, 1.65, 2.85, 42.15, + 11.75, -1.25, -8.25, 0.05, 2.15, 0.65, -1.55, -2.75, 1.15, -0.15, -0.75, 16.85, 1.15, 1.45, + 15.35, 19.45, 8.65, -1.25, 0.25, 2.15, 0.15, 2.85, -2.25, 1.75, -15.15, 4.15, -0.45, -8.25, + 1.25, -0.85, 3.55, 0.45, -1.25, 9.65, 1.25, 3.15, -2.05, -6.85, -0.05, 3.25, 7.05, 2.35, + -1.45, -1.05, 20.25, 1.15, 1.35, 1.05, 5.15, 2.55, 0.55, 0.55, -0.15, 0.65, -28.35, 3.85, + 2.05, -1.15, 3.05, -0.95, -1.55, -0.35, 101.95, 0.35, -2.05, -2.15, 4.25, 105.15, 1.15, 27.45, + 30.15, 18.45, -2.45, 1.85, 2.95, -3.75, -0.65, 0.05, 0.25, 34.45, -2.05, 0.25, 3.25, 2.05, + 2.85, 3.45, 20.95, 1.45, -1.95, -0.35, -6.85, 1.15, -31.95, 11.85, 2.75, 0.15, 8.35, 1.15, + 2.15, -1.15, -1.05, 2.45, 1.45, 0.15, -1.65, 41.85, 0.35, 0.65, -0.35, 0.25, 56.75, 23.55, + 88.85, -7.25, 1.05, 0.75, -1.05, -1.65, -9.75, -16.95, -0.05, -10.05, 34.15, 14.75, -0.95, 1.45, + 4.85, -0.05, -0.35, 0.75, 64.75, 24.25, -0.35, -13.65, 2.85, 1.75, -0.35, 0.25, -12.15, 108.05, + -0.35, -3.35, 1.95, -0.35, 21.25, -20.05, 95.85, -1.05, -17.75, -0.55, 2.75, 0.65, 0.75, -1.85, + 2.65, -2.15, 1.05, -0.05, 4.25, 3.75, -13.55, -0.05, 105.95, 0.45, 3.05, 9.35, 79.25, 1.75, + 7.65, -0.45, 0.95, 79.15, 28.05, 0.05, 0.65, -0.35, 0.95, 2.05, 1.15, 2.75, -1.65, 8.65, + 3.55, -0.25, -28.95, -7.35, 122.25, 0.55, 4.75, 1.75, 11.15, 0.15, 2.55, 0.05, -7.95, 51.05, + 6.25, 0.05, -1.15, 0.75, 26.65, -1.25, 1.15, -0.55, 0.05, 5.85, 1.55, 2.25, -1.65, -16.85, + -62.65, -1.25, -1.05, -1.55, 1.35, 0.25, -0.65, 0.85, 17.45, 0.25, -9.35, 34.35, 0.95, -0.95, + -10.05, 1.45, -6.05, 93.25, 3.15, -10.85, -1.65, -0.15, -2.45, -0.35, 0.15, 118.15, -81.85, 4.05, + 1.05, -0.85, 152.35, 0.65, 1.35, -12.35, 95.35, -23.25, -0.75, 75.65, 50.85, 47.85, 2.55, 0.55, + 0.15, 0.25, 38.15, -2.65, -1.95, -1.05, 110.25, 35.25, 2.65, 3.65, 18.75, 89.45, -0.55, 0.35, + 0.25, 105.05, 0.25, 1.25, -34.65, -0.55, -0.15, 0.75, -0.15, -0.15, -94.25, -12.05, -15.35, -1.75, + 31.35, 0.15, -2.15, -0.15, -12.05, -0.35, -0.65, -0.55, 28.95, 39.05, 7.05, 0.65, -1.65, 2.85, + 4.85, -1.85, 1.75, -31.65, 0.05, 13.75, -0.35, 0.35, -5.75, 83.85, 0.95, 27.95, -0.25, -19.05, + 2.45, -13.25, 44.05, 51.85, -0.05, 0.05, 79.35, 111.25, -61.65, 3.05, -69.95, 35.65, 62.05, -0.25, + -1.05, -2.95, 0.95, -0.15, -18.15, -18.65, 74.55, 2.65}; + } else { + // With data augmentation + // box_params_ = {}; + // thresholds_ = {}; + + // Without data augmentation + box_params_ = { + {25, 13, 14, 15, 6}, {16, 14, 15, 11, 1}, {14, 7, 14, 8, 6}, {10, 6, 9, 20, 6}, {13, 13, 26, 19, 5}, + {19, 19, 14, 5, 4}, {16, 15, 19, 13, 2}, {26, 21, 26, 12, 5}, {18, 15, 23, 20, 2}, {12, 10, 15, 20, 1}, + {26, 18, 4, 8, 3}, {8, 2, 21, 29, 2}, {19, 17, 16, 19, 1}, {10, 5, 3, 13, 3}, {16, 10, 10, 14, 1}, + {19, 18, 12, 17, 1}, {21, 21, 26, 19, 5}, {6, 5, 7, 5, 5}, {22, 20, 12, 14, 2}, {14, 13, 12, 17, 1}, + {11, 10, 16, 13, 2}, {7, 7, 23, 17, 3}, {27, 25, 13, 8, 4}, {20, 16, 19, 14, 1}, {27, 24, 10, 16, 2}, + {13, 13, 12, 6, 2}, {14, 13, 18, 23, 1}, {14, 11, 8, 1, 1}, {14, 12, 23, 9, 2}, {6, 2, 19, 13, 2}, + {8, 6, 19, 19, 3}, {18, 17, 28, 25, 3}, {29, 25, 28, 22, 2}, {15, 15, 19, 17, 3}, {23, 19, 21, 19, 1}, + {20, 20, 20, 16, 3}, {29, 25, 4, 8, 2}, {17, 16, 6, 25, 2}, {12, 8, 21, 29, 1}, {14, 9, 15, 17, 2}, + {18, 17, 5, 3, 3}, {21, 18, 12, 10, 1}, {17, 14, 14, 14, 2}, {5, 3, 26, 6, 3}, {16, 15, 13, 14, 1}, + {28, 24, 21, 22, 3}, {13, 13, 12, 10, 1}, {22, 21, 3, 11, 3}, {27, 4, 27, 16, 4}, {12, 7, 13, 10, 1}, + {15, 15, 25, 22, 2}, {19, 18, 10, 12, 1}, {17, 17, 16, 9, 2}, {21, 21, 17, 14, 2}, {13, 12, 19, 16, 1}, + {11, 9, 11, 15, 1}, {15, 14, 26, 28, 3}, {17, 17, 22, 20, 1}, {10, 2, 26, 27, 2}, {28, 26, 12, 23, 3}, + {4, 3, 5, 14, 3}, {17, 17, 7, 4, 3}, {19, 17, 15, 15, 1}, {7, 2, 8, 5, 2}, {22, 19, 15, 14, 2}, + {15, 12, 16, 20, 1}, {13, 12, 19, 20, 1}, {17, 17, 10, 8, 2}, {26, 19, 16, 15, 4}, {9, 8, 14, 20, 2}, + {27, 27, 14, 4, 4}, {17, 15, 14, 9, 1}, {5, 5, 4, 3, 3}, {15, 9, 30, 5, 1}, {7, 7, 25, 23, 6}, + {12, 11, 24, 16, 1}, {20, 20, 29, 20, 2}, {19, 15, 18, 19, 1}, {9, 7, 11, 11, 7}, {27, 26, 26, 15, 4}, + {10, 10, 28, 27, 3}, {8, 8, 12, 6, 3}, {21, 16, 23, 22, 1}, {22, 4, 7, 25, 4}, {17, 16, 19, 15, 1}, + {28, 11, 21, 15, 3}, {15, 15, 3, 2, 2}, {16, 14, 16, 17, 3}, {10, 7, 17, 18, 3}, {12, 12, 18, 15, 1}, + {18, 16, 16, 13, 1}, {20, 19, 16, 15, 1}, {16, 11, 15, 11, 1}, {4, 2, 14, 13, 2}, {29, 27, 18, 17, 2}, + {16, 14, 18, 16, 1}, {23, 22, 29, 27, 2}, {18, 18, 13, 11, 1}, {26, 21, 23, 27, 4}, {18, 17, 22, 18, 1}, + {3, 2, 11, 21, 2}, {13, 13, 18, 9, 3}, {15, 14, 14, 5, 2}, {1, 1, 14, 1, 1}, {29, 5, 2, 9, 2}, + {12, 11, 17, 17, 1}, {13, 12, 10, 25, 4}, {5, 1, 13, 25, 1}, {13, 13, 16, 12, 1}, {16, 16, 23, 12, 1}, + {27, 22, 14, 14, 2}, {29, 27, 29, 27, 2}, {23, 22, 6, 4, 4}, {22, 22, 16, 8, 3}, {14, 11, 1, 9, 1}, + {12, 10, 11, 8, 2}, {24, 7, 19, 16, 7}, {5, 2, 29, 20, 2}, {19, 19, 15, 13, 1}, {15, 8, 18, 24, 2}, + {4, 1, 24, 30, 1}, {17, 17, 30, 26, 1}, {9, 7, 8, 5, 2}, {15, 15, 20, 18, 1}, {27, 14, 5, 26, 4}, + {18, 18, 19, 15, 1}, {24, 9, 14, 12, 1}, {20, 18, 6, 10, 1}, {21, 21, 23, 21, 1}, {19, 6, 17, 6, 6}, + {10, 6, 13, 12, 3}, {30, 27, 10, 14, 1}, {9, 6, 5, 3, 3}, {26, 18, 21, 19, 2}, {23, 23, 5, 4, 4}, + {14, 11, 11, 12, 1}, {18, 16, 13, 13, 1}, {7, 3, 8, 16, 3}, {16, 16, 15, 12, 2}, {25, 24, 20, 25, 3}, + {20, 19, 14, 14, 1}, {12, 12, 29, 5, 1}, {23, 13, 17, 13, 5}, {27, 23, 27, 22, 4}, {11, 11, 4, 3, 3}, + {9, 7, 18, 15, 1}, {18, 18, 17, 14, 1}, {28, 6, 2, 17, 2}, {5, 3, 20, 22, 3}, {30, 30, 30, 2, 1}, + {16, 15, 8, 13, 1}, {15, 14, 16, 13, 1}, {28, 27, 5, 5, 3}, {13, 12, 13, 12, 1}, {7, 6, 8, 7, 6}, + {10, 10, 21, 17, 1}, {11, 3, 17, 30, 1}, {16, 9, 17, 14, 7}, {17, 9, 16, 14, 1}, {14, 13, 29, 27, 2}, + {19, 19, 5, 3, 2}, {18, 14, 16, 14, 1}, {10, 8, 23, 25, 2}, {17, 15, 17, 18, 1}, {16, 16, 22, 16, 6}, + {29, 27, 11, 11, 2}, {13, 7, 9, 11, 1}, {18, 17, 23, 19, 4}, {12, 11, 14, 17, 1}, {13, 11, 23, 18, 2}, + {27, 23, 8, 20, 4}, {18, 18, 18, 11, 4}, {8, 5, 21, 8, 5}, {23, 21, 5, 10, 1}, {16, 16, 16, 12, 1}, + {18, 14, 17, 19, 1}, {16, 16, 27, 24, 2}, {21, 15, 17, 15, 1}, {16, 15, 5, 9, 2}, {24, 1, 16, 30, 1}, + {15, 14, 14, 19, 1}, {19, 12, 12, 14, 2}, {5, 3, 5, 4, 3}, {16, 16, 11, 9, 1}, {16, 6, 9, 18, 6}, + {25, 23, 24, 14, 1}, {5, 5, 26, 17, 5}, {9, 6, 16, 18, 1}, {29, 9, 25, 24, 2}, {25, 24, 22, 30, 1}, + {22, 20, 2, 5, 2}, {27, 25, 1, 11, 1}, {15, 14, 12, 10, 1}, {17, 16, 6, 8, 1}, {28, 23, 8, 7, 3}, + {24, 23, 24, 22, 7}, {7, 5, 18, 20, 3}, {22, 20, 15, 20, 1}, {30, 28, 21, 20, 1}, {3, 2, 18, 18, 2}, + {6, 5, 14, 15, 1}, {15, 15, 18, 16, 1}, {7, 5, 11, 2, 1}, {17, 13, 17, 15, 3}, {12, 7, 15, 15, 5}, + {16, 15, 12, 18, 1}, {14, 14, 26, 25, 5}, {11, 8, 17, 18, 1}, {23, 15, 13, 21, 7}, {10, 10, 9, 2, 2}, + {17, 12, 13, 19, 1}, {20, 19, 25, 22, 1}, {9, 8, 26, 21, 1}, {19, 19, 22, 18, 1}, {8, 3, 15, 12, 1}, + {26, 16, 13, 19, 5}, {24, 21, 12, 13, 1}, {12, 12, 14, 9, 1}, {3, 1, 7, 1, 1}, {16, 15, 9, 3, 3}, + {23, 23, 20, 8, 7}, {24, 22, 16, 15, 1}, {20, 20, 19, 14, 1}, {30, 29, 27, 22, 1}, {27, 4, 17, 16, 4}, + {8, 5, 13, 13, 5}, {19, 10, 8, 16, 3}, {30, 30, 11, 4, 1}, {14, 14, 21, 20, 1}, {14, 13, 11, 13, 1}, + {30, 28, 2, 5, 1}, {17, 12, 29, 24, 2}, {15, 6, 25, 30, 1}, {4, 1, 1, 1, 1}, {12, 5, 16, 20, 5}, + {16, 14, 20, 15, 1}, {6, 6, 17, 9, 3}, {20, 12, 17, 20, 4}, {15, 12, 15, 4, 4}, {28, 22, 20, 21, 3}, + {14, 9, 18, 18, 5}, {26, 23, 1, 5, 1}, {21, 11, 24, 10, 7}, {15, 14, 19, 12, 1}, {27, 11, 29, 16, 1}, + {23, 22, 19, 29, 1}, {2, 2, 30, 29, 1}, {14, 6, 16, 5, 3}, {17, 14, 13, 16, 1}, {19, 15, 14, 16, 1}, + {20, 13, 25, 15, 6}, {19, 11, 18, 12, 5}, {30, 30, 30, 13, 1}, {3, 1, 14, 9, 1}, {20, 1, 17, 18, 1}, + {16, 12, 20, 19, 1}}; + thresholds_ = { + 21.65, 5.65, 4.95, 2.45, 2.25, 0.85, 3.35, 1.75, 4.55, -1.55, 4.55, -5.05, 3.15, 4.85, 9.95, + 1.35, -2.05, -0.15, 1.55, 3.35, 0.25, 0.35, 2.45, 2.75, -1.65, -0.05, -0.75, 0.85, 2.95, -1.65, + -0.05, -0.25, -3.85, -0.05, 3.35, 0.05, -3.55, 2.65, 1.95, 6.35, 0.85, 2.65, 12.45, 0.05, 3.35, + 1.75, -1.05, -1.05, 28.25, 0.35, -0.15, 2.05, 2.55, 0.85, 1.35, 1.15, 1.25, 1.35, 1.85, 3.95, + 0.75, 1.65, -3.15, -6.35, 2.05, -5.15, 1.75, -0.65, -0.65, 1.05, -0.85, 0.85, -0.35, 9.05, 0.75, + -1.75, 0.75, 16.05, 0.35, 0.75, 0.05, 0.05, 3.75, 14.15, -8.95, 67.25, -0.45, 1.65, -1.95, 1.15, + 1.85, 3.95, -1.75, 0.45, -1.55, 1.05, -0.25, -1.05, 3.05, -1.05, 1.95, -0.05, 0.85, 3.05, 34.85, + -0.15, 4.35, -10.65, 2.35, -1.35, 0.05, 1.05, 1.05, -0.15, 0.45, -0.55, 10.45, 1.35, -0.95, 0.45, + -0.85, 1.45, -1.85, 1.65, 2.75, 1.05, 81.45, 3.35, 0.85, 2.65, 9.35, 1.15, 1.35, -1.55, 0.85, + 20.65, 2.05, 12.85, 7.95, 2.25, 0.05, 0.85, 8.75, -8.25, -0.35, 1.65, -3.95, 92.55, 0.55, 0.35, + -0.75, -12.25, 0.55, 1.05, 0.95, 1.15, -43.25, 3.05, 4.35, 7.15, 0.15, 57.95, 4.35, 0.75, 0.05, + 0.05, 5.45, 0.55, 0.95, 20.55, -4.45, 0.75, 4.55, -0.15, 8.65, 42.65, -0.45, -1.25, -1.75, 11.25, + -8.15, 2.85, -2.85, -5.05, 44.65, 1.45, -0.75, 11.85, 2.05, 1.25, 4.45, -1.35, 5.95, 1.35, -2.55, + 5.05, -2.85, 7.35, -1.35, -0.45, 0.45, -11.85, -39.65, 1.65, -0.05, 3.65, -0.35, 0.05, 1.85, -0.45, + -1.75, 3.95, 5.25, -1.05, -11.95, 37.05, -1.15, 1.25, 0.75, -6.05, -1.55, -1.65, 0.85, 0.35, 101.55, + -5.05, 3.65, -2.35, -0.35, -1.65, 0.65, 6.35, 2.85, 5.25, 24.05, 38.15, -1.05, 3.05, 0.35, -16.05, + -1.25, 0.25, 1.95, -0.85, 107.65, -1.55, -0.25, 26.95, 35.95, -4.85, 1.55, 10.85, -7.15, -4.25, -25.15, + 2.75}; + } +} + +void BAD::compute(cv::InputArray _image, + std::vector &keypoints, + cv::OutputArray &_descriptors) { + cv::Mat image = _image.getMat(); + + if (image.empty()) + return; + + if (keypoints.empty()) { + // clean output buffer (it may be reused with "allocated" data) + _descriptors.release(); + return; + } + + assert(image.type() == CV_8UC1); + cv::Mat integral_img; + + // compute the integral image + cv::integral(image, integral_img); + + // Create the output array of descriptors + _descriptors.create((int)keypoints.size(), descriptorSize(), descriptorType()); + + // descriptor storage + cv::Mat descriptors = _descriptors.getMat(); + assert(descriptors.type() == CV_8UC1); + + computeBAD(integral_img, keypoints, descriptors); +} + +void BAD::computeBAD(const cv::Mat &integral_img, + const std::vector &keypoints, + cv::Mat &descriptors) { + assert(!integral_img.empty()); + assert(descriptors.rows == keypoints.size()); + + const int *integral_ptr = integral_img.ptr(); + cv::Size frame_size(integral_img.cols - 1, integral_img.rows - 1); + + /////////////////// Parallel Loop to process descriptors //////////////////// + +#ifndef UPM_BAD_PARALLEL + const cv::Range range(0, keypoints.size()); +#else + cv::parallel_for_(cv::Range(0, int(keypoints.size())), [&](const cv::Range &range){ +#endif + // Get a pointer to the first element in the range + // Get a pointer to the first element in the range + BoxPairParams *box_pair; + float response_fun; + int area_response_fun, kpIdx; + size_t box_pair_idx; + int box1x1, box1y1, box1x2, box1y2, box2x1, box2y1, box2x2, box2y2, bit_idx, side; + uchar byte = 0; + std::vector img_boxes(box_params_.size()); + uchar *d = &descriptors.at(range.start, 0); + + for (kpIdx = range.start; kpIdx < range.end; kpIdx++) { + // Rectify the weak learners coordinates using the keypoint information + // Rectify the weak learners coordinates using the keypoint information + rectifyBoxes(box_params_, img_boxes, keypoints[kpIdx], scale_factor_, patch_size_); + if (isKeypointInTheBorder(keypoints[kpIdx], frame_size, patch_size_, scale_factor_)) { + // Code to process the keypoints in the image margins + for (box_pair_idx = 0; box_pair_idx < box_params_.size(); box_pair_idx++) { + bit_idx = 7 - int(box_pair_idx % 8); + response_fun = computeBadResponse(img_boxes[box_pair_idx], integral_img); + // Set the bit to 1 if the response function is less or equal to the threshod + byte |= (response_fun <= thresholds_[box_pair_idx]) << bit_idx; + // If we filled the byte, save it + if (bit_idx == 0) { + *d = byte; + byte = 0; + d++; + } + } + } else { + // Code to process the keypoints in the image center + box_pair = img_boxes.data(); + for (box_pair_idx = 0; box_pair_idx < box_params_.size(); box_pair_idx++) { + bit_idx = 7 - int(box_pair_idx % 8); + + // For the first box, we calculate its margin coordinates + box1x1 = box_pair->x1 - box_pair->boxRadius; + box1y1 = (box_pair->y1 - box_pair->boxRadius) * integral_img.cols; + box1x2 = box_pair->x1 + box_pair->boxRadius + 1; + box1y2 = (box_pair->y1 + box_pair->boxRadius + 1) * integral_img.cols; + // For the second box, we calculate its margin coordinates + box2x1 = box_pair->x2 - box_pair->boxRadius; + box2y1 = (box_pair->y2 - box_pair->boxRadius) * integral_img.cols; + box2x2 = box_pair->x2 + box_pair->boxRadius + 1; + box2y2 = (box_pair->y2 + box_pair->boxRadius + 1) * integral_img.cols; + side = 1 + (box_pair->boxRadius << 1); + + // Get the difference between the average level of the two boxes + area_response_fun = (integral_ptr[box1y1 + box1x1] // A of Box1 + + integral_ptr[box1y2 + box1x2] // D of Box1 + - integral_ptr[box1y1 + box1x2] // B of Box1 + - integral_ptr[box1y2 + box1x1] // C of Box1 + - integral_ptr[box2y1 + box2x1] // A of Box2 + - integral_ptr[box2y2 + box2x2] // D of Box2 + + integral_ptr[box2y1 + box2x2] // B of Box2 + + integral_ptr[box2y2 + box2x1]); // C of Box2 + + // Set the bit to 1 if the response function is less or equal to the threshod + byte |= (area_response_fun <= (thresholds_[box_pair_idx] * (side * side))) << bit_idx; + box_pair++; + // If we filled the byte, save it + if (bit_idx == 0) { + *d = byte; + byte = 0; + d++; + } + } // End of for each dimension + } // End of else (of pixels in the image center) + } // End of for each keypoint +#ifdef UPM_BAD_PARALLEL + }); +#endif + } // namespace upm +} diff --git a/localization/interest_point/src/HashSIFT.cpp b/localization/interest_point/src/HashSIFT.cpp new file mode 100644 index 0000000000..0849c25209 --- /dev/null +++ b/localization/interest_point/src/HashSIFT.cpp @@ -0,0 +1,101 @@ +/** + * @copyright 2021 Xoan Iago Suarez Canosa. All rights reserved. + * Constact: iago.suarez@thegraffter.com + * Software developed in the PhD: Low-level vision for resource-limited devices + */ +#include + +namespace upm { + +HashSIFT::HashSIFT(float cropping_scale, + HashSiftSize n_bits, + double sigma) { + if (n_bits == SIZE_512_BITS) { + #include + b_matrix_ = cv::Mat(512, 129, CV_64FC1, HASH_SIFT_512_VALS); + b_matrix_.convertTo(b_matrix_, CV_32FC1); + } else { + #include + b_matrix_ = cv::Mat(256, 129, CV_64FC1, HASH_SIFT_256_VALS); + b_matrix_.convertTo(b_matrix_, CV_32FC1); + } + + nbits_ = b_matrix_.rows; + transp_b_matrix_ = b_matrix_.t(); + + // 1 / 6.75f + sift_ = std::make_shared(1 / 6.0, cropping_scale, sigma); +} + +cv::Ptr HashSIFT::create(float cropping_scale, + HashSiftSize n_bits, + double sigma) { + return cv::makePtr(cropping_scale, n_bits, sigma); +} + +void HashSIFT::compute(cv::InputArray& _image, std::vector& keypoints, cv::OutputArray& _descriptors) { + cv::Mat image = _image.getMat(); + + if (image.empty()) + return; + + if (keypoints.empty()) { + // clean output buffer (it may be reused with "allocated" data) + _descriptors.release(); + return; + } + + assert(image.type() == CV_8UC1); + + // Create the output array of descriptors + _descriptors.create((int)keypoints.size(), descriptorSize(), descriptorType()); + cv::Mat descriptors = _descriptors.getMat(); + cv::Mat sift_descriptors(keypoints.size(), 129, CV_32FC1); + sift_descriptors.col(0).setTo(1); + cv::Mat wlInt8tResponses(keypoints.size(), 129, CV_8UC1); + +#ifndef UPM_PARALLEL_HASH_SIFT + const cv::Range range(0, keypoints.size()); +#else + parallel_for_(cv::Range(0, keypoints.size()), [&](const cv::Range &range) { +#endif + cv::Mat patch(sift_->GetPatchSize(), CV_8UC1); + for (int r = range.start; r < range.end; r++) { + PatchSIFT::rectifyPatch(image, keypoints[r], sift_->GetPatchSize(), patch, + sift_->GetCroppingScale()); + sift_->calcSIFTDescriptor(patch, + sift_descriptors(cv::Range(r, r + 1), + cv::Range(1, sift_descriptors.cols))); + } + + // Compute the linear projection and hash + matmulAndSign(sift_descriptors.rowRange(range), descriptors.rowRange(range)); + +#ifdef UPM_PARALLEL_HASH_SIFT + }); +#endif + } // namespace upm + +void HashSIFT::matmulAndSign(const cv::Mat &wlResponses, cv::Mat descriptors) { + assert(wlResponses.rows == descriptors.rows); + cv::Mat tmp = wlResponses * transp_b_matrix_; + float *pTmp = tmp.ptr(); + uint8_t *p_descr = descriptors.ptr(); + uint8_t byte; + int d, b; + for (d = 0; d < descriptors.rows; d++) { + for (b = 0; b < tmp.cols / 8; b++) { + byte = 0; + byte |= (*pTmp++ > 0) << 7; + byte |= (*pTmp++ > 0) << 6; + byte |= (*pTmp++ > 0) << 5; + byte |= (*pTmp++ > 0) << 4; + byte |= (*pTmp++ > 0) << 3; + byte |= (*pTmp++ > 0) << 2; + byte |= (*pTmp++ > 0) << 1; + byte |= (*pTmp++ > 0) << 0; + *p_descr++ = byte; + } // End of for each bit + } // End of for each keypoint +} +} diff --git a/localization/interest_point/src/PatchSIFT.cpp b/localization/interest_point/src/PatchSIFT.cpp new file mode 100644 index 0000000000..86c31c8b3f --- /dev/null +++ b/localization/interest_point/src/PatchSIFT.cpp @@ -0,0 +1,292 @@ +/** + * @copyright 2021 Xoan Iago Suarez Canosa. All rights reserved. + * Constact: iago.suarez@thegraffter.com + * Software developed in the PhD: Low-level vision for resource-limited devices + */ +#include + +namespace upm { + +void PatchSIFT::calcSIFTDescriptor(const cv::Mat &gray, cv::Mat descriptor) { + assert(descriptor.type() == CV_32FC1); + assert(descriptor.rows == 1 && descriptor.cols == descriptorSize()); + assert(gray.channels() == 1); + + int i, j, k, r, c; + + // Step 1: Filter the image using a gaussian filter of size sigma + cv::Mat img; + if (step1_pyramid) { + float sig_diff = sqrtf(std::max(float(sigma) * float(sigma) - SIFT_INIT_SIGMA * SIFT_INIT_SIGMA, 0.01f)); + cv::GaussianBlur(gray, img, cv::Size(), sig_diff, sig_diff); + } else { + img = gray; + } + // Step 2: We assume a pre-oriented and pre-scale patch of fixed size + + // Step 3: Compute the image derivatives + // X and Y derivatives + cv::Mat X(img.rows - 2, img.cols - 2, CV_32FC1); + cv::Mat Y(img.rows - 2, img.cols - 2, CV_32FC1); + // Row and column bins + cv::Mat RBin(img.rows - 2, img.cols - 2, CV_32FC1); + cv::Mat CBin(img.rows - 2, img.cols - 2, CV_32FC1); + + // The radius of the keypoint in pixels + const float cell_width = SIFT_DESCR_SCL_FCTR * (kp_scale * img.cols * 0.5f); + const float cell_height = SIFT_DESCR_SCL_FCTR * (kp_scale * img.rows * 0.5f); + + float *pX = X.ptr(), *pY = Y.ptr(), *pRBin = RBin.ptr(), + *pCBin = CBin.ptr(); + float c_rot, r_rot; + uint8_t *p, *pImg = img.ptr(); + + int img_width = img.cols, pos = 0; + // Compute image derivatives + for (i = 1; i < (img.rows - 1); i++) { + p = pImg + i * img_width + 1; + for (j = 1; j < (img.cols - 1); j++) { + // Compute the derivative using the previous and next pixels + pX[pos] = *(p + 1) - *(p - 1); + pY[pos] = *(p - img_width) - *(p + img_width); + + // Assign each pixels to its bin + c_rot = (j - img.cols / 2.0f) / cell_width; + r_rot = (i - img.rows / 2.0f) / cell_height; + // Check that the indices of the histogram are correct + assert((r_rot + r_bins / 2 - 0.5f) > -2 && (r_rot + r_bins / 2 - 0.5f) <= r_bins); + assert((c_rot + c_bins / 2 - 0.5f) > -2 && (c_rot + c_bins / 2 - 0.5f) <= c_bins); + pRBin[pos] = r_rot + r_bins / 2 - 0.5f; + pCBin[pos] = c_rot + c_bins / 2 - 0.5f; + pos++; + p++; + } + } + + // Compute the gradient direction and magnitude + cv::Mat Mag, Ori; + cv::cartToPolar(X, Y, Mag, Ori); + float *pMag = Mag.ptr(), *pOri = Ori.ptr(); + + // Step 4: Create the gaussian weighting assigned to each pixel + if (step4_gaussian_weight) { + cv::Mat W = cv::Mat::ones(img.rows - 2, img.cols - 2, CV_32FC1); + const float kp_radius = kp_scale * img.rows * 0.5f; + float kernel_sigma = 0.5 * c_bins * SIFT_DESCR_SCL_FCTR * kp_radius; + float dx, dy, dist_to_center2; + float *pW = W.ptr(); + for (r = 0; r < W.rows; r++) { + for (c = 0; c < W.cols; c++) { + dx = r - W.cols / 2.0f; + dy = c - W.rows / 2.0f; + dist_to_center2 = dx * dx + dy * dy; + *pW = -dist_to_center2 / (2 * kernel_sigma * kernel_sigma); + pW++; + } + } + // Multiply the gradient magnitude by the importance of each pixel + cv::exp(W, W); + Mag = Mag.mul(W); + } + + // Step 5: Build the histogram of orientations + // We have an histogram bigger than usual to capture the circular + float histogram[r_bins + 2][c_bins + 2][ori_bins + 2]; + // Fill the histogram with zeros + std::fill(&histogram[0][0][0], &histogram[r_bins + 1][c_bins + 1][ori_bins + 1], 0); + float bins_per_rad = ori_bins / (2 * M_PI); + int r0, c0, o0; + float rbin, obin, mag, cbin, v_r1, v_rc11, v_rc01, v_rco111, v_rco101, v_rco011, v_rco001, v_r0, + v_rc10, v_rc00, + v_rco110, v_rco100, v_rco010, v_rco000; + pos = 0; + for (r = 0; r < Ori.rows; r++) { + for (c = 0; c < Ori.cols; c++) { + rbin = pRBin[pos]; + cbin = pCBin[pos]; + obin = pOri[pos] * bins_per_rad; + mag = pMag[pos]; + + // Step6: Histogram update using tri-linear interpolation + if (step6_trilinear_interp) { + r0 = cvFloor(rbin); + c0 = cvFloor(cbin); + o0 = cvFloor(obin); + rbin -= r0; + cbin -= c0; + obin -= o0; + + // If the orientation is out of the bin center it + if (o0 < 0) o0 += ori_bins; + if (o0 >= ori_bins) o0 -= ori_bins; + + v_r1 = mag * rbin, v_r0 = mag - v_r1; + v_rc11 = v_r1 * cbin, v_rc10 = v_r1 - v_rc11; + v_rc01 = v_r0 * cbin, v_rc00 = v_r0 - v_rc01; + v_rco111 = v_rc11 * obin, v_rco110 = v_rc11 - v_rco111; + v_rco101 = v_rc10 * obin, v_rco100 = v_rc10 - v_rco101; + v_rco011 = v_rc01 * obin, v_rco010 = v_rc01 - v_rco011; + v_rco001 = v_rc00 * obin, v_rco000 = v_rc00 - v_rco001; + + histogram[r0 + 1][c0 + 1][o0] += v_rco000; + histogram[r0 + 1][c0 + 1][o0 + 1] += v_rco001; + histogram[r0 + 1][c0 + 2][o0] += v_rco010; + histogram[r0 + 1][c0 + 2][o0 + 1] += v_rco011; + histogram[r0 + 2][c0 + 1][o0] += v_rco100; + histogram[r0 + 2][c0 + 1][o0 + 1] += v_rco101; + histogram[r0 + 2][c0 + 2][o0] += v_rco110; + histogram[r0 + 2][c0 + 2][o0 + 1] += v_rco111; + } else { + // Hard nearest neighbour assignation + r0 = cvRound(rbin); + c0 = cvRound(cbin); + o0 = cvRound(obin); + + if (o0 < 0) o0 += ori_bins; + if (o0 >= ori_bins) o0 -= ori_bins; + + histogram[r0 + 1][c0 + 1][o0] += mag; + } + pos++; + } + } + + // Finalize histogram, since the orientation histograms are circular + float *p_dscr = descriptor.ptr(); + for (r = 0; r < r_bins; r++) + for (c = 0; c < c_bins; c++) { + // Increase the value in the penultimate orientation bin in the first one + histogram[r + 1][c + 1][0] += histogram[r + 1][c + 1][ori_bins]; + // Increase the value in last orientation bin in the second one + histogram[r + 1][c + 1][1] += histogram[r + 1][c + 1][ori_bins + 1]; + // Copy the values in the histogram to the output destination + for (k = 0; k < ori_bins; k++) + p_dscr[(r * r_bins + c) * ori_bins + k] = histogram[r + 1][c + 1][k]; + } + + // Step 7: Apply L2 normalization + if (step7_l2_normalization) { + float dscr_norm = std::max(float(cv::norm(descriptor)), FLT_EPSILON); + descriptor /= dscr_norm; + } + + // Step 8: Trim Big Values + if (step8_trim_bigvals) { + for (i = 0; i < descriptor.cols; i++) p_dscr[i] = std::min(p_dscr[i], magnitude_th); + float dscr_norm = std::max(float(cv::norm(descriptor)), FLT_EPSILON); + descriptor /= dscr_norm; + } + + // Optional Step 9: Scale the result, so that it can be easily converted to byte array + if (step9_uchar_scaling) { + for (k = 0; k < descriptor.cols; k++) { + p_dscr[k] = cv::saturate_cast(p_dscr[k] * int_descr_factor); + } + } +} + +////////////////////////////////////////////////////////////////////////////////////////// + +PatchSIFT::PatchSIFT(float kp_scale, + float cropping_scale, + double sigma, + bool step1_pyramid, + bool step4_gaussian_weight, + bool step6_trilinear_interp, + bool step7_l2_normalization, + bool step8_trim_bigvals, + bool step9_uchar_scaling) + : kp_scale(kp_scale), + cropping_scale(cropping_scale), + sigma(sigma), + step1_pyramid(step1_pyramid), + step4_gaussian_weight(step4_gaussian_weight), + step6_trilinear_interp(step6_trilinear_interp), + step7_l2_normalization(step7_l2_normalization), + step8_trim_bigvals(step8_trim_bigvals), + step9_uchar_scaling(step9_uchar_scaling) { +} + +void PatchSIFT::compute(const cv::_InputArray& _image, std::vector& keypoints, + const cv::_OutputArray& _descriptors) { + cv::Mat image = _image.getMat(); + _descriptors.create((int)keypoints.size(), descriptorSize(), descriptorType()); + cv::Mat descriptors = _descriptors.getMat(); + + auto describe_kps_range = [&](const cv::Range& range) { + for (int r = range.start; r < range.end; r++) { + cv::Mat patch; + rectifyPatch(image, keypoints[r], patch_size, patch, cropping_scale); + calcSIFTDescriptor(patch, descriptors.row(r)); + } + }; +#ifdef UPM_PARALLEL_SIFT + parallel_for_(cv::Range(0, keypoints.size()), describe_kps_range); +#else + describe_kps_range(cv::Range(0, keypoints.size())); +#endif +} + +int PatchSIFT::descriptorSize() const { + return r_bins * c_bins * ori_bins; +} + +void PatchSIFT::describeKeypoint(const cv::Mat &image, cv::Mat &descriptor) { + if (image.empty()) { + descriptor.release(); + return; + } + + if (image.empty() || image.depth() != CV_8U) + CV_Error(cv::Error::StsBadArg, "image is empty or has incorrect depth (!=CV_8U)"); + + cv::Mat gray; + if (image.channels() == 3 || image.channels() == 4) + cvtColor(image, gray, cv::COLOR_BGR2GRAY); + else + gray = image; + + descriptor.create(1, descriptorSize(), CV_32F); + calcSIFTDescriptor(gray, descriptor); +} + +cv::Ptr PatchSIFT::create(float kp_scale, + float cropping_scale, + double sigma, + bool step1_pyramid, + bool step4_gaussian_weight, + bool step6_trilinear_interp, + bool step7_l2_normalization, + bool step8_trim_bigvals, + bool step9_uchar_scaling) { + return cv::makePtr(kp_scale, + cropping_scale, + sigma, + step1_pyramid, + step4_gaussian_weight, + step6_trilinear_interp, + step7_l2_normalization, + step8_trim_bigvals, + step9_uchar_scaling); +} +void PatchSIFT::rectifyPatch(const cv::Mat &image, + const cv::KeyPoint &kp, + const cv::Size &patchSize, + cv::Mat &patch, + float scale_factor) { + const float s = scale_factor * kp.size / (0.5f * (patchSize.width + patchSize.height)); + + const float cosine = (kp.angle >= 0) ? cos(kp.angle * (float)CV_PI / 180.0f) : 1.f; + const float sine = (kp.angle >= 0) ? sin(kp.angle * (float)CV_PI / 180.0f) : 0.f; + + cv::Matx23f M(s * cosine, -s * sine, (-s * cosine + s * sine) * patchSize.width / 2.0f + kp.pt.x, + s * sine, s * cosine, (-s * sine - s * cosine) * patchSize.height / 2.0f + kp.pt.y); + warpAffine(image, + patch, + M, + patchSize, + cv::WARP_INVERSE_MAP + cv::INTER_CUBIC + cv::WARP_FILL_OUTLIERS, + cv::BORDER_REPLICATE); +} + +} // namespace upm diff --git a/localization/interest_point/src/matching.cc b/localization/interest_point/src/matching.cc index 37ea1ab808..913982ff23 100644 --- a/localization/interest_point/src/matching.cc +++ b/localization/interest_point/src/matching.cc @@ -16,8 +16,10 @@ * under the License. */ -#include +#include #include +#include +#include #include #include @@ -175,6 +177,45 @@ namespace interest_point { cv::Ptr surf_; }; + class HashSIFTDynamicDetector : public DynamicDetector { + public: + HashSIFTDynamicDetector(int min_features, int max_features, int max_retries, + double min_thresh, double default_thresh, double max_thresh) + : DynamicDetector(min_features, max_features, max_retries, + min_thresh, default_thresh, max_thresh) { + // 6.25 when paired with surf detector + // smaller values for binary detectors (see opencv TEBLID docs) + // TODO: test 512 detector! test w/ and w/o hist equalization! test w/ clahe! + hash_sift_ = upm::HashSIFT::create(6.25, upm::HashSIFT::SIZE_256_BITS); // dynamic_thresh_); + surf_ = cv::xfeatures2d::SURF::create(dynamic_thresh_); + } + + virtual void DetectImpl(const cv::Mat& image, std::vector* keypoints) { + surf_->detect(image, *keypoints); + } + virtual void ComputeImpl(const cv::Mat& image, std::vector* keypoints, + cv::Mat* keypoints_description) { + hash_sift_->compute(image, *keypoints, *keypoints_description); + } + virtual void TooMany(void) { + dynamic_thresh_ *= 1.1; + if (dynamic_thresh_ > max_thresh_) + dynamic_thresh_ = max_thresh_; + surf_->setHessianThreshold(static_cast(dynamic_thresh_)); + } + virtual void TooFew(void) { + dynamic_thresh_ *= 0.9; + if (dynamic_thresh_ < min_thresh_) + dynamic_thresh_ = min_thresh_; + surf_->setHessianThreshold(static_cast(dynamic_thresh_)); + } + + private: + cv::Ptr hash_sift_; + cv::Ptr surf_; + }; + + FeatureDetector::FeatureDetector(std::string const& detector_name, int min_features, int max_features, int retries, double min_thresh, double default_thresh, double max_thresh) { @@ -211,7 +252,8 @@ namespace interest_point { // Populate the defaults if (max_features <= 0) { - if (detector_name == "SURF") { + // SURF and HASHSIFT both use SURF to detect features + if (detector_name == "SURF" || detector_name == "HASHSIFT") { min_features = FLAGS_min_surf_features; max_features = FLAGS_max_surf_features; retries = FLAGS_detection_retries; @@ -237,8 +279,13 @@ namespace interest_point { else if (detector_name == "SURF") detector_ = new SurfDynamicDetector(min_features, max_features, retries, min_thresh, default_thresh, max_thresh); + else if (detector_name == "HASHSIFT") + detector_ = new HashSIFTDynamicDetector(min_features, max_features, retries, + min_thresh, default_thresh, max_thresh); else LOG(FATAL) << "Unimplemented feature detector: " << detector_name; + + LOG(INFO) << "Using descriptor: " << detector_name; } void FeatureDetector::Detect(const cv::Mat& image, From b54732421674d3fad58ed54bba57c6c0176ea47a Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Thu, 13 Jun 2024 19:54:06 -0700 Subject: [PATCH 02/61] added bad feature detector --- localization/interest_point/src/matching.cc | 72 +++++++++++++++++---- 1 file changed, 61 insertions(+), 11 deletions(-) diff --git a/localization/interest_point/src/matching.cc b/localization/interest_point/src/matching.cc index 913982ff23..8b12f938ac 100644 --- a/localization/interest_point/src/matching.cc +++ b/localization/interest_point/src/matching.cc @@ -183,39 +183,86 @@ namespace interest_point { double min_thresh, double default_thresh, double max_thresh) : DynamicDetector(min_features, max_features, max_retries, min_thresh, default_thresh, max_thresh) { - // 6.25 when paired with surf detector - // smaller values for binary detectors (see opencv TEBLID docs) - // TODO: test 512 detector! test w/ and w/o hist equalization! test w/ clahe! - hash_sift_ = upm::HashSIFT::create(6.25, upm::HashSIFT::SIZE_256_BITS); // dynamic_thresh_); - surf_ = cv::xfeatures2d::SURF::create(dynamic_thresh_); + Reset(); + } + + void Reset(void) { + hash_sift_ = upm::HashSIFT::create(5.0, upm::HashSIFT::SIZE_256_BITS); + brisk_ = interest_point::BRISK::create(dynamic_thresh_, FLAGS_orgbrisk_octaves, + FLAGS_orgbrisk_pattern_scale); } virtual void DetectImpl(const cv::Mat& image, std::vector* keypoints) { - surf_->detect(image, *keypoints); + brisk_->detect(image, *keypoints); } virtual void ComputeImpl(const cv::Mat& image, std::vector* keypoints, cv::Mat* keypoints_description) { hash_sift_->compute(image, *keypoints, *keypoints_description); } virtual void TooMany(void) { - dynamic_thresh_ *= 1.1; + dynamic_thresh_ *= 1.25; + dynamic_thresh_ = static_cast(dynamic_thresh_); // for backwards compatibility if (dynamic_thresh_ > max_thresh_) dynamic_thresh_ = max_thresh_; - surf_->setHessianThreshold(static_cast(dynamic_thresh_)); + brisk_->setThreshold(dynamic_thresh_); } virtual void TooFew(void) { - dynamic_thresh_ *= 0.9; + dynamic_thresh_ *= 0.8; + dynamic_thresh_ = static_cast(dynamic_thresh_); // for backwards compatibility if (dynamic_thresh_ < min_thresh_) dynamic_thresh_ = min_thresh_; - surf_->setHessianThreshold(static_cast(dynamic_thresh_)); + brisk_->setThreshold(dynamic_thresh_); } private: cv::Ptr hash_sift_; - cv::Ptr surf_; + cv::Ptr brisk_; + }; + + class BadDynamicDetector : public DynamicDetector { + public: + BadDynamicDetector(int min_features, int max_features, int max_retries, + double min_thresh, double default_thresh, double max_thresh) + : DynamicDetector(min_features, max_features, max_retries, + min_thresh, default_thresh, max_thresh) { + Reset(); + } + + void Reset(void) { + bad_ = upm::BAD::create(5.0, upm::BAD::SIZE_256_BITS); + brisk_ = interest_point::BRISK::create(dynamic_thresh_, FLAGS_orgbrisk_octaves, + FLAGS_orgbrisk_pattern_scale); + } + + virtual void DetectImpl(const cv::Mat& image, std::vector* keypoints) { + brisk_->detect(image, *keypoints); + } + virtual void ComputeImpl(const cv::Mat& image, std::vector* keypoints, + cv::Mat* keypoints_description) { + bad_->compute(image, *keypoints, *keypoints_description); + } + virtual void TooMany(void) { + dynamic_thresh_ *= 1.25; + dynamic_thresh_ = static_cast(dynamic_thresh_); // for backwards compatibility + if (dynamic_thresh_ > max_thresh_) + dynamic_thresh_ = max_thresh_; + brisk_->setThreshold(dynamic_thresh_); + } + virtual void TooFew(void) { + dynamic_thresh_ *= 0.8; + dynamic_thresh_ = static_cast(dynamic_thresh_); // for backwards compatibility + if (dynamic_thresh_ < min_thresh_) + dynamic_thresh_ = min_thresh_; + brisk_->setThreshold(dynamic_thresh_); + } + + private: + cv::Ptr bad_; + cv::Ptr brisk_; }; + FeatureDetector::FeatureDetector(std::string const& detector_name, int min_features, int max_features, int retries, double min_thresh, double default_thresh, double max_thresh) { @@ -282,6 +329,9 @@ namespace interest_point { else if (detector_name == "HASHSIFT") detector_ = new HashSIFTDynamicDetector(min_features, max_features, retries, min_thresh, default_thresh, max_thresh); + else if (detector_name == "BAD") + detector_ = new BadDynamicDetector(min_features, max_features, retries, + min_thresh, default_thresh, max_thresh); else LOG(FATAL) << "Unimplemented feature detector: " << detector_name; From 15096a0d9853e29e5fda7ea81679c75f1c5b6c52 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Thu, 13 Jun 2024 20:06:05 -0700 Subject: [PATCH 03/61] added clahe instead of normal histogram equalization --- .../sparse_mapping/include/sparse_mapping/sparse_map.h | 2 ++ localization/sparse_mapping/src/sparse_map.cc | 6 +++++- 2 files changed, 7 insertions(+), 1 deletion(-) diff --git a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h index 1fa91d79f7..527e0731db 100644 --- a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h +++ b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h @@ -28,6 +28,7 @@ #include #include +#include #include #include @@ -298,6 +299,7 @@ struct SparseMap { std::vector user_cid_to_keypoint_map_; std::vector > user_pid_to_cid_fid_; std::vector user_pid_to_xyz_; + cv::Ptr clahe_; std::mutex mutex_detector_; private: diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index b6fd572b49..e0623ebe52 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -74,6 +74,7 @@ SparseMap::SparseMap(const std::vector & filenames, ransac_inlier_tolerance_(FLAGS_ransac_inlier_tolerance), early_break_landmarks_(FLAGS_early_break_landmarks), histogram_equalization_(FLAGS_histogram_equalization) { + clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); cid_to_descriptor_map_.resize(cid_to_filename_.size()); // TODO(bcoltin): only record scale and orientation for opensift? cid_to_keypoint_map_.resize(cid_to_filename_.size()); @@ -87,6 +88,7 @@ SparseMap::SparseMap(const std::string & protobuf_file, bool localization) : ransac_inlier_tolerance_(FLAGS_ransac_inlier_tolerance), early_break_landmarks_(FLAGS_early_break_landmarks), histogram_equalization_(FLAGS_histogram_equalization) { + clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); // The above camera params used bad values because we are expected to reload // later. Load(protobuf_file, localization); @@ -103,6 +105,7 @@ SparseMap::SparseMap(const std::vector& cid_to_cam_t, ransac_inlier_tolerance_(FLAGS_ransac_inlier_tolerance), early_break_landmarks_(FLAGS_early_break_landmarks), histogram_equalization_(FLAGS_histogram_equalization) { + clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); if (filenames.size() != cid_to_cam_t.size()) LOG(FATAL) << "Expecting as many images as cameras"; @@ -132,6 +135,7 @@ SparseMap::SparseMap(bool bundler_format, std::string const& filename, ransac_inlier_tolerance_(FLAGS_ransac_inlier_tolerance), early_break_landmarks_(FLAGS_early_break_landmarks), histogram_equalization_(FLAGS_histogram_equalization) { + clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); std::string ext = ff_common::file_extension(filename); boost::to_lower(ext); @@ -597,7 +601,7 @@ void SparseMap::DetectFeatures(const cv::Mat& image, cv::Mat * image_ptr = const_cast(&image); cv::Mat hist_image; if (histogram_equalization_) { - cv::equalizeHist(image, hist_image); + clahe_->apply(image, hist_image); image_ptr = &hist_image; } From c87ad534c5c376699765fdc6018b10fbf03e5c94 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Fri, 21 Jun 2024 14:39:30 -0700 Subject: [PATCH 04/61] removed hashsift, made localize a member fcn --- .../include/interest_point/HashSIFT.h | 90 ------ .../interest_point/HashSiftWeights256.h | 1 - .../interest_point/HashSiftWeights512.h | 1 - .../include/interest_point/PatchSIFT.h | 138 --------- localization/interest_point/src/HashSIFT.cpp | 101 ------ localization/interest_point/src/PatchSIFT.cpp | 292 ------------------ localization/interest_point/src/matching.cc | 65 +--- .../include/sparse_mapping/sparse_map.h | 43 ++- localization/sparse_mapping/src/sparse_map.cc | 10 +- 9 files changed, 32 insertions(+), 709 deletions(-) delete mode 100644 localization/interest_point/include/interest_point/HashSIFT.h delete mode 100644 localization/interest_point/include/interest_point/HashSiftWeights256.h delete mode 100644 localization/interest_point/include/interest_point/HashSiftWeights512.h delete mode 100644 localization/interest_point/include/interest_point/PatchSIFT.h delete mode 100644 localization/interest_point/src/HashSIFT.cpp delete mode 100644 localization/interest_point/src/PatchSIFT.cpp diff --git a/localization/interest_point/include/interest_point/HashSIFT.h b/localization/interest_point/include/interest_point/HashSIFT.h deleted file mode 100644 index b797a9b5d5..0000000000 --- a/localization/interest_point/include/interest_point/HashSIFT.h +++ /dev/null @@ -1,90 +0,0 @@ -/** - * @copyright 2021 Xoan Iago Suarez Canosa. All rights reserved. - * Constact: iago.suarez@thegraffter.com - * Software developed in the PhD: Low-level vision for resource-limited devices - */ -#ifndef EFFICIENT_DESCRIPTORS_HASHSIFT_H_ -#define EFFICIENT_DESCRIPTORS_HASHSIFT_H_ - -#include -#include -#include -#include - -namespace upm { -/** - * HashSIFT descriptor described in the article - * "Suarez, I., Buenaposada, J. M., & Baumela, L. (2021). Revisiting Binary Local Image - * Description for Resource Limited Devices. IEEE Robotics and Automation Letters." - * - * The descriptor computes first the SIFT features using the class PatchSIFT and then it hashes - * the floating point SIFT descriptor with a pre-learnt linear projection: b_matrix_ - * The weights b_matrix_ are loaded from the files HashSiftWeights256.i and HashSiftWeights512.i. - */ -class HashSIFT : public cv::Feature2D { - public: - /** - * @brief Descriptor number of bits, each bit is a weak-descriptor. - * The user can choose between 512 or 256 bits. - */ - enum HashSiftSize { - SIZE_512_BITS = 100, SIZE_256_BITS = 101, - }; - - /** - * - * @param cropping_scale Determines the size of the patch cropped for description. - * The diameter of the patch will be: cropping_scale * kp.size - * @param n_bits The number of bits of the descriptor (512 or 256) - * @param sigma The standard deviation of the gaussian smoothing filter applied to the patch - * before description. - */ - explicit HashSIFT(float cropping_scale, - HashSiftSize n_bits = SIZE_256_BITS, - double sigma = 1.6); - - /** - * Creates a pointer to a new instance - * @param cropping_scale Determines the size of the patch cropped for description. - * The diameter of the patch will be: cropping_scale * kp.size - * @param n_bits The number of bits of the descriptor (512 or 256) - * @param sigma The standard deviation of the gaussian smoothing filter applied to the patch - * before description. - * @return A pointer to the new cv::Feature2D descriptor object - */ - static cv::Ptr create(float cropping_scale, - HashSiftSize n_bits = SIZE_256_BITS, - double sigma = 1.6); - - /** - * Computes the descriptors corresponding to the specified Keypoints - * @param image The input grayscale image - * @param keypoints The detected input keypoints - * @param descriptors The output descriptors. The shape of the output cv::Mat will be: - * n_keypoints x (nbits / 8) - */ - void compute(cv::InputArray image, CV_OUT CV_IN_OUT std::vector& keypoints, - cv::OutputArray descriptors) override; - - int descriptorSize() const override { return nbits_ / 8; } - int descriptorType() const override { return CV_8UC1; } - int defaultNorm() const override { return cv::NORM_HAMMING; } - - private: - /** - * @brief Transforms the wlResponses with the B^T matrix and apply the sign operation. - * The matrix multiplication is done using floating point arithmetic from OpenCV - * @param wlResponses A floating point matrix with the WL responses. the shape is: - * (n_descriptors, n_wls) i.e. each descriptor is a row of the matrix - * @param descriptors The Output matrix where we are going to store the resulting binary descriptors. - */ - void matmulAndSign(const cv::Mat &wlResponses, cv::Mat descriptors); - - std::shared_ptr sift_{}; - int nbits_{-1}; - cv::Mat_ b_matrix_; - cv::Mat_ transp_b_matrix_; -}; - -} // namespace upm -#endif // EFFICIENT_DESCRIPTORS_HASHSIFT_H_ diff --git a/localization/interest_point/include/interest_point/HashSiftWeights256.h b/localization/interest_point/include/interest_point/HashSiftWeights256.h deleted file mode 100644 index f9fa2edf35..0000000000 --- a/localization/interest_point/include/interest_point/HashSiftWeights256.h +++ /dev/null @@ -1 +0,0 @@ -double 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\ No newline at end of file diff --git a/localization/interest_point/include/interest_point/HashSiftWeights512.h b/localization/interest_point/include/interest_point/HashSiftWeights512.h deleted file mode 100644 index 45a091117d..0000000000 --- a/localization/interest_point/include/interest_point/HashSiftWeights512.h +++ /dev/null @@ -1 +0,0 @@ -double 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\ No newline at end of file diff --git a/localization/interest_point/include/interest_point/PatchSIFT.h b/localization/interest_point/include/interest_point/PatchSIFT.h deleted file mode 100644 index a60eb8ac80..0000000000 --- a/localization/interest_point/include/interest_point/PatchSIFT.h +++ /dev/null @@ -1,138 +0,0 @@ -/** - * @copyright 2021 Xoan Iago Suarez Canosa. All rights reserved. - * Constact: iago.suarez@thegraffter.com - * Software developed in the PhD: Low-level vision for resource-limited devices - */ -#ifndef EFFICIENT_DESCRIPTORS_PATCHSIFT_H_ -#define EFFICIENT_DESCRIPTORS_PATCHSIFT_H_ - -#include -#include - -namespace upm { - -/** - * Implementation of the SIFT descriptor: - * Lowe, D. G. (2004). Distinctive image features from scale-invariant keypoints. - * International journal of computer vision, 60(2), 91-110. - * - * This code does not include the detection part. Instead, it is intended to be used with any - */ -class PatchSIFT : public cv::Feature2D { - public: - explicit PatchSIFT(float kp_scale, // Default 1 / 6.0 - float cropping_scale, - double sigma = 1.6, - bool step1_pyramid = true, - bool step4_gaussian_weight = true, - bool step6_trilinear_interp = true, - bool step7_l2_normalization = true, - bool step8_trim_bigvals = true, - bool step9_uchar_scaling = true); - - static cv::Ptr create(float kp_scale, // Default 1 / 6.0 - float cropping_scale, - double sigma = 1.6, - bool step1_pyramid = true, - bool step4_gaussian_weight = true, - bool step6_trilinear_interp = true, - bool step7_l2_normalization = true, - bool step8_trim_bigvals = true, - bool step9_uchar_scaling = true); - - //! returns the descriptor size in floats (128) - int descriptorSize() const override; - int descriptorType() const override { return CV_32FC1; } - int defaultNorm() const override { return cv::NORM_L2; } - - void compute(cv::InputArray image, - CV_OUT CV_IN_OUT std::vector &keypoints, - cv::OutputArray descriptors) override; - - void describeKeypoint(const cv::Mat &image, cv::Mat &descriptor); - - void calcSIFTDescriptor(const cv::Mat &img, cv::Mat descriptor); - - inline const cv::Size &GetPatchSize() const { return patch_size; } - inline const float &GetCroppingScale() const { return cropping_scale; } - - static void rectifyPatch(const cv::Mat &image, - const cv::KeyPoint &kp, - const cv::Size &patchSize, - cv::Mat &patch, - float scale_factor); - - protected: - // The scale of the keypoint relative to the patch size. If will be used to modify the variance - // of the gaussian that give more weight to the pixels in the center - float kp_scale; - double sigma; - // default number of bins per histogram in descriptor array - int ori_bins = 8; - // default width of descriptor histogram array - int r_bins = 4; - // default width of descriptor histogram array - int c_bins = 4; - // threshold on magnitude of elements of descriptor vector - float magnitude_th = 0.2f; - // factor used to convert floating-point descriptor to unsigned char - float int_descr_factor = 512.f; - // Steps of the algorithm we can configure - bool step1_pyramid = true; - bool step4_gaussian_weight = true; - bool step6_trilinear_interp = true; - bool step7_l2_normalization = true; - bool step8_trim_bigvals = true; - bool step9_uchar_scaling = true; - - cv::Size patch_size{32, 32}; - float cropping_scale = 1.0f; -}; - -/******************************* Defs and macros *****************************/ - -// assumed gaussian blur for input image -static const float SIFT_INIT_SIGMA = 0.5f; - -// determines the size of a single descriptor orientation histogram -static const float SIFT_DESCR_SCL_FCTR = 3.f; - -class RootPatchSIFT : public PatchSIFT { - public: - RootPatchSIFT(float kp_scale, // Default 1 / 6.0 - float cropping_scale, double sigma = 1.6, bool step1_pyramid = true, bool step4_gaussian_weight = true, - bool step6_trilinear_interp = true, bool step7_l2_normalization = true, bool step8_trim_bigvals = true, - bool step9_uchar_scaling = true) - : PatchSIFT(kp_scale, cropping_scale, sigma, step1_pyramid, step4_gaussian_weight, step6_trilinear_interp, - step7_l2_normalization, step8_trim_bigvals, step9_uchar_scaling) {} - - void compute(cv::InputArray image, - CV_OUT CV_IN_OUT std::vector &keypoints, - cv::OutputArray _descriptors) override { - PatchSIFT::compute(image, keypoints, _descriptors); - cv::Mat descriptors = _descriptors.getMat(); - for (int i = 0; i < descriptors.rows; i++) { - double norm = cv::norm(descriptors.row(i), cv::NORM_L1); - cv::sqrt(descriptors.row(i) / norm, descriptors.row(i)); - } - } - - static cv::Ptr create(float kp_scale, // Default 1 / 6.0 - float cropping_scale, double sigma = 1.6, bool step1_pyramid = true, - bool step4_gaussian_weight = true, bool step6_trilinear_interp = true, - bool step7_l2_normalization = true, bool step8_trim_bigvals = true, - bool step9_uchar_scaling = true) { - return cv::makePtr(kp_scale, - cropping_scale, - sigma, - step1_pyramid, - step4_gaussian_weight, - step6_trilinear_interp, - step7_l2_normalization, - step8_trim_bigvals, - step9_uchar_scaling); - } -}; - -} // namespace upm -#endif // EFFICIENT_DESCRIPTORS_PATCHSIFT_H_ diff --git a/localization/interest_point/src/HashSIFT.cpp b/localization/interest_point/src/HashSIFT.cpp deleted file mode 100644 index 0849c25209..0000000000 --- a/localization/interest_point/src/HashSIFT.cpp +++ /dev/null @@ -1,101 +0,0 @@ -/** - * @copyright 2021 Xoan Iago Suarez Canosa. All rights reserved. - * Constact: iago.suarez@thegraffter.com - * Software developed in the PhD: Low-level vision for resource-limited devices - */ -#include - -namespace upm { - -HashSIFT::HashSIFT(float cropping_scale, - HashSiftSize n_bits, - double sigma) { - if (n_bits == SIZE_512_BITS) { - #include - b_matrix_ = cv::Mat(512, 129, CV_64FC1, HASH_SIFT_512_VALS); - b_matrix_.convertTo(b_matrix_, CV_32FC1); - } else { - #include - b_matrix_ = cv::Mat(256, 129, CV_64FC1, HASH_SIFT_256_VALS); - b_matrix_.convertTo(b_matrix_, CV_32FC1); - } - - nbits_ = b_matrix_.rows; - transp_b_matrix_ = b_matrix_.t(); - - // 1 / 6.75f - sift_ = std::make_shared(1 / 6.0, cropping_scale, sigma); -} - -cv::Ptr HashSIFT::create(float cropping_scale, - HashSiftSize n_bits, - double sigma) { - return cv::makePtr(cropping_scale, n_bits, sigma); -} - -void HashSIFT::compute(cv::InputArray& _image, std::vector& keypoints, cv::OutputArray& _descriptors) { - cv::Mat image = _image.getMat(); - - if (image.empty()) - return; - - if (keypoints.empty()) { - // clean output buffer (it may be reused with "allocated" data) - _descriptors.release(); - return; - } - - assert(image.type() == CV_8UC1); - - // Create the output array of descriptors - _descriptors.create((int)keypoints.size(), descriptorSize(), descriptorType()); - cv::Mat descriptors = _descriptors.getMat(); - cv::Mat sift_descriptors(keypoints.size(), 129, CV_32FC1); - sift_descriptors.col(0).setTo(1); - cv::Mat wlInt8tResponses(keypoints.size(), 129, CV_8UC1); - -#ifndef UPM_PARALLEL_HASH_SIFT - const cv::Range range(0, keypoints.size()); -#else - parallel_for_(cv::Range(0, keypoints.size()), [&](const cv::Range &range) { -#endif - cv::Mat patch(sift_->GetPatchSize(), CV_8UC1); - for (int r = range.start; r < range.end; r++) { - PatchSIFT::rectifyPatch(image, keypoints[r], sift_->GetPatchSize(), patch, - sift_->GetCroppingScale()); - sift_->calcSIFTDescriptor(patch, - sift_descriptors(cv::Range(r, r + 1), - cv::Range(1, sift_descriptors.cols))); - } - - // Compute the linear projection and hash - matmulAndSign(sift_descriptors.rowRange(range), descriptors.rowRange(range)); - -#ifdef UPM_PARALLEL_HASH_SIFT - }); -#endif - } // namespace upm - -void HashSIFT::matmulAndSign(const cv::Mat &wlResponses, cv::Mat descriptors) { - assert(wlResponses.rows == descriptors.rows); - cv::Mat tmp = wlResponses * transp_b_matrix_; - float *pTmp = tmp.ptr(); - uint8_t *p_descr = descriptors.ptr(); - uint8_t byte; - int d, b; - for (d = 0; d < descriptors.rows; d++) { - for (b = 0; b < tmp.cols / 8; b++) { - byte = 0; - byte |= (*pTmp++ > 0) << 7; - byte |= (*pTmp++ > 0) << 6; - byte |= (*pTmp++ > 0) << 5; - byte |= (*pTmp++ > 0) << 4; - byte |= (*pTmp++ > 0) << 3; - byte |= (*pTmp++ > 0) << 2; - byte |= (*pTmp++ > 0) << 1; - byte |= (*pTmp++ > 0) << 0; - *p_descr++ = byte; - } // End of for each bit - } // End of for each keypoint -} -} diff --git a/localization/interest_point/src/PatchSIFT.cpp b/localization/interest_point/src/PatchSIFT.cpp deleted file mode 100644 index 86c31c8b3f..0000000000 --- a/localization/interest_point/src/PatchSIFT.cpp +++ /dev/null @@ -1,292 +0,0 @@ -/** - * @copyright 2021 Xoan Iago Suarez Canosa. All rights reserved. - * Constact: iago.suarez@thegraffter.com - * Software developed in the PhD: Low-level vision for resource-limited devices - */ -#include - -namespace upm { - -void PatchSIFT::calcSIFTDescriptor(const cv::Mat &gray, cv::Mat descriptor) { - assert(descriptor.type() == CV_32FC1); - assert(descriptor.rows == 1 && descriptor.cols == descriptorSize()); - assert(gray.channels() == 1); - - int i, j, k, r, c; - - // Step 1: Filter the image using a gaussian filter of size sigma - cv::Mat img; - if (step1_pyramid) { - float sig_diff = sqrtf(std::max(float(sigma) * float(sigma) - SIFT_INIT_SIGMA * SIFT_INIT_SIGMA, 0.01f)); - cv::GaussianBlur(gray, img, cv::Size(), sig_diff, sig_diff); - } else { - img = gray; - } - // Step 2: We assume a pre-oriented and pre-scale patch of fixed size - - // Step 3: Compute the image derivatives - // X and Y derivatives - cv::Mat X(img.rows - 2, img.cols - 2, CV_32FC1); - cv::Mat Y(img.rows - 2, img.cols - 2, CV_32FC1); - // Row and column bins - cv::Mat RBin(img.rows - 2, img.cols - 2, CV_32FC1); - cv::Mat CBin(img.rows - 2, img.cols - 2, CV_32FC1); - - // The radius of the keypoint in pixels - const float cell_width = SIFT_DESCR_SCL_FCTR * (kp_scale * img.cols * 0.5f); - const float cell_height = SIFT_DESCR_SCL_FCTR * (kp_scale * img.rows * 0.5f); - - float *pX = X.ptr(), *pY = Y.ptr(), *pRBin = RBin.ptr(), - *pCBin = CBin.ptr(); - float c_rot, r_rot; - uint8_t *p, *pImg = img.ptr(); - - int img_width = img.cols, pos = 0; - // Compute image derivatives - for (i = 1; i < (img.rows - 1); i++) { - p = pImg + i * img_width + 1; - for (j = 1; j < (img.cols - 1); j++) { - // Compute the derivative using the previous and next pixels - pX[pos] = *(p + 1) - *(p - 1); - pY[pos] = *(p - img_width) - *(p + img_width); - - // Assign each pixels to its bin - c_rot = (j - img.cols / 2.0f) / cell_width; - r_rot = (i - img.rows / 2.0f) / cell_height; - // Check that the indices of the histogram are correct - assert((r_rot + r_bins / 2 - 0.5f) > -2 && (r_rot + r_bins / 2 - 0.5f) <= r_bins); - assert((c_rot + c_bins / 2 - 0.5f) > -2 && (c_rot + c_bins / 2 - 0.5f) <= c_bins); - pRBin[pos] = r_rot + r_bins / 2 - 0.5f; - pCBin[pos] = c_rot + c_bins / 2 - 0.5f; - pos++; - p++; - } - } - - // Compute the gradient direction and magnitude - cv::Mat Mag, Ori; - cv::cartToPolar(X, Y, Mag, Ori); - float *pMag = Mag.ptr(), *pOri = Ori.ptr(); - - // Step 4: Create the gaussian weighting assigned to each pixel - if (step4_gaussian_weight) { - cv::Mat W = cv::Mat::ones(img.rows - 2, img.cols - 2, CV_32FC1); - const float kp_radius = kp_scale * img.rows * 0.5f; - float kernel_sigma = 0.5 * c_bins * SIFT_DESCR_SCL_FCTR * kp_radius; - float dx, dy, dist_to_center2; - float *pW = W.ptr(); - for (r = 0; r < W.rows; r++) { - for (c = 0; c < W.cols; c++) { - dx = r - W.cols / 2.0f; - dy = c - W.rows / 2.0f; - dist_to_center2 = dx * dx + dy * dy; - *pW = -dist_to_center2 / (2 * kernel_sigma * kernel_sigma); - pW++; - } - } - // Multiply the gradient magnitude by the importance of each pixel - cv::exp(W, W); - Mag = Mag.mul(W); - } - - // Step 5: Build the histogram of orientations - // We have an histogram bigger than usual to capture the circular - float histogram[r_bins + 2][c_bins + 2][ori_bins + 2]; - // Fill the histogram with zeros - std::fill(&histogram[0][0][0], &histogram[r_bins + 1][c_bins + 1][ori_bins + 1], 0); - float bins_per_rad = ori_bins / (2 * M_PI); - int r0, c0, o0; - float rbin, obin, mag, cbin, v_r1, v_rc11, v_rc01, v_rco111, v_rco101, v_rco011, v_rco001, v_r0, - v_rc10, v_rc00, - v_rco110, v_rco100, v_rco010, v_rco000; - pos = 0; - for (r = 0; r < Ori.rows; r++) { - for (c = 0; c < Ori.cols; c++) { - rbin = pRBin[pos]; - cbin = pCBin[pos]; - obin = pOri[pos] * bins_per_rad; - mag = pMag[pos]; - - // Step6: Histogram update using tri-linear interpolation - if (step6_trilinear_interp) { - r0 = cvFloor(rbin); - c0 = cvFloor(cbin); - o0 = cvFloor(obin); - rbin -= r0; - cbin -= c0; - obin -= o0; - - // If the orientation is out of the bin center it - if (o0 < 0) o0 += ori_bins; - if (o0 >= ori_bins) o0 -= ori_bins; - - v_r1 = mag * rbin, v_r0 = mag - v_r1; - v_rc11 = v_r1 * cbin, v_rc10 = v_r1 - v_rc11; - v_rc01 = v_r0 * cbin, v_rc00 = v_r0 - v_rc01; - v_rco111 = v_rc11 * obin, v_rco110 = v_rc11 - v_rco111; - v_rco101 = v_rc10 * obin, v_rco100 = v_rc10 - v_rco101; - v_rco011 = v_rc01 * obin, v_rco010 = v_rc01 - v_rco011; - v_rco001 = v_rc00 * obin, v_rco000 = v_rc00 - v_rco001; - - histogram[r0 + 1][c0 + 1][o0] += v_rco000; - histogram[r0 + 1][c0 + 1][o0 + 1] += v_rco001; - histogram[r0 + 1][c0 + 2][o0] += v_rco010; - histogram[r0 + 1][c0 + 2][o0 + 1] += v_rco011; - histogram[r0 + 2][c0 + 1][o0] += v_rco100; - histogram[r0 + 2][c0 + 1][o0 + 1] += v_rco101; - histogram[r0 + 2][c0 + 2][o0] += v_rco110; - histogram[r0 + 2][c0 + 2][o0 + 1] += v_rco111; - } else { - // Hard nearest neighbour assignation - r0 = cvRound(rbin); - c0 = cvRound(cbin); - o0 = cvRound(obin); - - if (o0 < 0) o0 += ori_bins; - if (o0 >= ori_bins) o0 -= ori_bins; - - histogram[r0 + 1][c0 + 1][o0] += mag; - } - pos++; - } - } - - // Finalize histogram, since the orientation histograms are circular - float *p_dscr = descriptor.ptr(); - for (r = 0; r < r_bins; r++) - for (c = 0; c < c_bins; c++) { - // Increase the value in the penultimate orientation bin in the first one - histogram[r + 1][c + 1][0] += histogram[r + 1][c + 1][ori_bins]; - // Increase the value in last orientation bin in the second one - histogram[r + 1][c + 1][1] += histogram[r + 1][c + 1][ori_bins + 1]; - // Copy the values in the histogram to the output destination - for (k = 0; k < ori_bins; k++) - p_dscr[(r * r_bins + c) * ori_bins + k] = histogram[r + 1][c + 1][k]; - } - - // Step 7: Apply L2 normalization - if (step7_l2_normalization) { - float dscr_norm = std::max(float(cv::norm(descriptor)), FLT_EPSILON); - descriptor /= dscr_norm; - } - - // Step 8: Trim Big Values - if (step8_trim_bigvals) { - for (i = 0; i < descriptor.cols; i++) p_dscr[i] = std::min(p_dscr[i], magnitude_th); - float dscr_norm = std::max(float(cv::norm(descriptor)), FLT_EPSILON); - descriptor /= dscr_norm; - } - - // Optional Step 9: Scale the result, so that it can be easily converted to byte array - if (step9_uchar_scaling) { - for (k = 0; k < descriptor.cols; k++) { - p_dscr[k] = cv::saturate_cast(p_dscr[k] * int_descr_factor); - } - } -} - -////////////////////////////////////////////////////////////////////////////////////////// - -PatchSIFT::PatchSIFT(float kp_scale, - float cropping_scale, - double sigma, - bool step1_pyramid, - bool step4_gaussian_weight, - bool step6_trilinear_interp, - bool step7_l2_normalization, - bool step8_trim_bigvals, - bool step9_uchar_scaling) - : kp_scale(kp_scale), - cropping_scale(cropping_scale), - sigma(sigma), - step1_pyramid(step1_pyramid), - step4_gaussian_weight(step4_gaussian_weight), - step6_trilinear_interp(step6_trilinear_interp), - step7_l2_normalization(step7_l2_normalization), - step8_trim_bigvals(step8_trim_bigvals), - step9_uchar_scaling(step9_uchar_scaling) { -} - -void PatchSIFT::compute(const cv::_InputArray& _image, std::vector& keypoints, - const cv::_OutputArray& _descriptors) { - cv::Mat image = _image.getMat(); - _descriptors.create((int)keypoints.size(), descriptorSize(), descriptorType()); - cv::Mat descriptors = _descriptors.getMat(); - - auto describe_kps_range = [&](const cv::Range& range) { - for (int r = range.start; r < range.end; r++) { - cv::Mat patch; - rectifyPatch(image, keypoints[r], patch_size, patch, cropping_scale); - calcSIFTDescriptor(patch, descriptors.row(r)); - } - }; -#ifdef UPM_PARALLEL_SIFT - parallel_for_(cv::Range(0, keypoints.size()), describe_kps_range); -#else - describe_kps_range(cv::Range(0, keypoints.size())); -#endif -} - -int PatchSIFT::descriptorSize() const { - return r_bins * c_bins * ori_bins; -} - -void PatchSIFT::describeKeypoint(const cv::Mat &image, cv::Mat &descriptor) { - if (image.empty()) { - descriptor.release(); - return; - } - - if (image.empty() || image.depth() != CV_8U) - CV_Error(cv::Error::StsBadArg, "image is empty or has incorrect depth (!=CV_8U)"); - - cv::Mat gray; - if (image.channels() == 3 || image.channels() == 4) - cvtColor(image, gray, cv::COLOR_BGR2GRAY); - else - gray = image; - - descriptor.create(1, descriptorSize(), CV_32F); - calcSIFTDescriptor(gray, descriptor); -} - -cv::Ptr PatchSIFT::create(float kp_scale, - float cropping_scale, - double sigma, - bool step1_pyramid, - bool step4_gaussian_weight, - bool step6_trilinear_interp, - bool step7_l2_normalization, - bool step8_trim_bigvals, - bool step9_uchar_scaling) { - return cv::makePtr(kp_scale, - cropping_scale, - sigma, - step1_pyramid, - step4_gaussian_weight, - step6_trilinear_interp, - step7_l2_normalization, - step8_trim_bigvals, - step9_uchar_scaling); -} -void PatchSIFT::rectifyPatch(const cv::Mat &image, - const cv::KeyPoint &kp, - const cv::Size &patchSize, - cv::Mat &patch, - float scale_factor) { - const float s = scale_factor * kp.size / (0.5f * (patchSize.width + patchSize.height)); - - const float cosine = (kp.angle >= 0) ? cos(kp.angle * (float)CV_PI / 180.0f) : 1.f; - const float sine = (kp.angle >= 0) ? sin(kp.angle * (float)CV_PI / 180.0f) : 0.f; - - cv::Matx23f M(s * cosine, -s * sine, (-s * cosine + s * sine) * patchSize.width / 2.0f + kp.pt.x, - s * sine, s * cosine, (-s * sine - s * cosine) * patchSize.height / 2.0f + kp.pt.y); - warpAffine(image, - patch, - M, - patchSize, - cv::WARP_INVERSE_MAP + cv::INTER_CUBIC + cv::WARP_FILL_OUTLIERS, - cv::BORDER_REPLICATE); -} - -} // namespace upm diff --git a/localization/interest_point/src/matching.cc b/localization/interest_point/src/matching.cc index 8b12f938ac..c884cfbc8a 100644 --- a/localization/interest_point/src/matching.cc +++ b/localization/interest_point/src/matching.cc @@ -18,7 +18,6 @@ #include #include -#include #include #include @@ -177,9 +176,9 @@ namespace interest_point { cv::Ptr surf_; }; - class HashSIFTDynamicDetector : public DynamicDetector { + class TeblidDynamicDetector : public DynamicDetector { public: - HashSIFTDynamicDetector(int min_features, int max_features, int max_retries, + TeblidDynamicDetector(int min_features, int max_features, int max_retries, double min_thresh, double default_thresh, double max_thresh) : DynamicDetector(min_features, max_features, max_retries, min_thresh, default_thresh, max_thresh) { @@ -187,7 +186,7 @@ namespace interest_point { } void Reset(void) { - hash_sift_ = upm::HashSIFT::create(5.0, upm::HashSIFT::SIZE_256_BITS); + teblid_ = upm::BAD::create(5.0, upm::BAD::SIZE_512_BITS); brisk_ = interest_point::BRISK::create(dynamic_thresh_, FLAGS_orgbrisk_octaves, FLAGS_orgbrisk_pattern_scale); } @@ -197,7 +196,7 @@ namespace interest_point { } virtual void ComputeImpl(const cv::Mat& image, std::vector* keypoints, cv::Mat* keypoints_description) { - hash_sift_->compute(image, *keypoints, *keypoints_description); + teblid_->compute(image, *keypoints, *keypoints_description); } virtual void TooMany(void) { dynamic_thresh_ *= 1.25; @@ -215,49 +214,7 @@ namespace interest_point { } private: - cv::Ptr hash_sift_; - cv::Ptr brisk_; - }; - - class BadDynamicDetector : public DynamicDetector { - public: - BadDynamicDetector(int min_features, int max_features, int max_retries, - double min_thresh, double default_thresh, double max_thresh) - : DynamicDetector(min_features, max_features, max_retries, - min_thresh, default_thresh, max_thresh) { - Reset(); - } - - void Reset(void) { - bad_ = upm::BAD::create(5.0, upm::BAD::SIZE_256_BITS); - brisk_ = interest_point::BRISK::create(dynamic_thresh_, FLAGS_orgbrisk_octaves, - FLAGS_orgbrisk_pattern_scale); - } - - virtual void DetectImpl(const cv::Mat& image, std::vector* keypoints) { - brisk_->detect(image, *keypoints); - } - virtual void ComputeImpl(const cv::Mat& image, std::vector* keypoints, - cv::Mat* keypoints_description) { - bad_->compute(image, *keypoints, *keypoints_description); - } - virtual void TooMany(void) { - dynamic_thresh_ *= 1.25; - dynamic_thresh_ = static_cast(dynamic_thresh_); // for backwards compatibility - if (dynamic_thresh_ > max_thresh_) - dynamic_thresh_ = max_thresh_; - brisk_->setThreshold(dynamic_thresh_); - } - virtual void TooFew(void) { - dynamic_thresh_ *= 0.8; - dynamic_thresh_ = static_cast(dynamic_thresh_); // for backwards compatibility - if (dynamic_thresh_ < min_thresh_) - dynamic_thresh_ = min_thresh_; - brisk_->setThreshold(dynamic_thresh_); - } - - private: - cv::Ptr bad_; + cv::Ptr teblid_; cv::Ptr brisk_; }; @@ -299,15 +256,14 @@ namespace interest_point { // Populate the defaults if (max_features <= 0) { - // SURF and HASHSIFT both use SURF to detect features - if (detector_name == "SURF" || detector_name == "HASHSIFT") { + if (detector_name == "SURF") { min_features = FLAGS_min_surf_features; max_features = FLAGS_max_surf_features; retries = FLAGS_detection_retries; min_thresh = FLAGS_min_surf_threshold; default_thresh = FLAGS_default_surf_threshold; max_thresh = FLAGS_max_surf_threshold; - } else if (detector_name == "ORGBRISK") { + } else if (detector_name == "ORGBRISK" || detector_name == "TEBLID") { min_features = FLAGS_min_brisk_features; max_features = FLAGS_max_brisk_features; retries = FLAGS_detection_retries; @@ -326,11 +282,8 @@ namespace interest_point { else if (detector_name == "SURF") detector_ = new SurfDynamicDetector(min_features, max_features, retries, min_thresh, default_thresh, max_thresh); - else if (detector_name == "HASHSIFT") - detector_ = new HashSIFTDynamicDetector(min_features, max_features, retries, - min_thresh, default_thresh, max_thresh); - else if (detector_name == "BAD") - detector_ = new BadDynamicDetector(min_features, max_features, retries, + else if (detector_name == "TEBLID") + detector_ = new TeblidDynamicDetector(min_features, max_features, retries, min_thresh, default_thresh, max_thresh); else LOG(FATAL) << "Unimplemented feature detector: " << detector_name; diff --git a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h index 527e0731db..fe18635b63 100644 --- a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h +++ b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h @@ -52,30 +52,6 @@ void InitializeCidFidToPid(int num_cid, std::vector > const& pid_to_cid_fid, std::vector > * cid_fid_to_pid); -/** - * Estimate the camera pose for a set of image descriptors and keypoints. - * Non-member function. We will invoke it both from within - * the SparseMap class and from outside of it. - **/ -bool Localize(cv::Mat const& test_descriptors, - Eigen::Matrix2Xd const& test_keypoints, - camera::CameraParameters const& camera_params, - camera::CameraModel* pose, - std::vector* inlier_landmarks, - std::vector* inlier_observations, - int num_cid, - std::string const& detector_name, - sparse_mapping::VocabDB * vocab_db, - int num_similar, - std::vector const& cid_to_filename, - std::vector const& cid_to_descriptor_map, - std::vector const& cid_to_keypoint_map, - std::vector > const& cid_fid_to_pid, - std::vector const& pid_to_xyz, - int num_ransac_iterations, int ransac_inlier_tolerance, - int early_break_landmarks, int histogram_equalization, - std::vector * cid_list); - /** * A class representing a sparse map, which consists of a collection * of keyframes and detected features. To localize, an image's features @@ -142,6 +118,25 @@ struct SparseMap { std::vector* inlier_landmarks, std::vector* inlier_observations, std::vector * cid_list = NULL); +bool Localize(cv::Mat const& test_descriptors, + Eigen::Matrix2Xd const& test_keypoints, + camera::CameraParameters const& camera_params, + camera::CameraModel* pose, + std::vector* inlier_landmarks, + std::vector* inlier_observations, + int num_cid, + std::string const& detector_name, + sparse_mapping::VocabDB * vocab_db, + int num_similar, + std::vector const& cid_to_filename, + std::vector const& cid_to_descriptor_map, + std::vector const& cid_to_keypoint_map, + std::vector > const& cid_fid_to_pid, + std::vector const& pid_to_xyz, + int num_ransac_iterations, int ransac_inlier_tolerance, + int early_break_landmarks, int histogram_equalization, + std::vector * cid_list); + // access map frames /** * Get the number of keyframes in the map. diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index e0623ebe52..f5561df51e 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -650,9 +650,7 @@ void SparseMap::DetectFeatures(const cv::Mat& image, } } -// A non-member Localize() function that can be invoked for a non-fully -// formed map. -bool Localize(cv::Mat const& test_descriptors, +bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const& test_keypoints, camera::CameraParameters const& camera_params, camera::CameraModel* pose, @@ -771,7 +769,7 @@ bool SparseMap::Localize(std::string const& img_file, Eigen::Matrix2Xd test_keypoints; bool multithreaded = false; DetectFeaturesFromFile(img_file, multithreaded, &test_descriptors, &test_keypoints); - return sparse_mapping::Localize(test_descriptors, test_keypoints, + return Localize(test_descriptors, test_keypoints, std::cref(camera_params_), pose, inlier_landmarks, inlier_observations, @@ -963,7 +961,7 @@ bool SparseMap::Localize(const cv::Mat & image, camera::CameraModel* pose, cv::Mat test_descriptors; Eigen::Matrix2Xd test_keypoints; DetectFeatures(image, multithreaded, &test_descriptors, &test_keypoints); - return sparse_mapping::Localize(test_descriptors, test_keypoints, + return Localize(test_descriptors, test_keypoints, std::cref(camera_params_), pose, inlier_landmarks, inlier_observations, @@ -988,7 +986,7 @@ bool SparseMap::Localize(const cv::Mat & test_descriptors, const Eigen::Matrix2X std::vector* inlier_landmarks, std::vector* inlier_observations, std::vector * cid_list) { - return sparse_mapping::Localize(test_descriptors, test_keypoints, + return Localize(test_descriptors, test_keypoints, std::cref(camera_params_), pose, inlier_landmarks, inlier_observations, From 7c2a29ae19a0f911a86a0ed95feb52238a7344c5 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Fri, 21 Jun 2024 14:40:04 -0700 Subject: [PATCH 05/61] removed hashsift --- localization/interest_point/CMakeLists.txt | 2 -- 1 file changed, 2 deletions(-) diff --git a/localization/interest_point/CMakeLists.txt b/localization/interest_point/CMakeLists.txt index 8558c5aa60..acdf0dd57f 100644 --- a/localization/interest_point/CMakeLists.txt +++ b/localization/interest_point/CMakeLists.txt @@ -62,8 +62,6 @@ add_library(interest_point src/essential.cc src/matching.cc src/BAD.cpp - src/HashSIFT.cpp - src/PatchSIFT.cpp ) add_dependencies(interest_point ${catkin_EXPORTED_TARGETS}) target_link_libraries(interest_point ${OPENMVG_LIBRARIES} ${catkin_LIBRARIES} ${OpenCV_LIBRARIES}) From 1995c801dbb2b7df4efa9566005b3215a6b4e5ea Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Fri, 21 Jun 2024 14:55:59 -0700 Subject: [PATCH 06/61] removed old localize call --- .../include/sparse_mapping/sparse_map.h | 19 +--- localization/sparse_mapping/src/sparse_map.cc | 95 +++---------------- 2 files changed, 16 insertions(+), 98 deletions(-) diff --git a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h index fe18635b63..442beb6dd7 100644 --- a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h +++ b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h @@ -113,29 +113,12 @@ struct SparseMap { camera::CameraModel* pose, std::vector* inlier_landmarks = NULL, std::vector* inlier_observations = NULL, std::vector * cid_list = NULL); - bool Localize(const cv::Mat & test_descriptors, const Eigen::Matrix2Xd & test_keypoints, - camera::CameraModel* pose, - std::vector* inlier_landmarks, - std::vector* inlier_observations, - std::vector * cid_list = NULL); bool Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const& test_keypoints, - camera::CameraParameters const& camera_params, camera::CameraModel* pose, std::vector* inlier_landmarks, std::vector* inlier_observations, - int num_cid, - std::string const& detector_name, - sparse_mapping::VocabDB * vocab_db, - int num_similar, - std::vector const& cid_to_filename, - std::vector const& cid_to_descriptor_map, - std::vector const& cid_to_keypoint_map, - std::vector > const& cid_fid_to_pid, - std::vector const& pid_to_xyz, - int num_ransac_iterations, int ransac_inlier_tolerance, - int early_break_landmarks, int histogram_equalization, - std::vector * cid_list); + std::vector * cid_list = NULL); // access map frames /** diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index f5561df51e..2436d364b9 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -652,31 +652,19 @@ void SparseMap::DetectFeatures(const cv::Mat& image, bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const& test_keypoints, - camera::CameraParameters const& camera_params, camera::CameraModel* pose, std::vector* inlier_landmarks, std::vector* inlier_observations, - int num_cid, - std::string const& detector_name, - sparse_mapping::VocabDB * vocab_db, - int num_similar, - std::vector const& cid_to_filename, - std::vector const& cid_to_descriptor_map, - std::vector const& cid_to_keypoint_map, - std::vector > const& cid_fid_to_pid, - std::vector const& pid_to_xyz, - int num_ransac_iterations, int ransac_inlier_tolerance, - int early_break_landmarks, int histogram_equalization, std::vector * cid_list) { std::vector indices; // Query the vocab tree. if (cid_list == NULL) - sparse_mapping::QueryDB(detector_name, - vocab_db, + sparse_mapping::QueryDB(detector_.GetDetectorName(), + &vocab_db_, // Notice that we request more similar // images than what we need. We'll prune // them below. - num_similar + FLAGS_num_extra_localization_db_images, + num_similar_ + FLAGS_num_extra_localization_db_images, test_descriptors, &indices); else @@ -684,6 +672,7 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, if (indices.empty()) { LOG(WARNING) << "Localizing against all keyframes as the vocab database is missing."; // Use all images, as no tree is available. + const int num_cid = cid_to_filename_.size(); for (int cid = 0; cid < num_cid; cid++) indices.push_back(cid); } @@ -705,28 +694,28 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, for (size_t i = 0; i < indices.size(); i++) { int cid = indices[i]; interest_point::FindMatches(test_descriptors, - cid_to_descriptor_map[cid], + cid_to_descriptor_map_[cid], &all_matches[i]); for (size_t j = 0; j < all_matches[i].size(); j++) { - if (cid_fid_to_pid[cid].count(all_matches[i][j].trainIdx) == 0) + if (cid_fid_to_pid_[cid].count(all_matches[i][j].trainIdx) == 0) continue; similarity_rank[i]++; } if (FLAGS_verbose_localization) std::cout << "Overall matches and validated matches to: " - << cid_to_filename[cid] << ": " + << cid_to_filename_[cid] << ": " << all_matches[i].size() << " " << similarity_rank[i] << "\n"; total += similarity_rank[i]; - if (total >= early_break_landmarks) + if (total >= early_break_landmarks_) break; } std::vector observations; std::vector landmarks; std::vector highly_ranked = ff_common::rv_order(similarity_rank); - int end = std::min(static_cast(highly_ranked.size()), num_similar); + int end = std::min(static_cast(highly_ranked.size()), num_similar_); std::set seen_landmarks; if (FLAGS_verbose_localization) std::cout << "Similar images: "; @@ -735,26 +724,26 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, std::vector* matches = &all_matches[highly_ranked[i]]; int num_matches = 0; for (size_t j = 0; j < matches->size(); j++) { - if (cid_fid_to_pid[cid].count(matches->at(j).trainIdx) == 0) + if (cid_fid_to_pid_[cid].count(matches->at(j).trainIdx) == 0) continue; - const int landmark_id = cid_fid_to_pid.at(cid).at(matches->at(j).trainIdx); + const int landmark_id = cid_fid_to_pid_.at(cid).at(matches->at(j).trainIdx); if (seen_landmarks.count(landmark_id) > 0) continue; Eigen::Vector2d obs(test_keypoints.col(matches->at(j).queryIdx)[0], test_keypoints.col(matches->at(j).queryIdx)[1]); observations.push_back(obs); - landmarks.push_back(pid_to_xyz[landmark_id]); + landmarks.push_back(pid_to_xyz_[landmark_id]); seen_landmarks.insert(landmark_id); num_matches++; } if (FLAGS_verbose_localization && num_matches > 0) - std::cout << " " << cid_to_filename[cid]; + std::cout << " " << cid_to_filename_[cid]; } if (FLAGS_verbose_localization) std::cout << std::endl; int ret = RansacEstimateCamera(landmarks, observations, - num_ransac_iterations, - ransac_inlier_tolerance, pose, + num_ransac_iterations_, + ransac_inlier_tolerance_, pose, inlier_landmarks, inlier_observations, FLAGS_verbose_localization); return (ret == 0); @@ -770,22 +759,8 @@ bool SparseMap::Localize(std::string const& img_file, bool multithreaded = false; DetectFeaturesFromFile(img_file, multithreaded, &test_descriptors, &test_keypoints); return Localize(test_descriptors, test_keypoints, - std::cref(camera_params_), pose, inlier_landmarks, inlier_observations, - cid_to_filename_.size(), - detector_.GetDetectorName(), - &vocab_db_, - num_similar_, - cid_to_filename_, - cid_to_descriptor_map_, - cid_to_keypoint_map_, - cid_fid_to_pid_, - pid_to_xyz_, - num_ransac_iterations_, - ransac_inlier_tolerance_, - early_break_landmarks_, - histogram_equalization_, cid_list); } @@ -962,48 +937,8 @@ bool SparseMap::Localize(const cv::Mat & image, camera::CameraModel* pose, Eigen::Matrix2Xd test_keypoints; DetectFeatures(image, multithreaded, &test_descriptors, &test_keypoints); return Localize(test_descriptors, test_keypoints, - std::cref(camera_params_), pose, inlier_landmarks, inlier_observations, - cid_to_filename_.size(), - detector_.GetDetectorName(), - &vocab_db_, - num_similar_, - cid_to_filename_, - cid_to_descriptor_map_, - cid_to_keypoint_map_, - cid_fid_to_pid_, - pid_to_xyz_, - num_ransac_iterations_, - ransac_inlier_tolerance_, - early_break_landmarks_, - histogram_equalization_, cid_list); } - -bool SparseMap::Localize(const cv::Mat & test_descriptors, const Eigen::Matrix2Xd & test_keypoints, - camera::CameraModel* pose, - std::vector* inlier_landmarks, - std::vector* inlier_observations, - std::vector * cid_list) { - return Localize(test_descriptors, test_keypoints, - std::cref(camera_params_), - pose, - inlier_landmarks, inlier_observations, - cid_to_filename_.size(), - detector_.GetDetectorName(), - &vocab_db_, - num_similar_, - cid_to_filename_, - cid_to_descriptor_map_, - cid_to_keypoint_map_, - cid_fid_to_pid_, - pid_to_xyz_, - num_ransac_iterations_, - ransac_inlier_tolerance_, - early_break_landmarks_, - histogram_equalization_, - cid_list); -} - } // namespace sparse_mapping From a5ea2532122709bfdd45985686f21c895e9972b2 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sat, 22 Jun 2024 08:47:04 -0700 Subject: [PATCH 07/61] added clahe to saving map, made optional --- .../include/sparse_mapping/sparse_map.h | 3 + localization/sparse_mapping/src/sparse_map.cc | 90 ++++++++++--------- 2 files changed, 52 insertions(+), 41 deletions(-) diff --git a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h index 442beb6dd7..688b1a73d7 100644 --- a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h +++ b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h @@ -191,6 +191,8 @@ bool Localize(cv::Mat const& test_descriptors, void SetEarlyBreakLandmarks(int early_break_landmarks) {early_break_landmarks_ = early_break_landmarks;} void SetHistogramEqualization(int histogram_equalization) {histogram_equalization_ = histogram_equalization;} int GetHistogramEqualization() {return histogram_equalization_;} + void SetCLAHE(bool use_clahe) {use_clahe_ = use_clahe;} + bool GetCLAHE() {return use_clahe_;} /** * Return the parameters of the camera used to construct the map. **/ @@ -260,6 +262,7 @@ bool Localize(cv::Mat const& test_descriptors, int ransac_inlier_tolerance_; int early_break_landmarks_; int histogram_equalization_; + bool use_clahe_; // e.g, 10th db image is 3rd image in cid_to_filename_ std::map db_to_cid_map_; diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index 2436d364b9..8dd53d69c6 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -57,6 +57,8 @@ DEFINE_int32(early_break_landmarks, 100, "Break early when we have this many landmarks during localization."); DEFINE_bool(histogram_equalization, false, "If true, equalize the histogram for images to improve robustness to illumination conditions."); +DEFINE_bool(use_clahe, false, + "If true, use CLAHE if histogram equalization enabled."); DEFINE_int32(num_extra_localization_db_images, 0, "Match this many extra images from the Vocab DB, only keep num_similar."); DEFINE_bool(verbose_localization, false, @@ -64,30 +66,31 @@ DEFINE_bool(verbose_localization, false, namespace sparse_mapping { -SparseMap::SparseMap(const std::vector & filenames, - const std::string & detector, - const camera::CameraParameters & params): - cid_to_filename_(filenames), - detector_(detector), camera_params_(params), - num_similar_(FLAGS_num_similar), - num_ransac_iterations_(FLAGS_num_ransac_iterations), - ransac_inlier_tolerance_(FLAGS_ransac_inlier_tolerance), - early_break_landmarks_(FLAGS_early_break_landmarks), - histogram_equalization_(FLAGS_histogram_equalization) { +SparseMap::SparseMap(const std::vector& filenames, const std::string& detector, + const camera::CameraParameters& params) + : cid_to_filename_(filenames), + detector_(detector), + camera_params_(params), + num_similar_(FLAGS_num_similar), + num_ransac_iterations_(FLAGS_num_ransac_iterations), + ransac_inlier_tolerance_(FLAGS_ransac_inlier_tolerance), + early_break_landmarks_(FLAGS_early_break_landmarks), + histogram_equalization_(FLAGS_histogram_equalization), + use_clahe_(FLAGS_use_clahe) { clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); cid_to_descriptor_map_.resize(cid_to_filename_.size()); // TODO(bcoltin): only record scale and orientation for opensift? cid_to_keypoint_map_.resize(cid_to_filename_.size()); } -SparseMap::SparseMap(const std::string & protobuf_file, bool localization) : - camera_params_(Eigen::Vector2i(-1, -1), Eigen::Vector2d::Constant(-1), - Eigen::Vector2d(-1, -1)), - num_similar_(FLAGS_num_similar), - num_ransac_iterations_(FLAGS_num_ransac_iterations), - ransac_inlier_tolerance_(FLAGS_ransac_inlier_tolerance), - early_break_landmarks_(FLAGS_early_break_landmarks), - histogram_equalization_(FLAGS_histogram_equalization) { +SparseMap::SparseMap(const std::string& protobuf_file, bool localization) + : camera_params_(Eigen::Vector2i(-1, -1), Eigen::Vector2d::Constant(-1), Eigen::Vector2d(-1, -1)), + num_similar_(FLAGS_num_similar), + num_ransac_iterations_(FLAGS_num_ransac_iterations), + ransac_inlier_tolerance_(FLAGS_ransac_inlier_tolerance), + early_break_landmarks_(FLAGS_early_break_landmarks), + histogram_equalization_(FLAGS_histogram_equalization), + use_clahe_(FLAGS_use_clahe) { clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); // The above camera params used bad values because we are expected to reload // later. @@ -95,16 +98,16 @@ SparseMap::SparseMap(const std::string & protobuf_file, bool localization) : } // Form a sparse map with given cameras/images, and no features -SparseMap::SparseMap(const std::vector& cid_to_cam_t, - const std::vector & filenames, - const std::string & detector, - const camera::CameraParameters & params): - detector_(detector), camera_params_(params), - num_similar_(FLAGS_num_similar), - num_ransac_iterations_(FLAGS_num_ransac_iterations), - ransac_inlier_tolerance_(FLAGS_ransac_inlier_tolerance), - early_break_landmarks_(FLAGS_early_break_landmarks), - histogram_equalization_(FLAGS_histogram_equalization) { +SparseMap::SparseMap(const std::vector& cid_to_cam_t, const std::vector& filenames, + const std::string& detector, const camera::CameraParameters& params) + : detector_(detector), + camera_params_(params), + num_similar_(FLAGS_num_similar), + num_ransac_iterations_(FLAGS_num_ransac_iterations), + ransac_inlier_tolerance_(FLAGS_ransac_inlier_tolerance), + early_break_landmarks_(FLAGS_early_break_landmarks), + histogram_equalization_(FLAGS_histogram_equalization), + use_clahe_(FLAGS_use_clahe) { clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); if (filenames.size() != cid_to_cam_t.size()) LOG(FATAL) << "Expecting as many images as cameras"; @@ -126,15 +129,15 @@ SparseMap::SparseMap(const std::vector& cid_to_cam_t, // Form a sparse map by reading a text file from disk. This is for comparing // bundler, nvm or theia maps. -SparseMap::SparseMap(bool bundler_format, std::string const& filename, - std::vector const& all_image_files): - camera_params_(Eigen::Vector2i(640, 480), Eigen::Vector2d::Constant(300), - Eigen::Vector2d(320, 240)), // these are placeholders and must be changed - num_similar_(FLAGS_num_similar), - num_ransac_iterations_(FLAGS_num_ransac_iterations), - ransac_inlier_tolerance_(FLAGS_ransac_inlier_tolerance), - early_break_landmarks_(FLAGS_early_break_landmarks), - histogram_equalization_(FLAGS_histogram_equalization) { +SparseMap::SparseMap(bool bundler_format, std::string const& filename, std::vector const& all_image_files) + : camera_params_(Eigen::Vector2i(640, 480), Eigen::Vector2d::Constant(300), + Eigen::Vector2d(320, 240)), // these are placeholders and must be changed + num_similar_(FLAGS_num_similar), + num_ransac_iterations_(FLAGS_num_ransac_iterations), + ransac_inlier_tolerance_(FLAGS_ransac_inlier_tolerance), + early_break_landmarks_(FLAGS_early_break_landmarks), + histogram_equalization_(FLAGS_histogram_equalization), + use_clahe_(FLAGS_use_clahe) { clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); std::string ext = ff_common::file_extension(filename); boost::to_lower(ext); @@ -412,9 +415,10 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { histogram_equalization_ = map.histogram_equalization(); - assert(histogram_equalization_ == 0 || - histogram_equalization_ == 1 || - histogram_equalization_ == 2); + assert(histogram_equalization_ == 0 || histogram_equalization_ == 1 || histogram_equalization_ == 2 || + histogram_equalization_ == 3); + + use_clahe_ = histogram_equalization_ == 3 ? true : false; // For backward compatibility with old maps, allow a map to have its // histogram_equalization flag unspecified, but it is best to avoid @@ -601,7 +605,11 @@ void SparseMap::DetectFeatures(const cv::Mat& image, cv::Mat * image_ptr = const_cast(&image); cv::Mat hist_image; if (histogram_equalization_) { - clahe_->apply(image, hist_image); + if (use_clahe_) { + clahe_->apply(image, hist_image); + } else { + cv::equalizeHist(image, hist_image); + } image_ptr = &hist_image; } From 74a8a13c38a41034e8a070bbcb6d27a9f192c7d6 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sat, 22 Jun 2024 09:10:26 -0700 Subject: [PATCH 08/61] added viz utils to sparse map --- localization/sparse_mapping/CMakeLists.txt | 1 + .../sparse_mapping/visualization_utilities.h | 44 ++++++++++++ .../src/visualization_utilities.cc | 68 +++++++++++++++++++ 3 files changed, 113 insertions(+) create mode 100644 localization/sparse_mapping/include/sparse_mapping/visualization_utilities.h create mode 100644 localization/sparse_mapping/src/visualization_utilities.cc diff --git a/localization/sparse_mapping/CMakeLists.txt b/localization/sparse_mapping/CMakeLists.txt index 92874609e2..677d2871a9 100644 --- a/localization/sparse_mapping/CMakeLists.txt +++ b/localization/sparse_mapping/CMakeLists.txt @@ -79,6 +79,7 @@ add_library(sparse_mapping src/sparse_map.cc src/sparse_mapping.cc src/tensor.cc + src/visualization_utilities.cc src/vocab_tree.cc ${PROTO_SRCS} ) diff --git a/localization/sparse_mapping/include/sparse_mapping/visualization_utilities.h b/localization/sparse_mapping/include/sparse_mapping/visualization_utilities.h new file mode 100644 index 0000000000..9a58b44fe4 --- /dev/null +++ b/localization/sparse_mapping/include/sparse_mapping/visualization_utilities.h @@ -0,0 +1,44 @@ +/* Copyright (c) 2017, United States Government, as represented by the + * Administrator of the National Aeronautics and Space Administration. + * + * All rights reserved. + * + * The Astrobee platform is licensed under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with the + * License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT + * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the + * License for the specific language governing permissions and limitations + * under the License. + */ + +#ifndef SPARSE_MAPPING_VISUALIZATION_UTILITIES_H_ +#define SPARSE_MAPPING_VISUALIZATION_UTILITIES_H_ + +#include + +#include +#include +#include + +#include + +namespace sparse_mapping { +// Convert keypoints from matrix to cv::KeyPoints +std::vector Keypoints(const Eigen::Matrix2Xd& keypoints_mat); + +// Convert keypoints from undistorted centered matrix to distorted cv::KeyPoints +std::vector DistortedKeypoints(const Eigen::Matrix2Xd& keypoints_mat, + const camera::CameraParameters& camera_params); + +// View input keypoints, map keypoints, and matches +void ViewMatches(const Eigen::Matrix2Xd& input_keypoints_mat, const Eigen::Matrix2Xd& map_keypoints_mat, + const std::vector& matches, const camera::CameraParameters& camera_params, + const cv::Mat& input_image, const cv::Mat& map_image); +} // namespace sparse_mapping + +#endif // SPARSE_MAPPING_VISUALIZATION_UTILITIES_H_ diff --git a/localization/sparse_mapping/src/visualization_utilities.cc b/localization/sparse_mapping/src/visualization_utilities.cc new file mode 100644 index 0000000000..f145333eeb --- /dev/null +++ b/localization/sparse_mapping/src/visualization_utilities.cc @@ -0,0 +1,68 @@ +/* Copyright (c) 2017, United States Government, as represented by the + * Administrator of the National Aeronautics and Space Administration. + * + * All rights reserved. + * + * The Astrobee platform is licensed under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with the + * License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT + * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the + * License for the specific language governing permissions and limitations + * under the License. + */ + +#include + +#include +#include + +namespace sparse_mapping { +std::vector Keypoints(const Eigen::Matrix2Xd& keypoints_mat) { + std::vector keypoints; + for (int i = 0; i < keypoints_mat.cols(); ++i) { + keypoints.emplace_back(cv::KeyPoint(keypoints_mat.col(i).x(), keypoints_mat.col(i).y(), 1.0)); + } + return keypoints; +} + +std::vector DistortedKeypoints(const Eigen::Matrix2Xd& keypoints_mat, + const camera::CameraParameters& camera_params) { + std::vector keypoints; + for (int i = 0; i < keypoints_mat.cols(); ++i) { + Eigen::Vector2d distorted_point; + camera_params.Convert(keypoints_mat.col(i), &distorted_point); + keypoints.emplace_back(cv::KeyPoint(distorted_point.x(), distorted_point.y(), 1.0)); + } + return keypoints; +} + +void ViewMatches(const Eigen::Matrix2Xd& input_keypoints_mat, const Eigen::Matrix2Xd& map_keypoints_mat, + const std::vector& matches, const camera::CameraParameters& camera_params, + const cv::Mat& input_image, const cv::Mat& map_image) { + const auto input_keypoints = DistortedKeypoints(input_keypoints_mat, camera_params); + const auto map_keypoints = DistortedKeypoints(map_keypoints_mat, camera_params); + cv::Mat input_keypoints_image, map_keypoints_image; + cv::drawKeypoints(input_image, input_keypoints, input_keypoints_image); + cv::drawKeypoints(map_image, map_keypoints, map_keypoints_image); + cv::Mat keypoints_image; + cv::resize(input_keypoints_image, input_keypoints_image, cv::Size(1.1 * 960, 1.1 * 540)); + cv::resize(map_keypoints_image, map_keypoints_image, cv::Size(1.1 * 960, 1.1 * 540)); + cv::Mat combined_image; + cv::hconcat(input_keypoints_image, map_keypoints_image, combined_image); + cv::imshow("Input and Map Keypoints", combined_image); + cv::waitKey(0); + cv::destroyAllWindows(); + cv::Mat matches_image; + cv::drawMatches(input_image, input_keypoints, map_image, map_keypoints, matches, matches_image, cv::Scalar::all(-1), + cv::Scalar::all(-1), std::vector(), cv::DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS); + cv::resize(matches_image, matches_image, cv::Size(1.7 * 960, 1.7 * 540)); + cv::imshow("Input to Map Matches", matches_image); + cv::waitKey(0); + cv::destroyAllWindows(); +} +} // namespace sparse_mapping From 7911ee9266b0e591758f0e2a70de87ad38a301b8 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sat, 22 Jun 2024 09:21:33 -0700 Subject: [PATCH 09/61] added option to visualize matches during loc --- .../include/sparse_mapping/sparse_map.h | 9 +++---- localization/sparse_mapping/src/sparse_map.cc | 25 +++++++++++++------ 2 files changed, 21 insertions(+), 13 deletions(-) diff --git a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h index 688b1a73d7..5799f20c25 100644 --- a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h +++ b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h @@ -113,12 +113,9 @@ struct SparseMap { camera::CameraModel* pose, std::vector* inlier_landmarks = NULL, std::vector* inlier_observations = NULL, std::vector * cid_list = NULL); -bool Localize(cv::Mat const& test_descriptors, - Eigen::Matrix2Xd const& test_keypoints, - camera::CameraModel* pose, - std::vector* inlier_landmarks, - std::vector* inlier_observations, - std::vector * cid_list = NULL); + bool Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const& test_keypoints, camera::CameraModel* pose, + std::vector* inlier_landmarks, std::vector* inlier_observations, + std::vector* cid_list = NULL, const cv::Mat& image = cv::Mat()); // access map frames /** diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index 8dd53d69c6..30e2e9c1ef 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -24,6 +24,7 @@ #include #include #include +#include #include #include @@ -63,6 +64,8 @@ DEFINE_int32(num_extra_localization_db_images, 0, "Match this many extra images from the Vocab DB, only keep num_similar."); DEFINE_bool(verbose_localization, false, "If true, list the images most similar to the one being localized."); +DEFINE_bool(visualize_localization_matches, false, + "If true, visualized matches between input image and each available map image during localization."); namespace sparse_mapping { @@ -658,12 +661,10 @@ void SparseMap::DetectFeatures(const cv::Mat& image, } } -bool SparseMap::Localize(cv::Mat const& test_descriptors, - Eigen::Matrix2Xd const& test_keypoints, - camera::CameraModel* pose, - std::vector* inlier_landmarks, - std::vector* inlier_observations, - std::vector * cid_list) { +bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const& test_keypoints, + camera::CameraModel* pose, std::vector* inlier_landmarks, + std::vector* inlier_observations, std::vector* cid_list, + const cv::Mat& image) { std::vector indices; // Query the vocab tree. if (cid_list == NULL) @@ -705,6 +706,16 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, cid_to_descriptor_map_[cid], &all_matches[i]); + if (FLAGS_visualize_localization_matches && !image.empty()) { + const auto map_filename = cid_to_filename_[cid]; + const auto map_image = cv::imread(map_filename, cv::IMREAD_GRAYSCALE); + if (map_image.empty()) { + LOG(ERROR) << "Failed to load map image: " << map_filename; + } else { + ViewMatches(test_keypoints, cid_to_keypoint_map_[cid], all_matches[i], camera_params_, image, map_image); + } + } + for (size_t j = 0; j < all_matches[i].size(); j++) { if (cid_fid_to_pid_[cid].count(all_matches[i][j].trainIdx) == 0) continue; @@ -947,6 +958,6 @@ bool SparseMap::Localize(const cv::Mat & image, camera::CameraModel* pose, return Localize(test_descriptors, test_keypoints, pose, inlier_landmarks, inlier_observations, - cid_list); + cid_list, image); } } // namespace sparse_mapping From 4574ea89a771bac706129b71042be590859fbbb8 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sat, 22 Jun 2024 20:32:19 -0700 Subject: [PATCH 10/61] changed binary interest feature matching --- localization/interest_point/src/matching.cc | 37 +++++++++++---------- 1 file changed, 20 insertions(+), 17 deletions(-) diff --git a/localization/interest_point/src/matching.cc b/localization/interest_point/src/matching.cc index c884cfbc8a..185174e8ea 100644 --- a/localization/interest_point/src/matching.cc +++ b/localization/interest_point/src/matching.cc @@ -32,8 +32,10 @@ // same settings! // TODO(oalexan1): Ideally the settings used here must be saved in the // map file, for the localize executable to read them from there. -DEFINE_int32(hamming_distance, 90, +DEFINE_int32(hamming_distance, 70, "A smaller value keeps fewer but more reliable binary descriptor matches."); +DEFINE_double(binary_goodness_ratio, 0.8, + "A smaller value keeps fewer but more reliable binary descriptor matches."); DEFINE_double(goodness_ratio, 0.8, "A smaller value keeps fewer but more reliable float descriptor matches."); DEFINE_int32(orgbrisk_octaves, 4, @@ -55,14 +57,14 @@ DEFINE_double(default_surf_threshold, 10, "Default threshold for feature detection using SURF."); DEFINE_double(max_surf_threshold, 1000, "Maximum threshold for feature detection using SURF."); -// ORGBRISK detector +// Binary detector DEFINE_int32(min_brisk_features, 400, "Minimum number of features to be computed using ORGBRISK."); -DEFINE_int32(max_brisk_features, 800, +DEFINE_int32(max_brisk_features, 3000, "Maximum number of features to be computed using ORGBRISK."); DEFINE_double(min_brisk_threshold, 20, "Minimum threshold for feature detection using ORGBRISK."); -DEFINE_double(default_brisk_threshold, 90, +DEFINE_double(default_brisk_threshold, 20, "Default threshold for feature detection using ORGBRISK."); DEFINE_double(max_brisk_threshold, 110, "Maximum threshold for feature detection using ORGBRISK."); @@ -320,22 +322,23 @@ namespace interest_point { if (img1_descriptor_map.depth() == CV_8U) { // Binary descriptor - - // cv::BFMatcher matcher(cv::NORM_HAMMING, true /* Forward & Backward matching */); cv::FlannBasedMatcher matcher(cv::makePtr(3, 18, 2)); - matcher.match(img1_descriptor_map, img2_descriptor_map, *matches); - - // Select only inlier matches that meet a BRISK threshold of - // of FLAGS_hamming_distance. - // TODO(oalexan1) This needs further study. - std::vector inlier_matches; - inlier_matches.reserve(matches->size()); // This saves time in allocation - for (cv::DMatch const& dmatch : *matches) { - if (dmatch.distance < FLAGS_hamming_distance) { - inlier_matches.push_back(dmatch); + std::vector > possible_matches; + matcher.knnMatch(img1_descriptor_map, img2_descriptor_map, possible_matches, 2); + matches->clear(); + matches->reserve(possible_matches.size()); + for (std::vector const& best_pair : possible_matches) { + if (best_pair.size() == 0 || best_pair.at(0).distance > FLAGS_hamming_distance) continue; + if (best_pair.size() == 1) { + // This was the only best match, push it. + matches->push_back(best_pair.at(0)); + } else { + // Push back a match only if it is a certain percent better than the next best. + if (best_pair.at(0).distance < FLAGS_binary_goodness_ratio * best_pair.at(1).distance) { + matches->push_back(best_pair[0]); + } } } - matches->swap(inlier_matches); // Doesn't invoke a copy of all elements. } else { // Traditional floating point descriptor cv::FlannBasedMatcher matcher; From ec0bec4ae141bcdaf6ba1b19cb0723b506554dc8 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sat, 22 Jun 2024 20:43:21 -0700 Subject: [PATCH 11/61] removed config paths from map matcher --- .../include/localization_analysis/map_matcher.h | 4 +--- tools/localization_analysis/src/map_matcher.cc | 6 ++---- tools/localization_analysis/tools/run_map_matcher.cc | 7 +------ 3 files changed, 4 insertions(+), 13 deletions(-) diff --git a/tools/localization_analysis/include/localization_analysis/map_matcher.h b/tools/localization_analysis/include/localization_analysis/map_matcher.h index 020bb2f2d4..eaeb75f41f 100644 --- a/tools/localization_analysis/include/localization_analysis/map_matcher.h +++ b/tools/localization_analysis/include/localization_analysis/map_matcher.h @@ -34,8 +34,7 @@ namespace localization_analysis { class MapMatcher { public: MapMatcher(const std::string& input_bag_name, const std::string& map_file, const std::string& image_topic, - const std::string& output_bag_name, const std::string& config_prefix = "", - const std::string& save_noloc_imgs = ""); + const std::string& output_bag_name, const std::string& save_noloc_imgs = ""); void AddMapMatches(); void LogResults(); @@ -48,7 +47,6 @@ class MapMatcher { std::string image_topic_; sparse_mapping::SparseMap map_; localization_node::Localizer map_feature_matcher_; - std::string config_prefix_; gtsam::Pose3 body_T_nav_cam_; localization_common::Averager feature_averager_; int sparse_mapping_min_num_landmarks_; diff --git a/tools/localization_analysis/src/map_matcher.cc b/tools/localization_analysis/src/map_matcher.cc index e66e2856f3..5196045847 100644 --- a/tools/localization_analysis/src/map_matcher.cc +++ b/tools/localization_analysis/src/map_matcher.cc @@ -30,21 +30,19 @@ namespace localization_analysis { namespace lc = localization_common; namespace mc = msg_conversions; MapMatcher::MapMatcher(const std::string& input_bag_name, const std::string& map_file, const std::string& image_topic, - const std::string& output_bag_name, const std::string& config_prefix, - const std::string& save_noloc_imgs) + const std::string& output_bag_name, const std::string& save_noloc_imgs) : input_bag_(input_bag_name, rosbag::bagmode::Read), output_bag_(output_bag_name, rosbag::bagmode::Write), nonloc_bag_(), image_topic_(image_topic), map_(map_file, true), map_feature_matcher_(&map_), - config_prefix_(config_prefix), feature_averager_("Total number of features detected"), match_count_(0), image_count_(0) { config_reader::ConfigReader config; config.AddFile("geometry.config"); - lc::LoadGraphLocalizerConfig(config, config_prefix); + lc::LoadGraphLocalizerConfig(config); if (!config.ReadFiles()) { LogFatal("Failed to read config files."); } diff --git a/tools/localization_analysis/tools/run_map_matcher.cc b/tools/localization_analysis/tools/run_map_matcher.cc index 059e973508..22c3e0df3d 100644 --- a/tools/localization_analysis/tools/run_map_matcher.cc +++ b/tools/localization_analysis/tools/run_map_matcher.cc @@ -32,20 +32,17 @@ int main(int argc, char** argv) { std::string image_topic; std::string robot_config_file; std::string world; - std::string config_path_prefix; std::string save_noloc_imgs; po::options_description desc("Matches images to provided map and saves matches features and poses to a new bag file"); desc.add_options()("help,h", "produce help message")("bagfile,b", po::value()->required(), "Input bagfile containing image messages.")( "map-file,m", po::value()->required(), "Map file")( - "config-path,c", po::value()->required(), "Path to config directory.")( "image-topic,i", po::value(&image_topic)->default_value("mgt/img_sampler/nav_cam/image_record"), "Image topic")("robot-config-file,r", po::value(&robot_config_file)->default_value("config/robots/bumble.config"), "Robot config file")("world,w", po::value(&world)->default_value("iss"), "World name")( "output-bagfile,o", po::value(&output_bagfile)->default_value(""), "Output bagfile, defaults to input_bag + _map_matches.bag")( - "config-path-prefix,p", po::value(&config_path_prefix)->default_value(""), "Config path prefix")( "save-noloc-imgs,s", po::value(&save_noloc_imgs)->default_value("")->implicit_value(""), "Save non-localized images to a bag, defaults to input_bag + _nonloc_imgs.bag"); po::positional_options_description p; @@ -67,7 +64,6 @@ int main(int argc, char** argv) { const std::string input_bag = vm["bagfile"].as(); const std::string map_file = vm["map-file"].as(); - const std::string config_path = vm["config-path"].as(); // Only pass program name to free flyer so that boost command line options // are ignored when parsing gflags. @@ -95,8 +91,7 @@ int main(int argc, char** argv) { } lc::SetEnvironmentConfigs(world, robot_config_file); config_reader::ConfigReader config; - localization_analysis::MapMatcher map_matcher(input_bag, map_file, image_topic, output_bagfile, config_path_prefix, - save_noloc_imgs); + localization_analysis::MapMatcher map_matcher(input_bag, map_file, image_topic, output_bagfile, save_noloc_imgs); map_matcher.AddMapMatches(); ROS_INFO_STREAM("Using " << input_bag << " on map " << map_file); From 5d49bb70e6fe9fe1ba53c91356b1337160ec6630 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sat, 22 Jun 2024 21:12:27 -0700 Subject: [PATCH 12/61] added option to check essential matrix --- .../include/sparse_mapping/tensor.h | 6 ++ localization/sparse_mapping/src/sparse_map.cc | 11 +++ localization/sparse_mapping/src/tensor.cc | 67 +++++++++++++------ 3 files changed, 65 insertions(+), 19 deletions(-) diff --git a/localization/sparse_mapping/include/sparse_mapping/tensor.h b/localization/sparse_mapping/include/sparse_mapping/tensor.h index f9bdc0a11b..a6b911e59f 100644 --- a/localization/sparse_mapping/include/sparse_mapping/tensor.h +++ b/localization/sparse_mapping/include/sparse_mapping/tensor.h @@ -144,6 +144,12 @@ namespace sparse_mapping { void PrintTrackStats(std::vector >const& pid_to_cid_fid, std::string const& step); + // Filter the matches by a geometric constraint. Compute the essential matrix. + void FindEssentialAndInliers(Eigen::Matrix2Xd const& keypoints1, Eigen::Matrix2Xd const& keypoints2, + std::vector const& matches, camera::CameraParameters const& camera_params, + std::vector* inlier_matches, std::vector* vec_inliers, + Eigen::Matrix3d* essential_matrix); + void BuildMapFindEssentialAndInliers(const Eigen::Matrix2Xd & keypoints1, const Eigen::Matrix2Xd & keypoints2, const std::vector & matches, diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index 30e2e9c1ef..be498b03a2 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -66,6 +66,9 @@ DEFINE_bool(verbose_localization, false, "If true, list the images most similar to the one being localized."); DEFINE_bool(visualize_localization_matches, false, "If true, visualized matches between input image and each available map image during localization."); +DEFINE_bool(localization_check_essential_matrix, true, + "If true, verify a valid essential matrix can be calculated between the input image and each potential map " + "match image before adding map matches."); namespace sparse_mapping { @@ -716,6 +719,14 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const } } + if (FLAGS_localization_check_essential_matrix) { + std::vector inlier_matches; + std::vector vec_inliers; + Eigen::Matrix3d essential_matrix; + FindEssentialAndInliers(test_keypoints, cid_to_keypoint_map_[cid], all_matches[i], camera_params_, + &inlier_matches, &vec_inliers, &essential_matrix); + } + for (size_t j = 0; j < all_matches[i].size(); j++) { if (cid_fid_to_pid_[cid].count(all_matches[i][j].trainIdx) == 0) continue; diff --git a/localization/sparse_mapping/src/tensor.cc b/localization/sparse_mapping/src/tensor.cc index de2eb100af..c0c2a402af 100644 --- a/localization/sparse_mapping/src/tensor.cc +++ b/localization/sparse_mapping/src/tensor.cc @@ -1933,21 +1933,12 @@ void ReadAffineCSV(std::string const& input_filename, } // Filter the matches by a geometric constraint. Compute the essential matrix. -void BuildMapFindEssentialAndInliers(Eigen::Matrix2Xd const& keypoints1, - Eigen::Matrix2Xd const& keypoints2, - std::vector const& matches, - camera::CameraParameters const& camera_params, - bool compute_inliers_only, - size_t cam_a_idx, size_t cam_b_idx, - std::mutex * match_mutex, - CIDPairAffineMap * relative_affines, - std::vector * inlier_matches, - bool compute_rays_angle, - double * rays_angle) { +void FindEssentialAndInliers(Eigen::Matrix2Xd const& keypoints1, Eigen::Matrix2Xd const& keypoints2, + std::vector const& matches, camera::CameraParameters const& camera_params, + std::vector* inlier_matches, std::vector* vec_inliers, + Eigen::Matrix3d* essential_matrix) { // Initialize the outputs inlier_matches->clear(); - if (compute_rays_angle) - *rays_angle = 0.0; int pt_count = matches.size(); Eigen::MatrixXd observationsa(2, pt_count); @@ -1961,25 +1952,56 @@ void BuildMapFindEssentialAndInliers(Eigen::Matrix2Xd const& keypoints1, camera_params.GetUndistortedSize()[1]); Eigen::Matrix3d k = camera_params.GetIntrinsicMatrix(); - Eigen::Matrix3d e; // Calculate the essential matrix - std::vector vec_inliers; double error_max = std::numeric_limits::max(); double max_expected_error = 2.5; if (!interest_point::RobustEssential(k, k, observationsa, observationsb, - &e, &vec_inliers, + essential_matrix, vec_inliers, image_size, image_size, &error_max, max_expected_error)) { + VLOG(2) << " | Estimation of essential matrix failed!\n"; + return; + } + + int num_inliers = vec_inliers->size(); + inlier_matches->clear(); + inlier_matches->reserve(num_inliers); + for (int i = 0; i < num_inliers; i++) { + inlier_matches->push_back(matches[(*vec_inliers)[i]]); + } + return; +} + +// Filter the matches by a geometric constraint. Compute the essential matrix. +void BuildMapFindEssentialAndInliers(Eigen::Matrix2Xd const& keypoints1, + Eigen::Matrix2Xd const& keypoints2, + std::vector const& matches, + camera::CameraParameters const& camera_params, + bool compute_inliers_only, + size_t cam_a_idx, size_t cam_b_idx, + std::mutex * match_mutex, + CIDPairAffineMap * relative_affines, + std::vector * inlier_matches, + bool compute_rays_angle, + double * rays_angle) { + // Initialize the outputs + if (compute_rays_angle) + *rays_angle = 0.0; + + std::vector vec_inliers; + Eigen::Matrix3d e; + FindEssentialAndInliers(keypoints1, keypoints2, matches, camera_params, inlier_matches, &vec_inliers, &e); + if (!inlier_matches) { VLOG(2) << cam_a_idx << " " << cam_b_idx << " | Estimation of essential matrix failed!\n"; return; } - if (vec_inliers.size() < static_cast(FLAGS_min_valid)) { + if (inlier_matches->size() < static_cast(FLAGS_min_valid)) { VLOG(2) << cam_a_idx << " " << cam_b_idx - << " | Failed to get enough inliers " << vec_inliers.size(); + << " | Failed to get enough inliers " << inlier_matches->size(); return; } @@ -1989,7 +2011,6 @@ void BuildMapFindEssentialAndInliers(Eigen::Matrix2Xd const& keypoints1, int num_inliers = vec_inliers.size(); inlier_matches->clear(); inlier_matches->reserve(num_inliers); - std::vector observations2(2, Eigen::Matrix2Xd(2, num_inliers)); for (int i = 0; i < num_inliers; i++) { inlier_matches->push_back(matches[vec_inliers[i]]); } @@ -1999,6 +2020,14 @@ void BuildMapFindEssentialAndInliers(Eigen::Matrix2Xd const& keypoints1, // Estimate the best possible R & T from the found Essential Matrix Eigen::Matrix3d r; Eigen::Vector3d t; + int pt_count = matches.size(); + Eigen::MatrixXd observationsa(2, pt_count); + Eigen::MatrixXd observationsb(2, pt_count); + for (int i = 0; i < pt_count; i++) { + observationsa.col(i) = keypoints1.col(matches[i].queryIdx); + observationsb.col(i) = keypoints2.col(matches[i].trainIdx); + } + Eigen::Matrix3d k = camera_params.GetIntrinsicMatrix(); if (!interest_point::EstimateRTFromE(k, k, observationsa, observationsb, e, vec_inliers, &r, &t)) { From c8cf52093c1c220890d1eb3a5cc680154ebeb097 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sat, 22 Jun 2024 21:19:11 -0700 Subject: [PATCH 13/61] added check for inlier matches --- localization/sparse_mapping/src/sparse_map.cc | 1 + 1 file changed, 1 insertion(+) diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index be498b03a2..bbbfbb89af 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -725,6 +725,7 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const Eigen::Matrix3d essential_matrix; FindEssentialAndInliers(test_keypoints, cid_to_keypoint_map_[cid], all_matches[i], camera_params_, &inlier_matches, &vec_inliers, &essential_matrix); + all_matches[i] = inlier_matches; } for (size_t j = 0; j < all_matches[i].size(); j++) { From 1cedb9d4a4b94e5d49e2b3487cd33339ea139303 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sun, 23 Jun 2024 05:55:18 -0700 Subject: [PATCH 14/61] added size check for matches --- localization/sparse_mapping/src/sparse_map.cc | 3 +++ 1 file changed, 3 insertions(+) diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index bbbfbb89af..570bd609a0 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -719,10 +719,13 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const } } + if (all_matches[i].size() < 5) continue; + if (FLAGS_localization_check_essential_matrix) { std::vector inlier_matches; std::vector vec_inliers; Eigen::Matrix3d essential_matrix; + // TODO(rsoussan): Add param for num ransac iterations? Time this? (uses 4096 its...) FindEssentialAndInliers(test_keypoints, cid_to_keypoint_map_[cid], all_matches[i], camera_params_, &inlier_matches, &vec_inliers, &essential_matrix); all_matches[i] = inlier_matches; From 64c9b70e8bf0ff10e547964ad4ba7446fe34649c Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sun, 23 Jun 2024 09:12:16 -0700 Subject: [PATCH 15/61] added connectivity check --- .../include/sparse_mapping/sparse_map.h | 1 + localization/sparse_mapping/src/sparse_map.cc | 43 +++++++++++++++++-- 2 files changed, 40 insertions(+), 4 deletions(-) diff --git a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h index 5799f20c25..a750c1bb94 100644 --- a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h +++ b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h @@ -250,6 +250,7 @@ struct SparseMap { std::vector cid_to_descriptor_map_; // generated on load std::vector > cid_fid_to_pid_; + std::vector> cid_to_matching_cid_counts_; interest_point::FeatureDetector detector_; camera::CameraParameters camera_params_; diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index 570bd609a0..dc3dc89714 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -69,6 +69,9 @@ DEFINE_bool(visualize_localization_matches, false, DEFINE_bool(localization_check_essential_matrix, true, "If true, verify a valid essential matrix can be calculated between the input image and each potential map " "match image before adding map matches."); +DEFINE_bool(localization_add_similar_images, true, + "If true, for each cid matched to, also attempt to match to any cid with at least 5 of the same features " + "as the matched cid."); namespace sparse_mapping { @@ -399,12 +402,24 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { } Eigen::Vector3d pos(l.loc().x(), l.loc().y(), l.loc().z()); pid_to_xyz_[i] = pos; + std::unordered_set cids; for (int j = 0; j < l.match_size(); j++) { sparse_mapping_protobuf::Matching m = l.match(j); - if (!localization) + if (!localization) { pid_to_cid_fid_[i][m.camera_id()] = m.feature_id(); - else + } else { cid_fid_to_pid_[m.camera_id()][m.feature_id()] = i; + cids.emplace(m.camera_id()); + } + } + if (localization) { + // Update matching cid counts + for (int cid : cids) { + for (int matching_cid : cids) { + if (cid == matching_cid) continue; + cid_to_matching_cid_counts_[cid][matching_cid]++; + } + } } } @@ -699,12 +714,14 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const // We will not localize using all images having matches, there are too // many false positives that way. Instead, limit ourselves to the images // which have most observations in common with the current one. - std::vector similarity_rank(indices.size(), 0); - std::vector > all_matches(indices.size()); + std::vector similarity_rank; + std::vector> all_matches; int total = 0; // TODO(oalexan1): Use multiple threads here? for (size_t i = 0; i < indices.size(); i++) { int cid = indices[i]; + similarity_rank.emplace_back(0); + all_matches.emplace_back(std::vector()); interest_point::FindMatches(test_descriptors, cid_to_descriptor_map_[cid], &all_matches[i]); @@ -731,6 +748,24 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const all_matches[i] = inlier_matches; } + if (FLAGS_localization_add_similar_images) { + // Add cids with more than 5 of the same features as the current cid to the list of cids to match to. + for (auto matching_cid_it = cid_to_matching_cid_counts_[cid].rbegin(); + matching_cid_it != cid_to_matching_cid_counts_[cid].rend() && matching_cid_it->second > 5; + ++matching_cid_it) { + const int matching_cid = matching_cid_it->first; + bool add_cid = true; + // Make sure new matching cid isn't already in indices list + for (const auto already_added_cid : indices) { + if (already_added_cid == matching_cid) { + add_cid = false; + break; + } + } + if (add_cid) indices.emplace_back(matching_cid); + } + } + for (size_t j = 0; j < all_matches[i].size(); j++) { if (cid_fid_to_pid_[cid].count(all_matches[i][j].trainIdx) == 0) continue; From f8f142d5375594309b59fbef6ddac849828d6a31 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sun, 23 Jun 2024 10:07:26 -0700 Subject: [PATCH 16/61] bug fixes --- localization/localization_node/CMakeLists.txt | 2 ++ localization/localization_node/package.xml | 2 ++ localization/localization_node/src/localization.cc | 3 +++ localization/sparse_mapping/src/sparse_map.cc | 2 ++ tools/localization_analysis/src/map_matcher.cc | 1 - 5 files changed, 9 insertions(+), 1 deletion(-) diff --git a/localization/localization_node/CMakeLists.txt b/localization/localization_node/CMakeLists.txt index fd16021ae7..94ad104b2b 100644 --- a/localization/localization_node/CMakeLists.txt +++ b/localization/localization_node/CMakeLists.txt @@ -32,6 +32,7 @@ find_package(catkin2 REQUIRED COMPONENTS ff_util sparse_mapping msg_conversions + localization_common ) # System dependencies are found with CMake's conventions @@ -59,6 +60,7 @@ catkin_package( msg_conversions ff_util nodelet + localization_common ) diff --git a/localization/localization_node/package.xml b/localization/localization_node/package.xml index 8842c24650..72c1597176 100644 --- a/localization/localization_node/package.xml +++ b/localization/localization_node/package.xml @@ -27,6 +27,7 @@ sparse_mapping msg_conversions ff_util + localization_common roscpp message_runtime std_msgs @@ -40,6 +41,7 @@ sparse_mapping msg_conversions ff_util + localization_common diff --git a/localization/localization_node/src/localization.cc b/localization/localization_node/src/localization.cc index 1f8a0f7f7b..4ab86b185b 100644 --- a/localization/localization_node/src/localization.cc +++ b/localization/localization_node/src/localization.cc @@ -93,6 +93,9 @@ bool Localizer::Localize(cv_bridge::CvImageConstPtr image_ptr, ff_msgs::VisualLa vl->header.frame_id = "world"; map_->DetectFeatures(image_ptr->image, multithreaded, &image_descriptors, image_keypoints); + + // TODO(rsoussan): store last stamp, if less than certain time passed, add previous + // localization estimate as prior!!! camera::CameraModel camera(Eigen::Vector3d(), Eigen::Matrix3d::Identity(), map_->GetCameraParameters()); diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index dc3dc89714..a8730b7f2b 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -393,6 +393,8 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { // Create directly cid_fid_to_pid cid_fid_to_pid_.clear(); cid_fid_to_pid_.resize(cid_to_filename_.size(), std::map()); + cid_to_matching_cid_counts_.clear(); + cid_to_matching_cid_counts_.resize(cid_to_filename_.size(), std::map()); } for (int i = 0; i < num_landmarks; i++) { diff --git a/tools/localization_analysis/src/map_matcher.cc b/tools/localization_analysis/src/map_matcher.cc index 5196045847..fbf9265288 100644 --- a/tools/localization_analysis/src/map_matcher.cc +++ b/tools/localization_analysis/src/map_matcher.cc @@ -47,7 +47,6 @@ MapMatcher::MapMatcher(const std::string& input_bag_name, const std::string& map LogFatal("Failed to read config files."); } body_T_nav_cam_ = lc::LoadTransform(config, "nav_cam_transform"); - sparse_mapping_min_num_landmarks_ = mc::LoadInt(config, "loc_adder_min_num_matches"); if (!save_noloc_imgs.empty()) { nonloc_bag_.open(save_noloc_imgs, rosbag::bagmode::Write); } From d66da2ca977089429828b1a140cf3d4cea434829 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sun, 23 Jun 2024 10:15:28 -0700 Subject: [PATCH 17/61] added image for localization for debugging --- localization/localization_node/src/localization.cc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/localization/localization_node/src/localization.cc b/localization/localization_node/src/localization.cc index 4ab86b185b..0d49982d0f 100644 --- a/localization/localization_node/src/localization.cc +++ b/localization/localization_node/src/localization.cc @@ -102,7 +102,7 @@ bool Localizer::Localize(cv_bridge::CvImageConstPtr image_ptr, ff_msgs::VisualLa std::vector landmarks; std::vector observations; if (!map_->Localize(image_descriptors, *image_keypoints, - &camera, &landmarks, &observations)) { + &camera, &landmarks, &observations, nullptr, image_ptr->image)) { // LOG(INFO) << "Failed to localize image."; return false; } From 9c84220d6396f66e88f2a4c30eddd2209d80a61a Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sun, 23 Jun 2024 10:28:14 -0700 Subject: [PATCH 18/61] added loading keypoints --- localization/sparse_mapping/src/sparse_map.cc | 20 ++++++++----------- 1 file changed, 8 insertions(+), 12 deletions(-) diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index a8730b7f2b..dae70966f0 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -64,12 +64,12 @@ DEFINE_int32(num_extra_localization_db_images, 0, "Match this many extra images from the Vocab DB, only keep num_similar."); DEFINE_bool(verbose_localization, false, "If true, list the images most similar to the one being localized."); -DEFINE_bool(visualize_localization_matches, false, +DEFINE_bool(visualize_localization_matches, true, "If true, visualized matches between input image and each available map image during localization."); -DEFINE_bool(localization_check_essential_matrix, true, +DEFINE_bool(localization_check_essential_matrix, false, "If true, verify a valid essential matrix can be calculated between the input image and each potential map " "match image before adding map matches."); -DEFINE_bool(localization_add_similar_images, true, +DEFINE_bool(localization_add_similar_images, false, "If true, for each cid matched to, also attempt to match to any cid with at least 5 of the same features " "as the matched cid."); @@ -325,10 +325,8 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { cid_to_filename_.resize(num_frames); cid_to_descriptor_map_.resize(num_frames); - if (!localization) { - cid_to_keypoint_map_.resize(num_frames); - cid_to_cam_t_global_.resize(num_frames); - } + cid_to_keypoint_map_.resize(num_frames); + cid_to_cam_t_global_.resize(num_frames); // load each frame for (int cid = 0; cid < num_frames; cid++) { @@ -342,8 +340,7 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { cid_to_filename_[cid] = ""; // load keypoints - if (!localization) - cid_to_keypoint_map_[cid].resize(Eigen::NoChange_t(), frame.feature_size()); + cid_to_keypoint_map_[cid].resize(Eigen::NoChange_t(), frame.feature_size()); // Poke the first frame's first descriptor to see how long the // descriptor is. @@ -361,8 +358,7 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { sparse_mapping_protobuf::Feature feature = frame.feature(fid); // Copy the features - if (!localization) - cid_to_keypoint_map_[cid].col(fid) << feature.x(), feature.y(); + cid_to_keypoint_map_[cid].col(fid) << feature.x(), feature.y(); // Copy the descriptors memcpy(cid_to_descriptor_map_[cid].ptr(fid), // Destination @@ -371,7 +367,7 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { } // Load pose - if (frame.has_pose() && !localization) { + if (frame.has_pose()) { sparse_mapping_protobuf::Affine3d pose = frame.pose(); cid_to_cam_t_global_[cid].translation() << pose.t0(), pose.t1(), pose.t2(); From 807fed3d59c063c849e5884d55bdd89eff065c60 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sun, 23 Jun 2024 18:01:50 -0700 Subject: [PATCH 19/61] fixed saving and loading use clahe --- localization/sparse_mapping/src/sparse_map.cc | 21 +++++++++++++++---- 1 file changed, 17 insertions(+), 4 deletions(-) diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index dae70966f0..fac767f72a 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -86,7 +86,10 @@ SparseMap::SparseMap(const std::vector& filenames, const std::strin early_break_landmarks_(FLAGS_early_break_landmarks), histogram_equalization_(FLAGS_histogram_equalization), use_clahe_(FLAGS_use_clahe) { - clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); + if (histogram_equalization_ && use_clahe_) { + clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); + histogram_equalization_ = 3; + } cid_to_descriptor_map_.resize(cid_to_filename_.size()); // TODO(bcoltin): only record scale and orientation for opensift? cid_to_keypoint_map_.resize(cid_to_filename_.size()); @@ -100,7 +103,10 @@ SparseMap::SparseMap(const std::string& protobuf_file, bool localization) early_break_landmarks_(FLAGS_early_break_landmarks), histogram_equalization_(FLAGS_histogram_equalization), use_clahe_(FLAGS_use_clahe) { - clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); + if (histogram_equalization_ && use_clahe_) { + clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); + histogram_equalization_ = 3; + } // The above camera params used bad values because we are expected to reload // later. Load(protobuf_file, localization); @@ -117,7 +123,10 @@ SparseMap::SparseMap(const std::vector& cid_to_cam_t, const std early_break_landmarks_(FLAGS_early_break_landmarks), histogram_equalization_(FLAGS_histogram_equalization), use_clahe_(FLAGS_use_clahe) { - clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); + if (histogram_equalization_ && use_clahe_) { + clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); + histogram_equalization_ = 3; + } if (filenames.size() != cid_to_cam_t.size()) LOG(FATAL) << "Expecting as many images as cameras"; @@ -147,7 +156,10 @@ SparseMap::SparseMap(bool bundler_format, std::string const& filename, std::vect early_break_landmarks_(FLAGS_early_break_landmarks), histogram_equalization_(FLAGS_histogram_equalization), use_clahe_(FLAGS_use_clahe) { - clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); + if (histogram_equalization_ && use_clahe_) { + clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); + histogram_equalization_ = 3; + } std::string ext = ff_common::file_extension(filename); boost::to_lower(ext); @@ -438,6 +450,7 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { histogram_equalization_ == 3); use_clahe_ = histogram_equalization_ == 3 ? true : false; + if (use_clahe_) clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); // For backward compatibility with old maps, allow a map to have its // histogram_equalization flag unspecified, but it is best to avoid From 1d98bd78db3f60302c71b6cae00118b18c0a5332 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sun, 23 Jun 2024 18:30:48 -0700 Subject: [PATCH 20/61] added more verbose loc printing --- localization/sparse_mapping/src/sparse_map.cc | 31 ++++++++++++++++--- 1 file changed, 27 insertions(+), 4 deletions(-) diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index fac767f72a..9088458c9e 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -62,14 +62,14 @@ DEFINE_bool(use_clahe, false, "If true, use CLAHE if histogram equalization enabled."); DEFINE_int32(num_extra_localization_db_images, 0, "Match this many extra images from the Vocab DB, only keep num_similar."); -DEFINE_bool(verbose_localization, false, +DEFINE_bool(verbose_localization, true, "If true, list the images most similar to the one being localized."); -DEFINE_bool(visualize_localization_matches, true, +DEFINE_bool(visualize_localization_matches, false, "If true, visualized matches between input image and each available map image during localization."); -DEFINE_bool(localization_check_essential_matrix, false, +DEFINE_bool(localization_check_essential_matrix, true, "If true, verify a valid essential matrix can be calculated between the input image and each potential map " "match image before adding map matches."); -DEFINE_bool(localization_add_similar_images, false, +DEFINE_bool(localization_add_similar_images, true, "If true, for each cid matched to, also attempt to match to any cid with at least 5 of the same features " "as the matched cid."); @@ -728,17 +728,25 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const std::vector similarity_rank; std::vector> all_matches; int total = 0; + if (FLAGS_verbose_localization) { + for (size_t i = 0; i < indices.size(); i++) { + std::cout << "Potential matching cid: " << indices[i] << std::endl; + } + } // TODO(oalexan1): Use multiple threads here? for (size_t i = 0; i < indices.size(); i++) { int cid = indices[i]; + if (FLAGS_verbose_localization) std::cout << "Checking index: " << i << ", cid: " << cid << std::endl; similarity_rank.emplace_back(0); all_matches.emplace_back(std::vector()); interest_point::FindMatches(test_descriptors, cid_to_descriptor_map_[cid], &all_matches[i]); + if (FLAGS_visualize_localization_matches && !image.empty()) { const auto map_filename = cid_to_filename_[cid]; + std::cout << "CID: " << cid << ", filename: " << map_filename << std::endl; const auto map_image = cv::imread(map_filename, cv::IMREAD_GRAYSCALE); if (map_image.empty()) { LOG(ERROR) << "Failed to load map image: " << map_filename; @@ -750,6 +758,8 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const if (all_matches[i].size() < 5) continue; if (FLAGS_localization_check_essential_matrix) { + if (FLAGS_verbose_localization) + std::cout << "Matches before essential filtering: " << all_matches[i].size() << std::endl; std::vector inlier_matches; std::vector vec_inliers; Eigen::Matrix3d essential_matrix; @@ -757,9 +767,13 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const FindEssentialAndInliers(test_keypoints, cid_to_keypoint_map_[cid], all_matches[i], camera_params_, &inlier_matches, &vec_inliers, &essential_matrix); all_matches[i] = inlier_matches; + if (FLAGS_verbose_localization) + std::cout << "Matches after essential filtering: " << all_matches[i].size() << std::endl; } if (FLAGS_localization_add_similar_images) { + if (FLAGS_verbose_localization) + std::cout << "Num indices before adding similar images: " << indices.size() << std::endl; // Add cids with more than 5 of the same features as the current cid to the list of cids to match to. for (auto matching_cid_it = cid_to_matching_cid_counts_[cid].rbegin(); matching_cid_it != cid_to_matching_cid_counts_[cid].rend() && matching_cid_it->second > 5; @@ -775,6 +789,8 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const } if (add_cid) indices.emplace_back(matching_cid); } + if (FLAGS_verbose_localization) + std::cout << "Num indices after adding similar images: " << indices.size() << std::endl; } for (size_t j = 0; j < all_matches[i].size(); j++) { @@ -792,6 +808,13 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const break; } + // Check if enough matches found for estimating pose + if (total < 5) { + if (FLAGS_verbose_localization) + std::cout << "Too few matches: " << total << std::endl; + return false; + } + std::vector observations; std::vector landmarks; std::vector highly_ranked = ff_common::rv_order(similarity_rank); From 76eec3d3d180d61b4c6b84be6011f63ee61862d7 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sun, 23 Jun 2024 19:17:21 -0700 Subject: [PATCH 21/61] updated values --- astrobee/config/localization.config | 10 +++++----- localization/interest_point/src/matching.cc | 2 +- localization/localization_node/src/localization.cc | 4 ++-- localization/sparse_mapping/src/sparse_mapping.cc | 7 +++++-- 4 files changed, 13 insertions(+), 10 deletions(-) diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index 2f02d6bf12..57d0f6cac9 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -19,13 +19,13 @@ num_similar = 20 ransac_inlier_tolerance = 5 ransac_iterations = 100 early_break_landmarks = 100 -histogram_equalization = 1 -min_features = 200 -max_features = 800 +histogram_equalization = 3 +min_features = 400 +max_features = 3000 detection_retries = 1 num_threads = 1 -min_brisk_threshold = 20.0 -default_brisk_threshold = 90.0 +min_brisk_threshold = 10.0 +default_brisk_threshold = 20.0 max_brisk_threshold = 110.0 matched_features_on = false all_features_on = false diff --git a/localization/interest_point/src/matching.cc b/localization/interest_point/src/matching.cc index 185174e8ea..fbf0098bc8 100644 --- a/localization/interest_point/src/matching.cc +++ b/localization/interest_point/src/matching.cc @@ -62,7 +62,7 @@ DEFINE_int32(min_brisk_features, 400, "Minimum number of features to be computed using ORGBRISK."); DEFINE_int32(max_brisk_features, 3000, "Maximum number of features to be computed using ORGBRISK."); -DEFINE_double(min_brisk_threshold, 20, +DEFINE_double(min_brisk_threshold, 10, "Minimum threshold for feature detection using ORGBRISK."); DEFINE_double(default_brisk_threshold, 20, "Default threshold for feature detection using ORGBRISK."); diff --git a/localization/localization_node/src/localization.cc b/localization/localization_node/src/localization.cc index 0d49982d0f..9a66dbb93c 100644 --- a/localization/localization_node/src/localization.cc +++ b/localization/localization_node/src/localization.cc @@ -56,9 +56,9 @@ void Localizer::ReadParams(config_reader::ConfigReader* config) { // For the brisk thresholds and other values, quietly assume some defaults if (!config->GetReal("min_brisk_threshold", &min_brisk_threshold)) - min_brisk_threshold = 20.0; + min_brisk_threshold = 10.0; if (!config->GetReal("default_brisk_threshold", &default_brisk_threshold)) - default_brisk_threshold = 90.0; + default_brisk_threshold = 20.0; if (!config->GetReal("max_brisk_threshold", &max_brisk_threshold)) max_brisk_threshold = 110.0; if (!config->GetInt("early_break_landmarks", &early_break_landmarks)) diff --git a/localization/sparse_mapping/src/sparse_mapping.cc b/localization/sparse_mapping/src/sparse_mapping.cc index 95d0b874ae..a3590c18b7 100644 --- a/localization/sparse_mapping/src/sparse_mapping.cc +++ b/localization/sparse_mapping/src/sparse_mapping.cc @@ -117,9 +117,12 @@ namespace sparse_mapping { // of unknown values, but intolerant when true and false are mixed. void sparse_mapping::HistogramEqualizationCheck(int histogram_equalization1, int histogram_equalization2) { - if ( (histogram_equalization1 == 0 && histogram_equalization2 == 1) || - (histogram_equalization1 == 1 && histogram_equalization2 == 0) ) + // Ignore if either has unknown equalization value + if (histogram_equalization1 == 2 || histogram_equalization2 == 2) { + return; + } else if (histogram_equalization1 != histogram_equalization2) { LOG(FATAL) << "Incompatible values of histogram equalization detected."; + } } bool sparse_mapping::IsBinaryDescriptor(std::string const& descriptor) { From fb8270eb1de012bcdb1ea88995c9a00875b5d221 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sun, 23 Jun 2024 19:34:01 -0700 Subject: [PATCH 22/61] updated loc config vals --- astrobee/config/localization.config | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index 57d0f6cac9..f20217598d 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -16,13 +16,13 @@ -- under the License. num_similar = 20 -ransac_inlier_tolerance = 5 -ransac_iterations = 100 +ransac_inlier_tolerance = 3 +ransac_iterations = 1000 early_break_landmarks = 100 histogram_equalization = 3 min_features = 400 max_features = 3000 -detection_retries = 1 +detection_retries = 5 num_threads = 1 min_brisk_threshold = 10.0 default_brisk_threshold = 20.0 From 04584a80a3c039a32b31ec36717e9b68f14876db Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sun, 23 Jun 2024 19:35:59 -0700 Subject: [PATCH 23/61] updated brisk thresh --- astrobee/config/localization.config | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index f20217598d..72b7cc50dc 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -25,7 +25,7 @@ max_features = 3000 detection_retries = 5 num_threads = 1 min_brisk_threshold = 10.0 -default_brisk_threshold = 20.0 +default_brisk_threshold = 40.0 max_brisk_threshold = 110.0 matched_features_on = false all_features_on = false From b194b86bbc09a384c6c987f850313b8e3b768cde Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sun, 23 Jun 2024 20:10:50 -0700 Subject: [PATCH 24/61] fixed hamming threshold --- localization/interest_point/src/matching.cc | 2 +- localization/sparse_mapping/src/sparse_map.cc | 4 +++- 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/localization/interest_point/src/matching.cc b/localization/interest_point/src/matching.cc index fbf0098bc8..60c7397987 100644 --- a/localization/interest_point/src/matching.cc +++ b/localization/interest_point/src/matching.cc @@ -32,7 +32,7 @@ // same settings! // TODO(oalexan1): Ideally the settings used here must be saved in the // map file, for the localize executable to read them from there. -DEFINE_int32(hamming_distance, 70, +DEFINE_int32(hamming_distance, 110, "A smaller value keeps fewer but more reliable binary descriptor matches."); DEFINE_double(binary_goodness_ratio, 0.8, "A smaller value keeps fewer but more reliable binary descriptor matches."); diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index 9088458c9e..5cb0a0e1d9 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -62,7 +62,7 @@ DEFINE_bool(use_clahe, false, "If true, use CLAHE if histogram equalization enabled."); DEFINE_int32(num_extra_localization_db_images, 0, "Match this many extra images from the Vocab DB, only keep num_similar."); -DEFINE_bool(verbose_localization, true, +DEFINE_bool(verbose_localization, false, "If true, list the images most similar to the one being localized."); DEFINE_bool(visualize_localization_matches, false, "If true, visualized matches between input image and each available map image during localization."); @@ -771,6 +771,8 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const std::cout << "Matches after essential filtering: " << all_matches[i].size() << std::endl; } + if (all_matches[i].size() < 5) continue; + if (FLAGS_localization_add_similar_images) { if (FLAGS_verbose_localization) std::cout << "Num indices before adding similar images: " << indices.size() << std::endl; From b59c3acb90ea8cb0ecfa1d4606c5c56a6ae09745 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sun, 23 Jun 2024 21:25:15 -0700 Subject: [PATCH 25/61] increased min features --- astrobee/config/localization.config | 2 +- localization/interest_point/src/matching.cc | 5 ++++- 2 files changed, 5 insertions(+), 2 deletions(-) diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index 72b7cc50dc..e1910cde7a 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -20,7 +20,7 @@ ransac_inlier_tolerance = 3 ransac_iterations = 1000 early_break_landmarks = 100 histogram_equalization = 3 -min_features = 400 +min_features = 1000 max_features = 3000 detection_retries = 5 num_threads = 1 diff --git a/localization/interest_point/src/matching.cc b/localization/interest_point/src/matching.cc index 60c7397987..2a8a7642f3 100644 --- a/localization/interest_point/src/matching.cc +++ b/localization/interest_point/src/matching.cc @@ -58,7 +58,7 @@ DEFINE_double(default_surf_threshold, 10, DEFINE_double(max_surf_threshold, 1000, "Maximum threshold for feature detection using SURF."); // Binary detector -DEFINE_int32(min_brisk_features, 400, +DEFINE_int32(min_brisk_features, 1000, "Minimum number of features to be computed using ORGBRISK."); DEFINE_int32(max_brisk_features, 3000, "Maximum number of features to be computed using ORGBRISK."); @@ -194,6 +194,9 @@ namespace interest_point { } virtual void DetectImpl(const cv::Mat& image, std::vector* keypoints) { + // std::cout << "detect max thresh: " << max_thresh_ << ", min: " << min_thresh_ << ", def: " << default_thresh_ + // << ", min feat: " << min_features_ << ", max_feat: " << max_features_ << ", dyn thresh: " << dynamic_thresh_ << + // std::endl; brisk_->detect(image, *keypoints); } virtual void ComputeImpl(const cv::Mat& image, std::vector* keypoints, From 9f9754272ed4c64fcd0adc774d6d600ae98f3325 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Sun, 23 Jun 2024 21:59:46 -0700 Subject: [PATCH 26/61] added check for best previous cid, added inserting similar images in place in indices --- .../include/sparse_mapping/sparse_map.h | 3 ++ localization/sparse_mapping/src/sparse_map.cc | 36 ++++++++++++++++++- 2 files changed, 38 insertions(+), 1 deletion(-) diff --git a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h index a750c1bb94..08d2e0b89b 100644 --- a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h +++ b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h @@ -26,6 +26,7 @@ #include #include +#include #include #include #include @@ -278,7 +279,9 @@ struct SparseMap { std::vector user_cid_to_keypoint_map_; std::vector > user_pid_to_cid_fid_; std::vector user_pid_to_xyz_; + cv::Ptr clahe_; + boost::optional best_previous_cid_; std::mutex mutex_detector_; private: diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index 5cb0a0e1d9..b2a7ab5fc7 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -72,6 +72,9 @@ DEFINE_bool(localization_check_essential_matrix, true, DEFINE_bool(localization_add_similar_images, true, "If true, for each cid matched to, also attempt to match to any cid with at least 5 of the same features " "as the matched cid."); +DEFINE_bool(localization_add_best_previous_cid, true, + "If true, add previous cid with the most matches to list of cids to check for" + "matches with."); namespace sparse_mapping { @@ -715,6 +718,20 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const indices.push_back(cid); } + if (FLAGS_localization_add_best_previous_cid && best_previous_cid_) { + bool add_cid = true; + for (const auto cid : indices) { + if (cid == *best_previous_cid_) { + add_cid = false; + break; + } + } + if (add_cid) { + indices.insert(indices.begin(), *best_previous_cid_); + } + best_previous_cid_ = boost::none; + } + // To turn on verbose localization for debugging // google::SetCommandLineOption("verbose_localization", "true"); @@ -777,6 +794,7 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const if (FLAGS_verbose_localization) std::cout << "Num indices before adding similar images: " << indices.size() << std::endl; // Add cids with more than 5 of the same features as the current cid to the list of cids to match to. + int index = i + 1; for (auto matching_cid_it = cid_to_matching_cid_counts_[cid].rbegin(); matching_cid_it != cid_to_matching_cid_counts_[cid].rend() && matching_cid_it->second > 5; ++matching_cid_it) { @@ -789,7 +807,11 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const break; } } - if (add_cid) indices.emplace_back(matching_cid); + // Make new matching cid the next cid to match to + if (add_cid) { + indices.insert(indices.begin() + index, matching_cid); + ++index; + } } if (FLAGS_verbose_localization) std::cout << "Num indices after adding similar images: " << indices.size() << std::endl; @@ -817,6 +839,18 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const return false; } + // Update best previous cid if there were enough matches in total + if (FLAGS_localization_add_best_previous_cid) { + // Make sure to only add best previous cid if it has at least 5 matches + int most_matches = 5; + for (int i = 0; i < indices.size(); ++i) { + if (all_matches[i].size() > most_matches) { + best_previous_cid_ = indices[i]; + most_matches = all_matches[i].size(); + } + } + } + std::vector observations; std::vector landmarks; std::vector highly_ranked = ff_common::rv_order(similarity_rank); From 86987f908131c87cd3dd5f768966f73d2e6910e6 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Mon, 24 Jun 2024 06:22:09 -0700 Subject: [PATCH 27/61] fixed bug for best previous cid --- localization/sparse_mapping/src/sparse_map.cc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index b2a7ab5fc7..a95c1b48f7 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -843,7 +843,7 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const if (FLAGS_localization_add_best_previous_cid) { // Make sure to only add best previous cid if it has at least 5 matches int most_matches = 5; - for (int i = 0; i < indices.size(); ++i) { + for (int i = 0; i < all_matches.size(); ++i) { if (all_matches[i].size() > most_matches) { best_previous_cid_ = indices[i]; most_matches = all_matches[i].size(); From 85dbf82bd56b8568945acb88eaa321cc6a1f8b1f Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Mon, 24 Jun 2024 07:24:23 -0700 Subject: [PATCH 28/61] updated default brisk threshold --- astrobee/config/localization.config | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index e1910cde7a..b64914e864 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -25,7 +25,7 @@ max_features = 3000 detection_retries = 5 num_threads = 1 min_brisk_threshold = 10.0 -default_brisk_threshold = 40.0 +default_brisk_threshold = 20.0 max_brisk_threshold = 110.0 matched_features_on = false all_features_on = false From b10fd2b5ddfafb60a6040bde4e9b1322917eb55b Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Mon, 24 Jun 2024 08:49:20 -0700 Subject: [PATCH 29/61] tuned vals --- localization/interest_point/src/matching.cc | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/localization/interest_point/src/matching.cc b/localization/interest_point/src/matching.cc index 2a8a7642f3..1c2d0534d0 100644 --- a/localization/interest_point/src/matching.cc +++ b/localization/interest_point/src/matching.cc @@ -32,7 +32,7 @@ // same settings! // TODO(oalexan1): Ideally the settings used here must be saved in the // map file, for the localize executable to read them from there. -DEFINE_int32(hamming_distance, 110, +DEFINE_int32(hamming_distance, 85, "A smaller value keeps fewer but more reliable binary descriptor matches."); DEFINE_double(binary_goodness_ratio, 0.8, "A smaller value keeps fewer but more reliable binary descriptor matches."); @@ -60,7 +60,7 @@ DEFINE_double(max_surf_threshold, 1000, // Binary detector DEFINE_int32(min_brisk_features, 1000, "Minimum number of features to be computed using ORGBRISK."); -DEFINE_int32(max_brisk_features, 3000, +DEFINE_int32(max_brisk_features, 5000, "Maximum number of features to be computed using ORGBRISK."); DEFINE_double(min_brisk_threshold, 10, "Minimum threshold for feature detection using ORGBRISK."); From 3bb9088bd4f02f54533221c9e715b8c54b30f593 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Mon, 24 Jun 2024 15:14:23 -0700 Subject: [PATCH 30/61] fixed avoid adding loading keypoints when in localization mode --- localization/sparse_mapping/src/sparse_map.cc | 22 +++++++++++++------ 1 file changed, 15 insertions(+), 7 deletions(-) diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index a95c1b48f7..ecf55393f7 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -340,8 +340,10 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { cid_to_filename_.resize(num_frames); cid_to_descriptor_map_.resize(num_frames); - cid_to_keypoint_map_.resize(num_frames); - cid_to_cam_t_global_.resize(num_frames); + if (!localization || FLAGS_visualize_localization_matches) { + cid_to_keypoint_map_.resize(num_frames); + cid_to_cam_t_global_.resize(num_frames); + } // load each frame for (int cid = 0; cid < num_frames; cid++) { @@ -354,8 +356,11 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { else cid_to_filename_[cid] = ""; - // load keypoints - cid_to_keypoint_map_[cid].resize(Eigen::NoChange_t(), frame.feature_size()); + + if (!localization || FLAGS_visualize_localization_matches) { + // load keypoints + cid_to_keypoint_map_[cid].resize(Eigen::NoChange_t(), frame.feature_size()); + } // Poke the first frame's first descriptor to see how long the // descriptor is. @@ -372,8 +377,11 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { for (int fid = 0; fid < frame.feature_size(); fid++) { sparse_mapping_protobuf::Feature feature = frame.feature(fid); - // Copy the features - cid_to_keypoint_map_[cid].col(fid) << feature.x(), feature.y(); + + if (!localization || FLAGS_visualize_localization_matches) { + // Copy the features + cid_to_keypoint_map_[cid].col(fid) << feature.x(), feature.y(); + } // Copy the descriptors memcpy(cid_to_descriptor_map_[cid].ptr(fid), // Destination @@ -382,7 +390,7 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { } // Load pose - if (frame.has_pose()) { + if (frame.has_pose() && !localization) { sparse_mapping_protobuf::Affine3d pose = frame.pose(); cid_to_cam_t_global_[cid].translation() << pose.t0(), pose.t1(), pose.t2(); From 15717de6b6817351ffd733cd460bfe3b63da8bf4 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Mon, 24 Jun 2024 22:02:14 -0700 Subject: [PATCH 31/61] added loc params, added different params for brisk vs. teblid --- astrobee/config/localization.config | 58 +++++-- .../include/interest_point/matching.h | 9 +- localization/interest_point/src/matching.cc | 18 ++- .../include/localization_node/localization.h | 5 +- .../localization_node/src/localization.cc | 89 ++++++----- .../src/localization_nodelet.cc | 6 +- .../sparse_mapping/localization_parameters.h | 41 +++++ .../include/sparse_mapping/sparse_map.h | 47 ++---- localization/sparse_mapping/src/sparse_map.cc | 147 ++++++++---------- localization/sparse_mapping/src/tensor.cc | 2 +- .../src/live_measurement_simulator.cc | 2 +- 11 files changed, 230 insertions(+), 194 deletions(-) create mode 100644 localization/sparse_mapping/include/sparse_mapping/localization_parameters.h diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index b64914e864..8332230f4b 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -15,17 +15,51 @@ -- License for the specific language governing permissions and limitations -- under the License. -num_similar = 20 -ransac_inlier_tolerance = 3 -ransac_iterations = 1000 -early_break_landmarks = 100 -histogram_equalization = 3 -min_features = 1000 -max_features = 3000 -detection_retries = 5 -num_threads = 1 -min_brisk_threshold = 10.0 -default_brisk_threshold = 20.0 -max_brisk_threshold = 110.0 matched_features_on = false all_features_on = false +num_threads = 1 +verbose_localization = false +visualize_localization_matches = false + +-- BRISK +brisk_num_similar = 20 +brisk_ransac_inlier_tolerance = 5 +brisk_num_ransac_iterations = 100 +brisk_early_break_landmarks = 100 +brisk_histogram_equalization = 1 +brisk_check_essential_matrix = false +brisk_add_similar_images = false +brisk_add_best_previous_image = false +brisk_hamming_distance = 90 +brisk_goodness_ratio = 0.8 +brisk_use_clahe_ = false +brisk_num_extra_localization_db_images = 0 +-- Detection Params +brisk_min_threshold = 20.0 +brisk_default_threshold = 90.0 +brisk_max_threshold = 110.0 +brisk_min_features = 200 +brisk_max_features = 800 +brisk_detection_retries = 1 + +-- TEBLID +teblid_num_similar = 20 +teblid_ransac_inlier_tolerance = 3 +teblid_num_ransac_iterations = 1000 +teblid_early_break_landmarks = 100 +teblid_histogram_equalization = 3 +teblid_check_essential_matrix = false +teblid_add_similar_images = true +teblid_add_best_previous_image = true +teblid_hamming_distance = 85 +teblid_goodness_ratio = 0.8 +teblid_use_clahe_ = false +teblid_num_extra_localization_db_images = 0 + +-- Detection Params +teblid_min_threshold = 10.0 +teblid_default_threshold = 20.0 +teblid_max_threshold = 110.0 +teblid_min_features = 1000 +teblid_max_features = 3000 +teblid_detection_retries = 5 diff --git a/localization/interest_point/include/interest_point/matching.h b/localization/interest_point/include/interest_point/matching.h index e2c2040e9f..408e4e521d 100644 --- a/localization/interest_point/include/interest_point/matching.h +++ b/localization/interest_point/include/interest_point/matching.h @@ -18,6 +18,7 @@ #ifndef INTEREST_POINT_MATCHING_H_ #define INTEREST_POINT_MATCHING_H_ +#include #include #include @@ -87,10 +88,12 @@ namespace interest_point { * descriptor is what opencv descriptor was used to make the descriptors * the descriptor maps are the features in the two images * matches is output to contain the matching features between the two images + * Optionally pass hamming distance and goodness ratio, otherwise flag + * values are used. **/ - void FindMatches(const cv::Mat & img1_descriptor_map, - const cv::Mat & img2_descriptor_map, - std::vector * matches); + void FindMatches(const cv::Mat& img1_descriptor_map, const cv::Mat& img2_descriptor_map, + std::vector* matches, boost::optional hamming_distance = boost::none, + boost::optional goodness_ratio = boost::none); } // namespace interest_point #endif // INTEREST_POINT_MATCHING_H_ diff --git a/localization/interest_point/src/matching.cc b/localization/interest_point/src/matching.cc index 1c2d0534d0..0f2a343421 100644 --- a/localization/interest_point/src/matching.cc +++ b/localization/interest_point/src/matching.cc @@ -34,10 +34,8 @@ // map file, for the localize executable to read them from there. DEFINE_int32(hamming_distance, 85, "A smaller value keeps fewer but more reliable binary descriptor matches."); -DEFINE_double(binary_goodness_ratio, 0.8, - "A smaller value keeps fewer but more reliable binary descriptor matches."); DEFINE_double(goodness_ratio, 0.8, - "A smaller value keeps fewer but more reliable float descriptor matches."); + "A smaller value keeps fewer but more reliable descriptor matches."); DEFINE_int32(orgbrisk_octaves, 4, "Number of octaves, or scale spaces, that BRISK will evaluate."); DEFINE_double(orgbrisk_pattern_scale, 1.0, @@ -311,12 +309,16 @@ namespace interest_point { } } - void FindMatches(const cv::Mat & img1_descriptor_map, - const cv::Mat & img2_descriptor_map, std::vector * matches) { + void FindMatches(const cv::Mat& img1_descriptor_map, const cv::Mat& img2_descriptor_map, + std::vector* matches, boost::optional hamming_distance, + boost::optional goodness_ratio) { CHECK(img1_descriptor_map.depth() == img2_descriptor_map.depth()) << "Mixed descriptor types. Did you mash BRISK with SIFT/SURF?"; + if (!hamming_distance) hamming_distance = FLAGS_hamming_distance; + if (!goodness_ratio) goodness_ratio = FLAGS_goodness_ratio; + // Check for early exit conditions matches->clear(); if (img1_descriptor_map.rows == 0 || @@ -331,13 +333,13 @@ namespace interest_point { matches->clear(); matches->reserve(possible_matches.size()); for (std::vector const& best_pair : possible_matches) { - if (best_pair.size() == 0 || best_pair.at(0).distance > FLAGS_hamming_distance) continue; + if (best_pair.size() == 0 || best_pair.at(0).distance > *hamming_distance) continue; if (best_pair.size() == 1) { // This was the only best match, push it. matches->push_back(best_pair.at(0)); } else { // Push back a match only if it is a certain percent better than the next best. - if (best_pair.at(0).distance < FLAGS_binary_goodness_ratio * best_pair.at(1).distance) { + if (best_pair.at(0).distance < *goodness_ratio * best_pair.at(1).distance) { matches->push_back(best_pair[0]); } } @@ -355,7 +357,7 @@ namespace interest_point { matches->push_back(best_pair.at(0)); } else { // Push back a match only if it is 25% better than the next best. - if (best_pair.at(0).distance < FLAGS_goodness_ratio * best_pair.at(1).distance) { + if (best_pair.at(0).distance < *goodness_ratio * best_pair.at(1).distance) { matches->push_back(best_pair[0]); } } diff --git a/localization/localization_node/include/localization_node/localization.h b/localization/localization_node/include/localization_node/localization.h index ccfd67b7f0..48c6f73df3 100644 --- a/localization/localization_node/include/localization_node/localization.h +++ b/localization/localization_node/include/localization_node/localization.h @@ -30,9 +30,8 @@ namespace localization_node { class Localizer { public: - explicit Localizer(sparse_mapping::SparseMap* comp_map_ptr); - ~Localizer(); - void ReadParams(config_reader::ConfigReader* config); + explicit Localizer(sparse_mapping::SparseMap* map); + void ReadParams(); bool Localize(cv_bridge::CvImageConstPtr image_ptr, ff_msgs::VisualLandmarks* vl, Eigen::Matrix2Xd* image_keypoints = NULL); private: diff --git a/localization/localization_node/src/localization.cc b/localization/localization_node/src/localization.cc index 9a66dbb93c..0e0654a652 100644 --- a/localization/localization_node/src/localization.cc +++ b/localization/localization_node/src/localization.cc @@ -27,55 +27,62 @@ namespace localization_node { -Localizer::Localizer(sparse_mapping::SparseMap* comp_map_ptr) : - map_(comp_map_ptr) { -} +Localizer::Localizer(sparse_mapping::SparseMap* map): map_(map) {} + +void Localizer::ReadParams() { + config_reader::ConfigReader config; + config.AddFile("cameras.config"); + config.AddFile("localization.config"); + if (!config.ReadFiles()) { + ROS_ERROR("Failed to read config files."); + return; + } -Localizer::~Localizer(void) { -} + camera::CameraParameters cam_params(&config, "nav_cam"); + std::string prefix; + const auto detector_name = map_->GetDetectorName(); + if (detector_name == "ORGBRISK") { + prefix = "brisk_"; + } else if (detector_name == "TEBLID") { + prefix = "teblid_"; + } else { + ROS_FATAL_STREAM("Invalid detector: " << detector_name); + } -void Localizer::ReadParams(config_reader::ConfigReader* config) { - int num_similar, ransac_inlier_tolerance, ransac_iterations, early_break_landmarks, histogram_equalization; + // Loc params + sparse_mapping::LocalizationParameters loc_params; + LOAD_PARAM(loc_params.num_similar, config, prefix); + LOAD_PARAM(loc_params.ransac_inlier_tolerance, config, prefix); + LOAD_PARAM(loc_params.num_ransac_iterations, config, prefix); + LOAD_PARAM(loc_params.early_break_landmarks, config, prefix); + LOAD_PARAM(loc_params.histogram_equalization, config, prefix); + LOAD_PARAM(loc_params.check_essential_matrix, config, prefix); + LOAD_PARAM(loc_params.add_similar_images, config, prefix); + LOAD_PARAM(loc_params.add_best_previous_image, config, prefix); + LOAD_PARAM(loc_params.hamming_distance, config, prefix); + LOAD_PARAM(loc_params.goodness_ratio, config, prefix); + LOAD_PARAM(loc_params.num_extra_localization_db_images, config, prefix); + LOAD_PARAM(loc_params.verbose_localization, config, ""); + LOAD_PARAM(loc_params.visualize_localization_matches, config, ""); + + // Detector Params + double min_threshold, default_threshold, max_threshold, goodness_ratio; int min_features, max_features, detection_retries; - double min_brisk_threshold, default_brisk_threshold, max_brisk_threshold; - camera::CameraParameters cam_params(config, "nav_cam"); - if (!config->GetInt("num_similar", &num_similar)) - ROS_FATAL("num_similar not specified in localization."); - if (!config->GetInt("ransac_inlier_tolerance", &ransac_inlier_tolerance)) - ROS_FATAL("ransac_inlier_tolerance not specified in localization."); - if (!config->GetInt("ransac_iterations", &ransac_iterations)) - ROS_FATAL("ransac_iterations not specified in localization."); - if (!config->GetInt("min_features", &min_features)) - ROS_FATAL("min_features not specified in localization."); - if (!config->GetInt("max_features", &max_features)) - ROS_FATAL("max_features not specified in localization."); - if (!config->GetInt("detection_retries", &detection_retries)) - ROS_FATAL("detection_retries not specified in localization."); - if (!config->GetInt("histogram_equalization", &histogram_equalization)) - ROS_FATAL("histogram_equalization not specified in localization."); - - // For the brisk thresholds and other values, quietly assume some defaults - if (!config->GetReal("min_brisk_threshold", &min_brisk_threshold)) - min_brisk_threshold = 10.0; - if (!config->GetReal("default_brisk_threshold", &default_brisk_threshold)) - default_brisk_threshold = 20.0; - if (!config->GetReal("max_brisk_threshold", &max_brisk_threshold)) - max_brisk_threshold = 110.0; - if (!config->GetInt("early_break_landmarks", &early_break_landmarks)) - early_break_landmarks = 100; + LOAD_PARAM(min_threshold, config, prefix); + LOAD_PARAM(default_threshold, config, prefix); + LOAD_PARAM(max_threshold, config, prefix); + LOAD_PARAM(detection_retries, config, prefix); + LOAD_PARAM(min_features, config, prefix); + LOAD_PARAM(max_features, config, prefix); // This check must happen before the histogram_equalization flag is set into the map // to compare with what is there already. sparse_mapping::HistogramEqualizationCheck(map_->GetHistogramEqualization(), - histogram_equalization); + loc_params.histogram_equalization); map_->SetCameraParameters(cam_params); - map_->SetNumSimilar(num_similar); - map_->SetRansacInlierTolerance(ransac_inlier_tolerance); - map_->SetRansacIterations(ransac_iterations); - map_->SetEarlyBreakLandmarks(early_break_landmarks); - map_->SetHistogramEqualization(histogram_equalization); + map_->SetLocParams(loc_params); map_->SetDetectorParams(min_features, max_features, detection_retries, - min_brisk_threshold, default_brisk_threshold, max_brisk_threshold); + min_threshold, default_threshold, max_threshold); } bool Localizer::Localize(cv_bridge::CvImageConstPtr image_ptr, ff_msgs::VisualLandmarks* vl, @@ -94,8 +101,6 @@ bool Localizer::Localize(cv_bridge::CvImageConstPtr image_ptr, ff_msgs::VisualLa map_->DetectFeatures(image_ptr->image, multithreaded, &image_descriptors, image_keypoints); - // TODO(rsoussan): store last stamp, if less than certain time passed, add previous - // localization estimate as prior!!! camera::CameraModel camera(Eigen::Vector3d(), Eigen::Matrix3d::Identity(), map_->GetCameraParameters()); diff --git a/localization/localization_node/src/localization_nodelet.cc b/localization/localization_node/src/localization_nodelet.cc index f1dfcf4495..b606480db4 100644 --- a/localization/localization_node/src/localization_nodelet.cc +++ b/localization/localization_node/src/localization_nodelet.cc @@ -125,11 +125,7 @@ void LocalizationNodelet::Initialize(ros::NodeHandle* nh) { } void LocalizationNodelet::ReadParams(void) { - if (!config_.ReadFiles()) { - ROS_ERROR("Failed to read config files."); - return; - } - if (inst_) inst_->ReadParams(&config_); + if (inst_) inst_->ReadParams(); } bool LocalizationNodelet::EnableService(ff_msgs::SetBool::Request & req, ff_msgs::SetBool::Response & res) { diff --git a/localization/sparse_mapping/include/sparse_mapping/localization_parameters.h b/localization/sparse_mapping/include/sparse_mapping/localization_parameters.h new file mode 100644 index 0000000000..08d9834e73 --- /dev/null +++ b/localization/sparse_mapping/include/sparse_mapping/localization_parameters.h @@ -0,0 +1,41 @@ +/* Copyright (c) 2017, United States Government, as represented by the + * Administrator of the National Aeronautics and Space Administration. + * + * All rights reserved. + * + * The Astrobee platform is licensed under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with the + * License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT + * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the + * License for the specific language governing permissions and limitations + * under the License. + */ + +#ifndef SPARSE_MAPPING_LOCALIZATION_PARAMETERS_H_ +#define SPARSE_MAPPING_LOCALIZATION_PARAMETERS_H_ + +namespace sparse_mapping { +struct LocalizationParameters { + int num_similar; + int ransac_inlier_tolerance; + int num_ransac_iterations; + int early_break_landmarks; + int histogram_equalization; + bool check_essential_matrix; + bool add_similar_images; + bool add_best_previous_image; + bool hamming_distance; + bool goodness_ratio; + bool use_clahe; + int num_extra_localization_db_images; + bool verbose_localization; + bool visualize_localization_matches; +}; +} // namespace sparse_mapping + +#endif // SPARSE_MAPPING_LOCALIZATION_PARAMETERS_H_ diff --git a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h index 08d2e0b89b..48256a0012 100644 --- a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h +++ b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h @@ -23,6 +23,7 @@ #include #include #include +#include #include #include @@ -90,6 +91,12 @@ struct SparseMap { SparseMap(bool bundler_format, std::string const& filename, std::vector const& files); + // Set default loc params using FLAG values + void SetDefaultLocParams(); + + // Set loc params + void SetLocParams(const LocalizationParameters& loc_params) { loc_params_ = loc_params; } + void SetDetectorParams(int min_features, int max_features, int retries, double min_thresh, double default_thresh, double max_thresh); @@ -165,32 +172,6 @@ struct SparseMap { const std::map & GetLandmarkCidToFidMap(int landmark) const {return pid_to_cid_fid_[landmark];} // access and modify parameters - /** - * Set the number of RANSAC iterations. - **/ - void SetRansacIterations(int iterations) {num_ransac_iterations_ = iterations;} - /** - * Return the number of RANSAC iterations. - **/ - int GetRansacIterations(void) const {return num_ransac_iterations_;} - /** - * Set the RANSAC inlier tolerance, the number of pixels an inlier - * feature is allowed to be off by. - **/ - void SetRansacInlierTolerance(int tolerance) {ransac_inlier_tolerance_ = tolerance;} - /** - * Get the RANSAC inlier tolerance, the number of pixels an inlier - * feature is allowed to be off by. - **/ - int GetRansacInlierTolerance(void) const {return ransac_inlier_tolerance_;} - /** - * Set the number of early break landmarks, when to stop in adding landmarks when localizing. - **/ - void SetEarlyBreakLandmarks(int early_break_landmarks) {early_break_landmarks_ = early_break_landmarks;} - void SetHistogramEqualization(int histogram_equalization) {histogram_equalization_ = histogram_equalization;} - int GetHistogramEqualization() {return histogram_equalization_;} - void SetCLAHE(bool use_clahe) {use_clahe_ = use_clahe;} - bool GetCLAHE() {return use_clahe_;} /** * Return the parameters of the camera used to construct the map. **/ @@ -234,12 +215,9 @@ struct SparseMap { // delete feature descriptors with no matching landmark void PruneMap(void); - /** - * Set the number of similar images queried by the VocabDB. - **/ - void SetNumSimilar(int num_similar) {num_similar_ = num_similar;} - std::string GetDetectorName() { return detector_.GetDetectorName(); } + int GetHistogramEqualization() {return loc_params_.histogram_equalization;} + const LocalizationParameters& loc_params() { return loc_params_; } // stored in map file std::vector cid_to_filename_; @@ -256,12 +234,7 @@ struct SparseMap { interest_point::FeatureDetector detector_; camera::CameraParameters camera_params_; mutable sparse_mapping::VocabDB vocab_db_; // TODO(oalexan1): Mutable means someone is doing something wrong. - int num_similar_; - int num_ransac_iterations_; - int ransac_inlier_tolerance_; - int early_break_landmarks_; - int histogram_equalization_; - bool use_clahe_; + LocalizationParameters loc_params_; // e.g, 10th db image is 3rd image in cid_to_filename_ std::map db_to_cid_map_; diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index ecf55393f7..c4cd5536d4 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -72,7 +72,7 @@ DEFINE_bool(localization_check_essential_matrix, true, DEFINE_bool(localization_add_similar_images, true, "If true, for each cid matched to, also attempt to match to any cid with at least 5 of the same features " "as the matched cid."); -DEFINE_bool(localization_add_best_previous_cid, true, +DEFINE_bool(localization_add_best_previous_image, true, "If true, add previous cid with the most matches to list of cids to check for" "matches with."); @@ -82,34 +82,16 @@ SparseMap::SparseMap(const std::vector& filenames, const std::strin const camera::CameraParameters& params) : cid_to_filename_(filenames), detector_(detector), - camera_params_(params), - num_similar_(FLAGS_num_similar), - num_ransac_iterations_(FLAGS_num_ransac_iterations), - ransac_inlier_tolerance_(FLAGS_ransac_inlier_tolerance), - early_break_landmarks_(FLAGS_early_break_landmarks), - histogram_equalization_(FLAGS_histogram_equalization), - use_clahe_(FLAGS_use_clahe) { - if (histogram_equalization_ && use_clahe_) { - clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); - histogram_equalization_ = 3; - } + camera_params_(params) { + SetDefaultLocParams(); cid_to_descriptor_map_.resize(cid_to_filename_.size()); // TODO(bcoltin): only record scale and orientation for opensift? cid_to_keypoint_map_.resize(cid_to_filename_.size()); } SparseMap::SparseMap(const std::string& protobuf_file, bool localization) - : camera_params_(Eigen::Vector2i(-1, -1), Eigen::Vector2d::Constant(-1), Eigen::Vector2d(-1, -1)), - num_similar_(FLAGS_num_similar), - num_ransac_iterations_(FLAGS_num_ransac_iterations), - ransac_inlier_tolerance_(FLAGS_ransac_inlier_tolerance), - early_break_landmarks_(FLAGS_early_break_landmarks), - histogram_equalization_(FLAGS_histogram_equalization), - use_clahe_(FLAGS_use_clahe) { - if (histogram_equalization_ && use_clahe_) { - clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); - histogram_equalization_ = 3; - } + : camera_params_(Eigen::Vector2i(-1, -1), Eigen::Vector2d::Constant(-1), Eigen::Vector2d(-1, -1)) { + SetDefaultLocParams(); // The above camera params used bad values because we are expected to reload // later. Load(protobuf_file, localization); @@ -119,17 +101,8 @@ SparseMap::SparseMap(const std::string& protobuf_file, bool localization) SparseMap::SparseMap(const std::vector& cid_to_cam_t, const std::vector& filenames, const std::string& detector, const camera::CameraParameters& params) : detector_(detector), - camera_params_(params), - num_similar_(FLAGS_num_similar), - num_ransac_iterations_(FLAGS_num_ransac_iterations), - ransac_inlier_tolerance_(FLAGS_ransac_inlier_tolerance), - early_break_landmarks_(FLAGS_early_break_landmarks), - histogram_equalization_(FLAGS_histogram_equalization), - use_clahe_(FLAGS_use_clahe) { - if (histogram_equalization_ && use_clahe_) { - clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); - histogram_equalization_ = 3; - } + camera_params_(params) { + SetDefaultLocParams(); if (filenames.size() != cid_to_cam_t.size()) LOG(FATAL) << "Expecting as many images as cameras"; @@ -152,17 +125,8 @@ SparseMap::SparseMap(const std::vector& cid_to_cam_t, const std // bundler, nvm or theia maps. SparseMap::SparseMap(bool bundler_format, std::string const& filename, std::vector const& all_image_files) : camera_params_(Eigen::Vector2i(640, 480), Eigen::Vector2d::Constant(300), - Eigen::Vector2d(320, 240)), // these are placeholders and must be changed - num_similar_(FLAGS_num_similar), - num_ransac_iterations_(FLAGS_num_ransac_iterations), - ransac_inlier_tolerance_(FLAGS_ransac_inlier_tolerance), - early_break_landmarks_(FLAGS_early_break_landmarks), - histogram_equalization_(FLAGS_histogram_equalization), - use_clahe_(FLAGS_use_clahe) { - if (histogram_equalization_ && use_clahe_) { - clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); - histogram_equalization_ = 3; - } + Eigen::Vector2d(320, 240)) /* these are placeholders and must be changed */ { + SetDefaultLocParams(); std::string ext = ff_common::file_extension(filename); boost::to_lower(ext); @@ -266,6 +230,25 @@ SparseMap::SparseMap(bool bundler_format, std::string const& filename, std::vect InitializeCidFidToPid(); } +void SparseMap::SetDefaultLocParams() { + loc_params_.num_similar = FLAGS_num_similar; + loc_params_.num_ransac_iterations = FLAGS_num_ransac_iterations; + loc_params_.ransac_inlier_tolerance = FLAGS_ransac_inlier_tolerance; + loc_params_.early_break_landmarks = FLAGS_early_break_landmarks; + loc_params_.histogram_equalization = FLAGS_histogram_equalization; + loc_params_.use_clahe = FLAGS_use_clahe; + loc_params_.check_essential_matrix = FLAGS_localization_check_essential_matrix; + loc_params_.add_similar_images = FLAGS_localization_add_similar_images; + loc_params_.add_best_previous_image = FLAGS_localization_add_best_previous_image; + loc_params_.num_extra_localization_db_images = FLAGS_num_extra_localization_db_images; + loc_params_.verbose_localization = FLAGS_verbose_localization; + loc_params_.visualize_localization_matches = FLAGS_visualize_localization_matches; + if (loc_params_.histogram_equalization && loc_params_.use_clahe) { + clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); + loc_params_.histogram_equalization = 3; + } +} + // Detect features in given images void SparseMap::DetectFeatures() { ff_common::ThreadPool pool; @@ -340,7 +323,7 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { cid_to_filename_.resize(num_frames); cid_to_descriptor_map_.resize(num_frames); - if (!localization || FLAGS_visualize_localization_matches) { + if (!localization || loc_params_.visualize_localization_matches) { cid_to_keypoint_map_.resize(num_frames); cid_to_cam_t_global_.resize(num_frames); } @@ -357,7 +340,7 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { cid_to_filename_[cid] = ""; - if (!localization || FLAGS_visualize_localization_matches) { + if (!localization || loc_params_.visualize_localization_matches) { // load keypoints cid_to_keypoint_map_[cid].resize(Eigen::NoChange_t(), frame.feature_size()); } @@ -378,7 +361,7 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { sparse_mapping_protobuf::Feature feature = frame.feature(fid); - if (!localization || FLAGS_visualize_localization_matches) { + if (!localization || loc_params_.visualize_localization_matches) { // Copy the features cid_to_keypoint_map_[cid].col(fid) << feature.x(), feature.y(); } @@ -455,18 +438,18 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { if (map.has_vocab_db()) vocab_db_.LoadProtobuf(input, map.vocab_db()); - histogram_equalization_ = map.histogram_equalization(); + loc_params_.histogram_equalization = map.histogram_equalization(); - assert(histogram_equalization_ == 0 || histogram_equalization_ == 1 || histogram_equalization_ == 2 || - histogram_equalization_ == 3); + assert(loc_params_.histogram_equalization == 0 || loc_params_.histogram_equalization == 1 || + loc_params_.histogram_equalization == 2 || loc_params_.histogram_equalization == 3); - use_clahe_ = histogram_equalization_ == 3 ? true : false; - if (use_clahe_) clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); + loc_params_.use_clahe = loc_params_.histogram_equalization == 3 ? true : false; + if (loc_params_.use_clahe) clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); // For backward compatibility with old maps, allow a map to have its // histogram_equalization flag unspecified, but it is best to avoid // that situation, and rebuild the map if necessary. - if (histogram_equalization_ == 2) + if (loc_params_.histogram_equalization == 2) std::cout << "Warning: Unknown value of histogram_equalization! " << "It is strongly suggested to rebuild this map to avoid " << "poor quality results." << std::endl; @@ -487,7 +470,7 @@ void SparseMap::Save(const std::string & protobuf_file) const { // For backward compatibility with old maps, allow a map to have its // histogram_equalization flag unspecified, but it is best to avoid // that situation, and rebuild the map if necessary. - if (histogram_equalization_ == 2) + if (loc_params_.histogram_equalization == 2) std::cout << "Warning: Unknown value of histogram_equalization! " << "It is strongly suggested to rebuild this map to avoid " << "poor quality results." << std::endl; @@ -523,7 +506,7 @@ void SparseMap::Save(const std::string & protobuf_file) const { if (vocab_db_.binary_db != NULL) map.set_vocab_db(sparse_mapping_protobuf::Map::BINARYDB); - map.set_histogram_equalization(histogram_equalization_); + map.set_histogram_equalization(loc_params_.histogram_equalization); LOG(INFO) << "Writing: " << protobuf_file; int output_fd = open(protobuf_file.c_str(), O_WRONLY | O_CREAT | O_TRUNC, S_IRUSR | S_IWUSR | S_IRGRP | S_IROTH); @@ -647,8 +630,8 @@ void SparseMap::DetectFeatures(const cv::Mat& image, // If using histogram equalization, need an extra image to store it cv::Mat * image_ptr = const_cast(&image); cv::Mat hist_image; - if (histogram_equalization_) { - if (use_clahe_) { + if (loc_params_.histogram_equalization) { + if (loc_params_.use_clahe) { clahe_->apply(image, hist_image); } else { cv::equalizeHist(image, hist_image); @@ -658,7 +641,7 @@ void SparseMap::DetectFeatures(const cv::Mat& image, #if 0 // This is useful for debugging - std::cout << "Histogram equalization is " << histogram_equalization_ << std::endl; + std::cout << "Histogram equalization is " << loc_params_.histogram_equalization << std::endl; static int count = 10000; count++; std::ostringstream oss; @@ -688,7 +671,7 @@ void SparseMap::DetectFeatures(const cv::Mat& image, } mutex_detector_.unlock(); - if (FLAGS_verbose_localization) + if (loc_params_.verbose_localization) std::cout << "Features detected " << storage.size() << std::endl; keypoints->resize(2, storage.size()); @@ -713,7 +696,7 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const // Notice that we request more similar // images than what we need. We'll prune // them below. - num_similar_ + FLAGS_num_extra_localization_db_images, + loc_params_.num_similar + loc_params_.num_extra_localization_db_images, test_descriptors, &indices); else @@ -726,7 +709,7 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const indices.push_back(cid); } - if (FLAGS_localization_add_best_previous_cid && best_previous_cid_) { + if (loc_params_.add_best_previous_image && best_previous_cid_) { bool add_cid = true; for (const auto cid : indices) { if (cid == *best_previous_cid_) { @@ -753,7 +736,7 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const std::vector similarity_rank; std::vector> all_matches; int total = 0; - if (FLAGS_verbose_localization) { + if (loc_params_.verbose_localization) { for (size_t i = 0; i < indices.size(); i++) { std::cout << "Potential matching cid: " << indices[i] << std::endl; } @@ -761,7 +744,7 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const // TODO(oalexan1): Use multiple threads here? for (size_t i = 0; i < indices.size(); i++) { int cid = indices[i]; - if (FLAGS_verbose_localization) std::cout << "Checking index: " << i << ", cid: " << cid << std::endl; + if (loc_params_.verbose_localization) std::cout << "Checking index: " << i << ", cid: " << cid << std::endl; similarity_rank.emplace_back(0); all_matches.emplace_back(std::vector()); interest_point::FindMatches(test_descriptors, @@ -769,7 +752,7 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const &all_matches[i]); - if (FLAGS_visualize_localization_matches && !image.empty()) { + if (loc_params_.visualize_localization_matches && !image.empty()) { const auto map_filename = cid_to_filename_[cid]; std::cout << "CID: " << cid << ", filename: " << map_filename << std::endl; const auto map_image = cv::imread(map_filename, cv::IMREAD_GRAYSCALE); @@ -782,8 +765,8 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const if (all_matches[i].size() < 5) continue; - if (FLAGS_localization_check_essential_matrix) { - if (FLAGS_verbose_localization) + if (loc_params_.check_essential_matrix) { + if (loc_params_.verbose_localization) std::cout << "Matches before essential filtering: " << all_matches[i].size() << std::endl; std::vector inlier_matches; std::vector vec_inliers; @@ -792,14 +775,14 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const FindEssentialAndInliers(test_keypoints, cid_to_keypoint_map_[cid], all_matches[i], camera_params_, &inlier_matches, &vec_inliers, &essential_matrix); all_matches[i] = inlier_matches; - if (FLAGS_verbose_localization) + if (loc_params_.verbose_localization) std::cout << "Matches after essential filtering: " << all_matches[i].size() << std::endl; } if (all_matches[i].size() < 5) continue; - if (FLAGS_localization_add_similar_images) { - if (FLAGS_verbose_localization) + if (loc_params_.add_similar_images) { + if (loc_params_.verbose_localization) std::cout << "Num indices before adding similar images: " << indices.size() << std::endl; // Add cids with more than 5 of the same features as the current cid to the list of cids to match to. int index = i + 1; @@ -821,7 +804,7 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const ++index; } } - if (FLAGS_verbose_localization) + if (loc_params_.verbose_localization) std::cout << "Num indices after adding similar images: " << indices.size() << std::endl; } @@ -830,25 +813,25 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const continue; similarity_rank[i]++; } - if (FLAGS_verbose_localization) + if (loc_params_.verbose_localization) std::cout << "Overall matches and validated matches to: " << cid_to_filename_[cid] << ": " << all_matches[i].size() << " " << similarity_rank[i] << "\n"; total += similarity_rank[i]; - if (total >= early_break_landmarks_) + if (total >= loc_params_.early_break_landmarks) break; } // Check if enough matches found for estimating pose if (total < 5) { - if (FLAGS_verbose_localization) + if (loc_params_.verbose_localization) std::cout << "Too few matches: " << total << std::endl; return false; } // Update best previous cid if there were enough matches in total - if (FLAGS_localization_add_best_previous_cid) { + if (loc_params_.add_best_previous_image) { // Make sure to only add best previous cid if it has at least 5 matches int most_matches = 5; for (int i = 0; i < all_matches.size(); ++i) { @@ -862,9 +845,9 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const std::vector observations; std::vector landmarks; std::vector highly_ranked = ff_common::rv_order(similarity_rank); - int end = std::min(static_cast(highly_ranked.size()), num_similar_); + int end = std::min(static_cast(highly_ranked.size()), loc_params_.num_similar); std::set seen_landmarks; - if (FLAGS_verbose_localization) + if (loc_params_.verbose_localization) std::cout << "Similar images: "; for (int i = 0; i < end; i++) { int cid = indices[highly_ranked[i]]; @@ -883,16 +866,16 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const seen_landmarks.insert(landmark_id); num_matches++; } - if (FLAGS_verbose_localization && num_matches > 0) + if (loc_params_.verbose_localization && num_matches > 0) std::cout << " " << cid_to_filename_[cid]; } - if (FLAGS_verbose_localization) std::cout << std::endl; + if (loc_params_.verbose_localization) std::cout << std::endl; int ret = RansacEstimateCamera(landmarks, observations, - num_ransac_iterations_, - ransac_inlier_tolerance_, pose, + loc_params_.num_ransac_iterations, + loc_params_.ransac_inlier_tolerance, pose, inlier_landmarks, inlier_observations, - FLAGS_verbose_localization); + loc_params_.verbose_localization); return (ret == 0); } diff --git a/localization/sparse_mapping/src/tensor.cc b/localization/sparse_mapping/src/tensor.cc index c0c2a402af..bf003a1839 100644 --- a/localization/sparse_mapping/src/tensor.cc +++ b/localization/sparse_mapping/src/tensor.cc @@ -222,7 +222,7 @@ void MatchFeatures(const std::string & essential_file, / static_cast (s->cid_to_keypoint_map_.size() - 1)); std::vector indices, queried_indices; sparse_mapping::QueryDB(s->detector_.GetDetectorName(), - &s->vocab_db_, s->num_similar_, + &s->vocab_db_, s->loc_params().num_similar, s->cid_to_descriptor_map_[cid], &queried_indices); diff --git a/tools/localization_analysis/src/live_measurement_simulator.cc b/tools/localization_analysis/src/live_measurement_simulator.cc index e52ab2ad3f..0da43bf0b8 100644 --- a/tools/localization_analysis/src/live_measurement_simulator.cc +++ b/tools/localization_analysis/src/live_measurement_simulator.cc @@ -49,7 +49,7 @@ LiveMeasurementSimulator::LiveMeasurementSimulator(const LiveMeasurementSimulato exit(0); } - map_feature_matcher_.ReadParams(&config); + map_feature_matcher_.ReadParams(); optical_flow_tracker_.ReadParams(&config); std::vector topics; topics.push_back(std::string("/") + TOPIC_HARDWARE_IMU); From a723095222da7a5f4114b6bb610250df234173fe Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Tue, 25 Jun 2024 06:38:22 -0700 Subject: [PATCH 32/61] fixed hamming and goodness types --- .../include/sparse_mapping/localization_parameters.h | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/localization/sparse_mapping/include/sparse_mapping/localization_parameters.h b/localization/sparse_mapping/include/sparse_mapping/localization_parameters.h index 08d9834e73..f16ea8db33 100644 --- a/localization/sparse_mapping/include/sparse_mapping/localization_parameters.h +++ b/localization/sparse_mapping/include/sparse_mapping/localization_parameters.h @@ -29,8 +29,8 @@ struct LocalizationParameters { bool check_essential_matrix; bool add_similar_images; bool add_best_previous_image; - bool hamming_distance; - bool goodness_ratio; + int hamming_distance; + double goodness_ratio; bool use_clahe; int num_extra_localization_db_images; bool verbose_localization; From 52905d7de90bf593a77d45eed369d6a773c93df8 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Tue, 25 Jun 2024 07:00:39 -0700 Subject: [PATCH 33/61] fixed reading loc node params --- astrobee/config/localization.config | 2 +- .../include/localization_node/localization.h | 2 +- localization/localization_node/src/localization.cc | 10 +--------- .../localization_node/src/localization_nodelet.cc | 6 ++++-- .../src/live_measurement_simulator.cc | 2 +- tools/localization_analysis/src/map_matcher.cc | 3 +++ 6 files changed, 11 insertions(+), 14 deletions(-) diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index 8332230f4b..4fa7b79010 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -48,7 +48,7 @@ teblid_ransac_inlier_tolerance = 3 teblid_num_ransac_iterations = 1000 teblid_early_break_landmarks = 100 teblid_histogram_equalization = 3 -teblid_check_essential_matrix = false +teblid_check_essential_matrix = true teblid_add_similar_images = true teblid_add_best_previous_image = true teblid_hamming_distance = 85 diff --git a/localization/localization_node/include/localization_node/localization.h b/localization/localization_node/include/localization_node/localization.h index 48c6f73df3..81147d45d8 100644 --- a/localization/localization_node/include/localization_node/localization.h +++ b/localization/localization_node/include/localization_node/localization.h @@ -31,7 +31,7 @@ namespace localization_node { class Localizer { public: explicit Localizer(sparse_mapping::SparseMap* map); - void ReadParams(); + void ReadParams(config_reader::ConfigReader& config); bool Localize(cv_bridge::CvImageConstPtr image_ptr, ff_msgs::VisualLandmarks* vl, Eigen::Matrix2Xd* image_keypoints = NULL); private: diff --git a/localization/localization_node/src/localization.cc b/localization/localization_node/src/localization.cc index 0e0654a652..d8ee7adec0 100644 --- a/localization/localization_node/src/localization.cc +++ b/localization/localization_node/src/localization.cc @@ -29,15 +29,7 @@ namespace localization_node { Localizer::Localizer(sparse_mapping::SparseMap* map): map_(map) {} -void Localizer::ReadParams() { - config_reader::ConfigReader config; - config.AddFile("cameras.config"); - config.AddFile("localization.config"); - if (!config.ReadFiles()) { - ROS_ERROR("Failed to read config files."); - return; - } - +void Localizer::ReadParams(config_reader::ConfigReader& config) { camera::CameraParameters cam_params(&config, "nav_cam"); std::string prefix; const auto detector_name = map_->GetDetectorName(); diff --git a/localization/localization_node/src/localization_nodelet.cc b/localization/localization_node/src/localization_nodelet.cc index b606480db4..bb1a9f9f25 100644 --- a/localization/localization_node/src/localization_nodelet.cc +++ b/localization/localization_node/src/localization_nodelet.cc @@ -72,7 +72,9 @@ void LocalizationNodelet::Initialize(ros::NodeHandle* nh) { config_.AddFile("cameras.config"); config_.AddFile("localization.config"); - config_.ReadFiles(); + if (!config_.ReadFiles()) { + ROS_FATAL("Failed to read config files."); + } // Resolve the full path to the AR tag file specified for the current world std::string map_file; @@ -125,7 +127,7 @@ void LocalizationNodelet::Initialize(ros::NodeHandle* nh) { } void LocalizationNodelet::ReadParams(void) { - if (inst_) inst_->ReadParams(); + if (inst_) inst_->ReadParams(config_); } bool LocalizationNodelet::EnableService(ff_msgs::SetBool::Request & req, ff_msgs::SetBool::Response & res) { diff --git a/tools/localization_analysis/src/live_measurement_simulator.cc b/tools/localization_analysis/src/live_measurement_simulator.cc index 0da43bf0b8..7377d53c65 100644 --- a/tools/localization_analysis/src/live_measurement_simulator.cc +++ b/tools/localization_analysis/src/live_measurement_simulator.cc @@ -49,7 +49,7 @@ LiveMeasurementSimulator::LiveMeasurementSimulator(const LiveMeasurementSimulato exit(0); } - map_feature_matcher_.ReadParams(); + map_feature_matcher_.ReadParams(config); optical_flow_tracker_.ReadParams(&config); std::vector topics; topics.push_back(std::string("/") + TOPIC_HARDWARE_IMU); diff --git a/tools/localization_analysis/src/map_matcher.cc b/tools/localization_analysis/src/map_matcher.cc index fbf9265288..1b0d76f50f 100644 --- a/tools/localization_analysis/src/map_matcher.cc +++ b/tools/localization_analysis/src/map_matcher.cc @@ -42,10 +42,13 @@ MapMatcher::MapMatcher(const std::string& input_bag_name, const std::string& map image_count_(0) { config_reader::ConfigReader config; config.AddFile("geometry.config"); + config.AddFile("camera.config"); + config.AddFile("localization.config"); lc::LoadGraphLocalizerConfig(config); if (!config.ReadFiles()) { LogFatal("Failed to read config files."); } + map_feature_matcher_.ReadParams(config); body_T_nav_cam_ = lc::LoadTransform(config, "nav_cam_transform"); if (!save_noloc_imgs.empty()) { nonloc_bag_.open(save_noloc_imgs, rosbag::bagmode::Write); From f0147255af8395fca0ec3f06632177dd9e4872ce Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Tue, 25 Jun 2024 07:03:01 -0700 Subject: [PATCH 34/61] fixed camera config path --- tools/localization_analysis/src/map_matcher.cc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tools/localization_analysis/src/map_matcher.cc b/tools/localization_analysis/src/map_matcher.cc index 1b0d76f50f..a5949b6c08 100644 --- a/tools/localization_analysis/src/map_matcher.cc +++ b/tools/localization_analysis/src/map_matcher.cc @@ -42,7 +42,7 @@ MapMatcher::MapMatcher(const std::string& input_bag_name, const std::string& map image_count_(0) { config_reader::ConfigReader config; config.AddFile("geometry.config"); - config.AddFile("camera.config"); + config.AddFile("cameras.config"); config.AddFile("localization.config"); lc::LoadGraphLocalizerConfig(config); if (!config.ReadFiles()) { From ea0fc5e963ffca5998aea42c13c8a00b7adb15c7 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Tue, 25 Jun 2024 07:16:26 -0700 Subject: [PATCH 35/61] added hamming and goodness to find matches call, added loading clahe param --- localization/localization_node/src/localization.cc | 1 + localization/sparse_mapping/src/sparse_map.cc | 6 ++---- 2 files changed, 3 insertions(+), 4 deletions(-) diff --git a/localization/localization_node/src/localization.cc b/localization/localization_node/src/localization.cc index d8ee7adec0..6dd410681f 100644 --- a/localization/localization_node/src/localization.cc +++ b/localization/localization_node/src/localization.cc @@ -53,6 +53,7 @@ void Localizer::ReadParams(config_reader::ConfigReader& config) { LOAD_PARAM(loc_params.add_best_previous_image, config, prefix); LOAD_PARAM(loc_params.hamming_distance, config, prefix); LOAD_PARAM(loc_params.goodness_ratio, config, prefix); + LOAD_PARAM(loc_params.use_clahe, config, prefix); LOAD_PARAM(loc_params.num_extra_localization_db_images, config, prefix); LOAD_PARAM(loc_params.verbose_localization, config, ""); LOAD_PARAM(loc_params.visualize_localization_matches, config, ""); diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index c4cd5536d4..671bd979e6 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -747,10 +747,8 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const if (loc_params_.verbose_localization) std::cout << "Checking index: " << i << ", cid: " << cid << std::endl; similarity_rank.emplace_back(0); all_matches.emplace_back(std::vector()); - interest_point::FindMatches(test_descriptors, - cid_to_descriptor_map_[cid], - &all_matches[i]); - + interest_point::FindMatches(test_descriptors, cid_to_descriptor_map_[cid], &all_matches[i], + loc_params_.hamming_distance, loc_params_.goodness_ratio); if (loc_params_.visualize_localization_matches && !image.empty()) { const auto map_filename = cid_to_filename_[cid]; From 69cb35e9aa92bdf0ba891c0d9d90bc7d8b5eb8c7 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Tue, 25 Jun 2024 07:24:02 -0700 Subject: [PATCH 36/61] added clahe param check --- localization/localization_node/src/localization.cc | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/localization/localization_node/src/localization.cc b/localization/localization_node/src/localization.cc index 6dd410681f..84bab93092 100644 --- a/localization/localization_node/src/localization.cc +++ b/localization/localization_node/src/localization.cc @@ -72,6 +72,11 @@ void Localizer::ReadParams(config_reader::ConfigReader& config) { // to compare with what is there already. sparse_mapping::HistogramEqualizationCheck(map_->GetHistogramEqualization(), loc_params.histogram_equalization); + // Check consistency between clahe params + if (loc_params.use_clahe && (loc_params.histgram_equalization != 3 || map_->GetHistogramEqualization() != 3) { + ROS_FATAL("Invalid clahe and histogram equalization settings."); + } + map_->SetCameraParameters(cam_params); map_->SetLocParams(loc_params); map_->SetDetectorParams(min_features, max_features, detection_retries, From a1545938107cbeedfb0b2a1b37878eb13187f7a4 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Tue, 25 Jun 2024 07:31:40 -0700 Subject: [PATCH 37/61] fix clahe check --- localization/localization_node/src/localization.cc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/localization/localization_node/src/localization.cc b/localization/localization_node/src/localization.cc index 84bab93092..e77c6fa103 100644 --- a/localization/localization_node/src/localization.cc +++ b/localization/localization_node/src/localization.cc @@ -73,7 +73,7 @@ void Localizer::ReadParams(config_reader::ConfigReader& config) { sparse_mapping::HistogramEqualizationCheck(map_->GetHistogramEqualization(), loc_params.histogram_equalization); // Check consistency between clahe params - if (loc_params.use_clahe && (loc_params.histgram_equalization != 3 || map_->GetHistogramEqualization() != 3) { + if (loc_params.use_clahe && (loc_params.histogram_equalization != 3 || map_->GetHistogramEqualization() != 3)) { ROS_FATAL("Invalid clahe and histogram equalization settings."); } From d42aa079155fd172e2bbb16adf83ef95d1666a09 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Tue, 25 Jun 2024 07:38:08 -0700 Subject: [PATCH 38/61] fixed clahe param in loc config --- astrobee/config/localization.config | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index 4fa7b79010..0d74173c24 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -32,7 +32,7 @@ brisk_add_similar_images = false brisk_add_best_previous_image = false brisk_hamming_distance = 90 brisk_goodness_ratio = 0.8 -brisk_use_clahe_ = false +brisk_use_clahe = false brisk_num_extra_localization_db_images = 0 -- Detection Params brisk_min_threshold = 20.0 @@ -53,7 +53,7 @@ teblid_add_similar_images = true teblid_add_best_previous_image = true teblid_hamming_distance = 85 teblid_goodness_ratio = 0.8 -teblid_use_clahe_ = false +teblid_use_clahe = false teblid_num_extra_localization_db_images = 0 -- Detection Params From ec8533a884dda93c6f8631deb2cca6c8c075aebb Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Tue, 25 Jun 2024 07:45:47 -0700 Subject: [PATCH 39/61] fixed teblid use clahe value --- astrobee/config/localization.config | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index 0d74173c24..712c85ec6d 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -53,7 +53,7 @@ teblid_add_similar_images = true teblid_add_best_previous_image = true teblid_hamming_distance = 85 teblid_goodness_ratio = 0.8 -teblid_use_clahe = false +teblid_use_clahe = true teblid_num_extra_localization_db_images = 0 -- Detection Params From 1a796d87debe6a83d8d7b9ecb6f301021a5baf2e Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Tue, 25 Jun 2024 07:53:59 -0700 Subject: [PATCH 40/61] added loading keypoint map --- localization/sparse_mapping/src/sparse_map.cc | 16 +++++----------- 1 file changed, 5 insertions(+), 11 deletions(-) diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index 671bd979e6..b184d33581 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -85,7 +85,6 @@ SparseMap::SparseMap(const std::vector& filenames, const std::strin camera_params_(params) { SetDefaultLocParams(); cid_to_descriptor_map_.resize(cid_to_filename_.size()); - // TODO(bcoltin): only record scale and orientation for opensift? cid_to_keypoint_map_.resize(cid_to_filename_.size()); } @@ -323,8 +322,8 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { cid_to_filename_.resize(num_frames); cid_to_descriptor_map_.resize(num_frames); - if (!localization || loc_params_.visualize_localization_matches) { - cid_to_keypoint_map_.resize(num_frames); + cid_to_keypoint_map_.resize(num_frames); + if (!localization) { cid_to_cam_t_global_.resize(num_frames); } @@ -340,10 +339,8 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { cid_to_filename_[cid] = ""; - if (!localization || loc_params_.visualize_localization_matches) { - // load keypoints - cid_to_keypoint_map_[cid].resize(Eigen::NoChange_t(), frame.feature_size()); - } + // load keypoints + cid_to_keypoint_map_[cid].resize(Eigen::NoChange_t(), frame.feature_size()); // Poke the first frame's first descriptor to see how long the // descriptor is. @@ -361,10 +358,7 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { sparse_mapping_protobuf::Feature feature = frame.feature(fid); - if (!localization || loc_params_.visualize_localization_matches) { - // Copy the features - cid_to_keypoint_map_[cid].col(fid) << feature.x(), feature.y(); - } + cid_to_keypoint_map_[cid].col(fid) << feature.x(), feature.y(); // Copy the descriptors memcpy(cid_to_descriptor_map_[cid].ptr(fid), // Destination From a84ac11a29083c3a6a8dfc50051c8779409cd87d Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Tue, 25 Jun 2024 12:56:42 -0700 Subject: [PATCH 41/61] Avoid multithread histogram equalization --- localization/sparse_mapping/src/sparse_map.cc | 1 + 1 file changed, 1 insertion(+) diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index b184d33581..080c22fc98 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -625,6 +625,7 @@ void SparseMap::DetectFeatures(const cv::Mat& image, cv::Mat * image_ptr = const_cast(&image); cv::Mat hist_image; if (loc_params_.histogram_equalization) { + cv::setNumThreads(0); if (loc_params_.use_clahe) { clahe_->apply(image, hist_image); } else { From 47004ca765f372ca57ec4546fd6860f58c2da580 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Tue, 25 Jun 2024 13:53:16 -0700 Subject: [PATCH 42/61] added support for teblid512 and teblid256 --- astrobee/config/localization.config | 60 +++++++++++++------ localization/interest_point/src/matching.cc | 18 ++++-- .../localization_node/src/localization.cc | 7 ++- .../sparse_mapping/tools/build_map.cc | 8 +-- 4 files changed, 62 insertions(+), 31 deletions(-) diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index 712c85ec6d..6b9216ddca 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -42,24 +42,46 @@ brisk_min_features = 200 brisk_max_features = 800 brisk_detection_retries = 1 --- TEBLID -teblid_num_similar = 20 -teblid_ransac_inlier_tolerance = 3 -teblid_num_ransac_iterations = 1000 -teblid_early_break_landmarks = 100 -teblid_histogram_equalization = 3 -teblid_check_essential_matrix = true -teblid_add_similar_images = true -teblid_add_best_previous_image = true -teblid_hamming_distance = 85 -teblid_goodness_ratio = 0.8 -teblid_use_clahe = true -teblid_num_extra_localization_db_images = 0 +-- TEBLID512 +teblid512_num_similar = 20 +teblid512_ransac_inlier_tolerance = 3 +teblid512_num_ransac_iterations = 1000 +teblid512_early_break_landmarks = 100 +teblid512_histogram_equalization = 3 +teblid512_check_essential_matrix = true +teblid512_add_similar_images = true +teblid512_add_best_previous_image = true +teblid512_hamming_distance = 85 +teblid512_goodness_ratio = 0.8 +teblid512_use_clahe = true +teblid512_num_extra_localization_db_images = 0 -- Detection Params -teblid_min_threshold = 10.0 -teblid_default_threshold = 20.0 -teblid_max_threshold = 110.0 -teblid_min_features = 1000 -teblid_max_features = 3000 -teblid_detection_retries = 5 +teblid512_min_threshold = 10.0 +teblid512_default_threshold = 20.0 +teblid512_max_threshold = 110.0 +teblid512_min_features = 1000 +teblid512_max_features = 3000 +teblid512_detection_retries = 5 + +-- TEBLID256 +teblid256_num_similar = 20 +teblid256_ransac_inlier_tolerance = 3 +teblid256_num_ransac_iterations = 1000 +teblid256_early_break_landmarks = 100 +teblid256_histogram_equalization = 3 +teblid256_check_essential_matrix = true +teblid256_add_similar_images = true +teblid256_add_best_previous_image = true +teblid256_hamming_distance = 85 +teblid256_goodness_ratio = 0.8 +teblid256_use_clahe = true +teblid256_num_extra_localization_db_images = 0 + +-- Detection Params +teblid256_min_threshold = 10.0 +teblid256_default_threshold = 20.0 +teblid256_max_threshold = 110.0 +teblid256_min_features = 1000 +teblid256_max_features = 3000 +teblid256_detection_retries = 5 diff --git a/localization/interest_point/src/matching.cc b/localization/interest_point/src/matching.cc index 0f2a343421..951c6ef7f3 100644 --- a/localization/interest_point/src/matching.cc +++ b/localization/interest_point/src/matching.cc @@ -179,14 +179,18 @@ namespace interest_point { class TeblidDynamicDetector : public DynamicDetector { public: TeblidDynamicDetector(int min_features, int max_features, int max_retries, - double min_thresh, double default_thresh, double max_thresh) + double min_thresh, double default_thresh, double max_thresh, bool use_512 = true) : DynamicDetector(min_features, max_features, max_retries, min_thresh, default_thresh, max_thresh) { + if (use_512) { + teblid_ = upm::BAD::create(5.0, upm::BAD::SIZE_512_BITS); + } else { + teblid_ = upm::BAD::create(5.0, upm::BAD::SIZE_256_BITS); + } Reset(); } void Reset(void) { - teblid_ = upm::BAD::create(5.0, upm::BAD::SIZE_512_BITS); brisk_ = interest_point::BRISK::create(dynamic_thresh_, FLAGS_orgbrisk_octaves, FLAGS_orgbrisk_pattern_scale); } @@ -266,7 +270,8 @@ namespace interest_point { min_thresh = FLAGS_min_surf_threshold; default_thresh = FLAGS_default_surf_threshold; max_thresh = FLAGS_max_surf_threshold; - } else if (detector_name == "ORGBRISK" || detector_name == "TEBLID") { + } else if (detector_name == "ORGBRISK" || detector_name == "TEBLID512" || + detector_name == "TEBLID256") { min_features = FLAGS_min_brisk_features; max_features = FLAGS_max_brisk_features; retries = FLAGS_detection_retries; @@ -285,9 +290,12 @@ namespace interest_point { else if (detector_name == "SURF") detector_ = new SurfDynamicDetector(min_features, max_features, retries, min_thresh, default_thresh, max_thresh); - else if (detector_name == "TEBLID") + else if (detector_name == "TEBLID512") detector_ = new TeblidDynamicDetector(min_features, max_features, retries, - min_thresh, default_thresh, max_thresh); + min_thresh, default_thresh, max_thresh, true); + else if (detector_name == "TEBLID256") + detector_ = new TeblidDynamicDetector(min_features, max_features, retries, + min_thresh, default_thresh, max_thresh, false); else LOG(FATAL) << "Unimplemented feature detector: " << detector_name; diff --git a/localization/localization_node/src/localization.cc b/localization/localization_node/src/localization.cc index e77c6fa103..948cfab96c 100644 --- a/localization/localization_node/src/localization.cc +++ b/localization/localization_node/src/localization.cc @@ -35,8 +35,10 @@ void Localizer::ReadParams(config_reader::ConfigReader& config) { const auto detector_name = map_->GetDetectorName(); if (detector_name == "ORGBRISK") { prefix = "brisk_"; - } else if (detector_name == "TEBLID") { - prefix = "teblid_"; + } else if (detector_name == "TEBLID512") { + prefix = "teblid512_"; + } else if (detector_name == "TEBLID256") { + prefix = "teblid256_"; } else { ROS_FATAL_STREAM("Invalid detector: " << detector_name); } @@ -98,7 +100,6 @@ bool Localizer::Localize(cv_bridge::CvImageConstPtr image_ptr, ff_msgs::VisualLa vl->header.frame_id = "world"; map_->DetectFeatures(image_ptr->image, multithreaded, &image_descriptors, image_keypoints); - camera::CameraModel camera(Eigen::Vector3d(), Eigen::Matrix3d::Identity(), map_->GetCameraParameters()); diff --git a/localization/sparse_mapping/tools/build_map.cc b/localization/sparse_mapping/tools/build_map.cc index 69663811a1..bfe1fe002a 100644 --- a/localization/sparse_mapping/tools/build_map.cc +++ b/localization/sparse_mapping/tools/build_map.cc @@ -51,9 +51,9 @@ DEFINE_bool(save_individual_maps, false, // output map parameters DEFINE_string(detector, "SURF", - "Feature detector to use. Options are: SURF, ORGBRISK."); -DEFINE_string(rebuild_detector, "ORGBRISK", - "Feature detector to use. Options are: SURF, ORGBRISK."); + "Feature detector to use. Options are: SURF, ORGBRISK, TEBLID512, TEBLID256."); +DEFINE_string(rebuild_detector, "TEBLID512", + "Feature detector to use. Options are: SURF, ORGBRISK, TEBLID512, TEBLID256."); // control options DEFINE_bool(feature_detection, false, @@ -98,7 +98,7 @@ DEFINE_bool(fix_cameras, false, "Keep the cameras fixed during bundle adjustment."); DEFINE_bool(rebuild_refloat_cameras, false, "Optimize the cameras as well as part of rebuilding. Usually that is " - "avoided when rebuilding with ORGBRISK, but could be useful with SURF."); + "avoided when rebuilding with binary features, but could be useful with SURF."); DEFINE_int32(db_restarts, 1, "Number of restarts when building the tree."); DEFINE_int32(db_depth, 0, "Depth of the tree to build. Default: 4"); From c973991299f6abc91d83071c8afce4d7a919ea1f Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Wed, 26 Jun 2024 13:30:50 -0700 Subject: [PATCH 43/61] added separete fcn to load keypoints --- .../include/sparse_mapping/sparse_map.h | 8 ++- localization/sparse_mapping/src/sparse_map.cc | 55 +++++++++++++++++-- 2 files changed, 57 insertions(+), 6 deletions(-) diff --git a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h index 48256a0012..cefa4b089f 100644 --- a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h +++ b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h @@ -95,7 +95,7 @@ struct SparseMap { void SetDefaultLocParams(); // Set loc params - void SetLocParams(const LocalizationParameters& loc_params) { loc_params_ = loc_params; } + void SetLocParams(const LocalizationParameters& loc_params); void SetDetectorParams(int min_features, int max_features, int retries, double min_thresh, double default_thresh, double max_thresh); @@ -200,6 +200,11 @@ struct SparseMap { // needed for localization. void Load(const std::string & protobuf_file, bool localization = false); + // Optionally load keypoints. Call this after loading the map, if for example + // the user needs to use the keypoints for visualization or essential matrix + // estimation and those params differ from the default FLAG values. + void LoadKeypoints(const std::string & protobuf_file); + // construct from pid_to_cid_fid void InitializeCidFidToPid(); @@ -235,6 +240,7 @@ struct SparseMap { camera::CameraParameters camera_params_; mutable sparse_mapping::VocabDB vocab_db_; // TODO(oalexan1): Mutable means someone is doing something wrong. LocalizationParameters loc_params_; + std::string protobuf_file_; // e.g, 10th db image is 3rd image in cid_to_filename_ std::map db_to_cid_map_; diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index 080c22fc98..5d26396c78 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -89,7 +89,8 @@ SparseMap::SparseMap(const std::vector& filenames, const std::strin } SparseMap::SparseMap(const std::string& protobuf_file, bool localization) - : camera_params_(Eigen::Vector2i(-1, -1), Eigen::Vector2d::Constant(-1), Eigen::Vector2d(-1, -1)) { + : camera_params_(Eigen::Vector2i(-1, -1), Eigen::Vector2d::Constant(-1), Eigen::Vector2d(-1, -1)), + protobuf_file_(protobuf_file) { SetDefaultLocParams(); // The above camera params used bad values because we are expected to reload // later. @@ -248,6 +249,14 @@ void SparseMap::SetDefaultLocParams() { } } +void SparseMap::SetLocParams(const LocalizationParameters& loc_params) { + loc_params_ = loc_params; + // Load keypoints if required since these aren't loaded by default for localization + if (!protobuf_file_.empty() && (loc_params_.check_essential_matrix || loc_params_.visualize_localization_matches)) { + LoadKeypoints(protobuf_file_); + } +} + // Detect features in given images void SparseMap::DetectFeatures() { ff_common::ThreadPool pool; @@ -322,8 +331,8 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { cid_to_filename_.resize(num_frames); cid_to_descriptor_map_.resize(num_frames); - cid_to_keypoint_map_.resize(num_frames); if (!localization) { + cid_to_keypoint_map_.resize(num_frames); cid_to_cam_t_global_.resize(num_frames); } @@ -340,7 +349,8 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { // load keypoints - cid_to_keypoint_map_[cid].resize(Eigen::NoChange_t(), frame.feature_size()); + if (!localization) + cid_to_keypoint_map_[cid].resize(Eigen::NoChange_t(), frame.feature_size()); // Poke the first frame's first descriptor to see how long the // descriptor is. @@ -357,8 +367,8 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { for (int fid = 0; fid < frame.feature_size(); fid++) { sparse_mapping_protobuf::Feature feature = frame.feature(fid); - - cid_to_keypoint_map_[cid].col(fid) << feature.x(), feature.y(); + if (!localization) + cid_to_keypoint_map_[cid].col(fid) << feature.x(), feature.y(); // Copy the descriptors memcpy(cid_to_descriptor_map_[cid].ptr(fid), // Destination @@ -452,6 +462,41 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { close(input_fd); } +void SparseMap::LoadKeypoints(const std::string & protobuf_file) { + sparse_mapping_protobuf::Map map; + int input_fd = open(protobuf_file.c_str(), O_RDONLY); + if (input_fd < 0) + LOG(FATAL) << "Failed to open map file: " << protobuf_file; + + google::protobuf::io::ZeroCopyInputStream* input = + new google::protobuf::io::FileInputStream(input_fd); + if (!ReadProtobufFrom(input, &map)) { + LOG(FATAL) << "Failed to parse map file."; + } + + int num_frames = map.num_frames(); + cid_to_keypoint_map_.resize(num_frames); + + // load each frame + for (int cid = 0; cid < num_frames; cid++) { + sparse_mapping_protobuf::Frame frame; + if (!ReadProtobufFrom(input, &frame)) { + LOG(FATAL) << "Failed to parse frame."; + } + + // load keypoints + cid_to_keypoint_map_[cid].resize(Eigen::NoChange_t(), frame.feature_size()); + + for (int fid = 0; fid < frame.feature_size(); fid++) { + sparse_mapping_protobuf::Feature feature = frame.feature(fid); + cid_to_keypoint_map_[cid].col(fid) << feature.x(), feature.y(); + } + } + + delete input; + close(input_fd); +} + void SparseMap::SetDetectorParams(int min_features, int max_features, int retries, double min_thresh, double default_thresh, double max_thresh) { mutex_detector_.lock(); From ad699134501cd16d999876ad3e290afa1562301f Mon Sep 17 00:00:00 2001 From: Marina Moreira Date: Wed, 26 Jun 2024 16:01:43 -0700 Subject: [PATCH 44/61] fix linters --- .../include/interest_point/BAD.h | 10 ++-- localization/interest_point/src/BAD.cpp | 51 ++++++++++++++----- 2 files changed, 45 insertions(+), 16 deletions(-) diff --git a/localization/interest_point/include/interest_point/BAD.h b/localization/interest_point/include/interest_point/BAD.h index 434d19a8f5..21ab65c7af 100644 --- a/localization/interest_point/include/interest_point/BAD.h +++ b/localization/interest_point/include/interest_point/BAD.h @@ -3,12 +3,14 @@ * Constact: iago.suarez@thegraffter.com * Software developed in the PhD: Low-level vision for resource-limited devices */ -#ifndef EFFICIENT_DESCRIPTORS_BAD_H_ -#define EFFICIENT_DESCRIPTORS_BAD_H_ +#ifndef INTEREST_POINT_BAD_H_ +#define INTEREST_POINT_BAD_H_ -#include #include +#include +#include + namespace upm { /** @@ -94,4 +96,4 @@ class BAD : public cv::Feature2D { }; } // namespace upm -#endif // EFFICIENT_DESCRIPTORS_BAD_H_ +#endif // INTEREST_POINT_BAD_H_ diff --git a/localization/interest_point/src/BAD.cpp b/localization/interest_point/src/BAD.cpp index 2d26abeef9..47835952a9 100644 --- a/localization/interest_point/src/BAD.cpp +++ b/localization/interest_point/src/BAD.cpp @@ -3,11 +3,12 @@ * Constact: iago.suarez@thegraffter.com * Software developed in the PhD: Low-level vision for resource-limited devices */ -#include #include +#include +#include #define UPM_DEGREES_TO_RADS 0.017453292519943295 -#define UPM_ROUNDNUM(x) ((int)(x + 0.5f)) +#define UPM_ROUNDNUM(x) (static_cast(x + 0.5f)) #define UPM_BAD_EXTRA_RATIO_MARGIN 1.75 namespace upm { @@ -40,8 +41,8 @@ static inline void rectifyBoxes(const std::vector &boxes_par m11 = s; m12 = -s * 0.5f * patch_size.height + kp.pt.y; } else { - cosine = (kp.angle >= 0) ? float(cos(kp.angle * UPM_DEGREES_TO_RADS)) : 1.f; - sine = (kp.angle >= 0) ? float(sin(kp.angle * UPM_DEGREES_TO_RADS)) : 0.f; + cosine = (kp.angle >= 0) ? static_cast(cos(kp.angle * UPM_DEGREES_TO_RADS)) : 1.f; + sine = (kp.angle >= 0) ? static_cast(sin(kp.angle * UPM_DEGREES_TO_RADS)) : 0.f; m00 = s * cosine; m01 = -s * sine; @@ -133,7 +134,7 @@ static inline float computeBadResponse(const BAD::BoxPairParams &box_params, D = integral_img.at(box1y2, box1x2); // Calculate the mean intensity value of the pixels in the box - sum1 = float(A + D - B - C); + sum1 = static_cast(A + D - B - C); box_area1 = (box1y2 - box1y1) * (box1x2 - box1x1); assert(box_area1 > 0); average1 = sum1 / box_area1; @@ -145,7 +146,7 @@ static inline float computeBadResponse(const BAD::BoxPairParams &box_params, D = integral_img.at(box2y2, box2x2); // Calculate the mean intensity value of the pixels in the box - sum2 = float(A + D - B - C); + sum2 = static_cast(A + D - B - C); box_area2 = (box2y2 - box2y1) * (box2x2 - box2x1); assert(box_area2 > 0); average2 = sum2 / box_area2; @@ -262,7 +263,33 @@ BAD::BAD(float scale_factor, BadSize n_bits) { // {15,15,15,11,1}, {17,16,14,13,1}, {12,18,12,17,1}, {30,3,30,2,1}, {21,20,18,28,3}, {25,25,7,14,5}, {3,11,2,3,2}, // {25,5,9,21,4}, {6,15,4,28,3}, {9,9,3,3,3}, {16,19,14,16,2}, {10,25,10,20,1}, {2,17,2,15,1}, {17,15,15,16,1}, // {20,15,19,15,1}, {22,2,22,1,1}, {15,19,15,18,1}, {15,16,10,12,1}, {28,2,23,14,2}, {11,3,9,2,1}}; thresholds_ = - // {14.45,4.15,7.75,9.65,2.25,0.15,0.45,-0.95,3.65,-1.75,1.05,5.45,-0.05,-2.65,3.35,1.65,-1.55,2.85,3.05,22.05,-3.65,-0.15,-0.55,-0.05,3.25,-2.85,-1.25,10.45,-1.05,1.25,3.15,2.05,-0.55,-1.25,3.45,4.35,2.45,2.55,1.35,1.25,2.75,-0.15,8.35,0.35,-1.25,0.75,-0.45,-0.05,0.85,3.65,1.55,1.75,-0.35,1.35,4.85,-2.25,0.25,-2.15,3.35,1.95,6.25,0.35,24.45,-1.15,0.85,-1.95,5.15,1.35,0.85,0.35,-0.45,4.95,-0.25,2.45,11.75,0.85,-1.65,0.05,4.05,-0.35,-0.95,-0.25,49.35,0.85,1.95,0.25,1.15,-2.65,-0.25,0.85,-5.65,1.15,3.05,4.05,7.35,9.05,0.35,1.65,1.65,2.55,6.95,1.75,0.85,-1.15,1.35,5.45,1.35,-2.35,-0.15,0.85,-3.05,0.05,-0.35,-0.65,11.65,-0.85,1.15,2.35,-9.25,16.05,-1.45,1.95,0.35,-0.35,0.15,0.25,-1.35,0.65,-4.05,-2.25,1.05,-0.05,-1.55,0.25,69.45,0.15,-1.25,-1.85,-0.65,8.75,-0.95,1.95,1.05,-1.45,2.15,-1.85,-1.75,-2.95,2.65,0.65,-1.05,4.35,0.25,19.65,0.35,1.65,0.65,2.75,2.85,-10.95,3.65,-4.15,0.25,-0.65,-2.25,3.75,35.75,3.15,-0.55,1.95,-6.55,88.35,7.25,1.75,-4.15,0.25,0.25,0.65,3.75,1.65,2.85,42.15,11.75,-1.25,-8.25,0.05,2.15,0.65,-1.55,-2.75,1.15,-0.15,-0.75,16.85,1.15,1.45,15.35,19.45,8.65,-1.25,0.25,2.15,0.15,2.85,-2.25,1.75,-15.15,4.15,-0.45,-8.25,1.25,-0.85,3.55,0.45,-1.25,9.65,1.25,3.15,-2.05,-6.85,-0.05,3.25,7.05,2.35,-1.45,-1.05,20.25,1.15,1.35,1.05,5.15,2.55,0.55,0.55,-0.15,0.65,-28.35,3.85,2.05,-1.15,3.05,-0.95,-1.55,-0.35,101.95,0.35,-2.05,-2.15,4.25,105.15,1.15,27.45,30.15,18.45,-2.45,1.85,2.95,-3.75,-0.65,0.05,0.25,34.45,-2.05,0.25,3.25,2.05,2.85,3.45,20.95,1.45,-1.95,-0.35,-6.85,1.15,-31.95,11.85,2.75,0.15,8.35,1.15,2.15,-1.15,-1.05,2.45,1.45,0.15,-1.65,41.85,0.35,0.65,-0.35,0.25,56.75,23.55,88.85,-7.25,1.05,0.75,-1.05,-1.65,-9.75,-16.95,-0.05,-10.05,34.15,14.75,-0.95,1.45,4.85,-0.05,-0.35,0.75,64.75,24.25,-0.35,-13.65,2.85,1.75,-0.35,0.25,-12.15,108.05,-0.35,-3.35,1.95,-0.35,21.25,-20.05,95.85,-1.05,-17.75,-0.55,2.75,0.65,0.75,-1.85,2.65,-2.15,1.05,-0.05,4.25,3.75,-13.55,-0.05,105.95,0.45,3.05,9.35,79.25,1.75,7.65,-0.45,0.95,79.15,28.05,0.05,0.65,-0.35,0.95,2.05,1.15,2.75,-1.65,8.65,3.55,-0.25,-28.95,-7.35,122.25,0.55,4.75,1.75,11.15,0.15,2.55,0.05,-7.95,51.05,6.25,0.05,-1.15,0.75,26.65,-1.25,1.15,-0.55,0.05,5.85,1.55,2.25,-1.65,-16.85,-62.65,-1.25,-1.05,-1.55,1.35,0.25,-0.65,0.85,17.45,0.25,-9.35,34.35,0.95,-0.95,-10.05,1.45,-6.05,93.25,3.15,-10.85,-1.65,-0.15,-2.45,-0.35,0.15,118.15,-81.85,4.05,1.05,-0.85,152.35,0.65,1.35,-12.35,95.35,-23.25,-0.75,75.65,50.85,47.85,2.55,0.55,0.15,0.25,38.15,-2.65,-1.95,-1.05,110.25,35.25,2.65,3.65,18.75,89.45,-0.55,0.35,0.25,105.05,0.25,1.25,-34.65,-0.55,-0.15,0.75,-0.15,-0.15,-94.25,-12.05,-15.35,-1.75,31.35,0.15,-2.15,-0.15,-12.05,-0.35,-0.65,-0.55,28.95,39.05,7.05,0.65,-1.65,2.85,4.85,-1.85,1.75,-31.65,0.05,13.75,-0.35,0.35,-5.75,83.85,0.95,27.95,-0.25,-19.05,2.45,-13.25,44.05,51.85,-0.05,0.05,79.35,111.25,-61.65,3.05,-69.95,35.65,62.05,-0.25,-1.05,-2.95,0.95,-0.15,-18.15,-18.65,74.55,2.65}; + // {14.45,4.15,7.75,9.65,2.25,0.15,0.45,-0.95,3.65,-1.75,1.05,5.45,-0.05,-2.65,3.35,1.65,-1.55,2.85,3.05,22.05, + // -3.65,-0.15,-0.55,-0.05,3.25,-2.85,-1.25,10.45,-1.05,1.25,3.15,2.05,-0.55,-1.25,3.45,4.35,2.45,2.55,1.35,1.25, + // 2.75,-0.15,8.35,0.35,-1.25,0.75,-0.45,-0.05,0.85,3.65,1.55,1.75,-0.35,1.35,4.85,-2.25,0.25,-2.15,3.35,1.95,6.25, + // 0.35,24.45,-1.15,0.85,-1.95,5.15,1.35,0.85,0.35,-0.45,4.95,-0.25,2.45,11.75,0.85,-1.65,0.05,4.05,-0.35,-0.95, + // -0.25,49.35,0.85,1.95,0.25,1.15,-2.65,-0.25,0.85,-5.65,1.15,3.05,4.05,7.35,9.05,0.35,1.65,1.65,2.55,6.95,1.75, + // 0.85,-1.15,1.35,5.45,1.35,-2.35,-0.15,0.85,-3.05,0.05,-0.35,-0.65,11.65,-0.85,1.15,2.35,-9.25,16.05,-1.45,1.95, + // 0.35,-0.35,0.15,0.25,-1.35,0.65,-4.05,-2.25,1.05,-0.05,-1.55,0.25,69.45,0.15,-1.25,-1.85,-0.65,8.75,-0.95,1.95, + // 1.05,-1.45,2.15,-1.85,-1.75,-2.95,2.65,0.65,-1.05,4.35,0.25,19.65,0.35,1.65,0.65,2.75,2.85,-10.95,3.65,-4.15, + // 0.25,-0.65,-2.25,3.75,35.75,3.15,-0.55,1.95,-6.55,88.35,7.25,1.75,-4.15,0.25,0.25,0.65,3.75,1.65,2.85,42.15, + // 11.75, -1.25,-8.25,0.05,2.15,0.65,-1.55,-2.75,1.15,-0.15,-0.75,16.85,1.15,1.45,15.35,19.45,8.65,-1.25,0.25, + // 2.15,0.15,2.85, -2.25,1.75,-15.15,4.15,-0.45,-8.25,1.25,-0.85,3.55,0.45,-1.25,9.65,1.25,3.15,-2.05,-6.85,-0.05, + // 3.25,7.05,2.35, -1.45,-1.05,20.25,1.15,1.35,1.05,5.15,2.55,0.55,0.55,-0.15,0.65,-28.35,3.85,2.05,-1.15,3.05, + // -0.95,-1.55,-0.35, 101.95,0.35,-2.05,-2.15,4.25,105.15,1.15,27.45,30.15,18.45,-2.45,1.85,2.95,-3.75,-0.65,0.05, + // 0.25,34.45,-2.05, 0.25,3.25,2.05,2.85,3.45,20.95,1.45,-1.95,-0.35,-6.85,1.15,-31.95,11.85,2.75,0.15,8.35,1.15, + // 2.15,-1.15,-1.05, 2.45,1.45,0.15,-1.65,41.85,0.35,0.65,-0.35,0.25,56.75,23.55,88.85,-7.25,1.05,0.75,-1.05,-1.65, + // -9.75,-16.95,-0.05, -10.05,34.15,14.75,-0.95,1.45,4.85,-0.05,-0.35,0.75,64.75,24.25,-0.35,-13.65,2.85,1.75, + // -0.35,0.25,-12.15,108.05, -0.35,-3.35,1.95,-0.35,21.25,-20.05,95.85,-1.05,-17.75,-0.55,2.75,0.65,0.75,-1.85, + // 2.65,-2.15,1.05,-0.05,4.25,3.75, -13.55,-0.05,105.95,0.45,3.05,9.35,79.25,1.75,7.65,-0.45,0.95,79.15,28.05,0.05, + // 0.65,-0.35,0.95,2.05,1.15,2.75, -1.65,8.65,3.55,-0.25,-28.95,-7.35,122.25,0.55,4.75,1.75,11.15,0.15,2.55,0.05, + // -7.95,51.05,6.25,0.05,-1.15,0.75, 26.65,-1.25,1.15,-0.55,0.05,5.85,1.55,2.25,-1.65,-16.85,-62.65,-1.25,-1.05, + // -1.55,1.35,0.25,-0.65,0.85,17.45, 0.25, -9.35,34.35,0.95,-0.95,-10.05,1.45,-6.05,93.25,3.15,-10.85,-1.65,-0.15, + // -2.45,-0.35,0.15,118.15,-81.85,4.05,1.05, -0.85,152.35,0.65,1.35,-12.35,95.35,-23.25,-0.75,75.65,50.85,47.85, + // 2.55,0.55,0.15,0.25,38.15,-2.65,-1.95,-1.05, 110.25,35.25,2.65,3.65,18.75,89.45,-0.55,0.35,0.25,105.05,0.25, + // 1.25,-34.65,-0.55,-0.15,0.75,-0.15,-0.15,-94.25, -12.05,-15.35,-1.75,31.35,0.15,-2.15,-0.15,-12.05,-0.35,-0.65, + // -0.55,28.95,39.05,7.05,0.65,-1.65,2.85,4.85,-1.85, 1.75,-31.65,0.05,13.75,-0.35,0.35,-5.75,83.85,0.95,27.95, + // -0.25,-19.05,2.45,-13.25,44.05,51.85,-0.05,0.05,79.35,111.25,-61.65,3.05,-69.95,35.65,62.05,-0.25,-1.05,-2.95, + // 0.95,-0.15,-18.15,-18.65,74.55,2.65}; // Without data augmentation box_params_ = { @@ -510,7 +537,7 @@ void BAD::compute(cv::InputArray _image, cv::integral(image, integral_img); // Create the output array of descriptors - _descriptors.create((int)keypoints.size(), descriptorSize(), descriptorType()); + _descriptors.create(static_cast(keypoints.size()), descriptorSize(), descriptorType()); // descriptor storage cv::Mat descriptors = _descriptors.getMat(); @@ -533,7 +560,7 @@ void BAD::computeBAD(const cv::Mat &integral_img, #ifndef UPM_BAD_PARALLEL const cv::Range range(0, keypoints.size()); #else - cv::parallel_for_(cv::Range(0, int(keypoints.size())), [&](const cv::Range &range){ + cv::parallel_for_(cv::Range(0, static_cast(keypoints.size())), [&](const cv::Range &range){ // NOLINT #endif // Get a pointer to the first element in the range // Get a pointer to the first element in the range @@ -553,7 +580,7 @@ void BAD::computeBAD(const cv::Mat &integral_img, if (isKeypointInTheBorder(keypoints[kpIdx], frame_size, patch_size_, scale_factor_)) { // Code to process the keypoints in the image margins for (box_pair_idx = 0; box_pair_idx < box_params_.size(); box_pair_idx++) { - bit_idx = 7 - int(box_pair_idx % 8); + bit_idx = 7 - static_cast(box_pair_idx % 8); response_fun = computeBadResponse(img_boxes[box_pair_idx], integral_img); // Set the bit to 1 if the response function is less or equal to the threshod byte |= (response_fun <= thresholds_[box_pair_idx]) << bit_idx; @@ -568,7 +595,7 @@ void BAD::computeBAD(const cv::Mat &integral_img, // Code to process the keypoints in the image center box_pair = img_boxes.data(); for (box_pair_idx = 0; box_pair_idx < box_params_.size(); box_pair_idx++) { - bit_idx = 7 - int(box_pair_idx % 8); + bit_idx = 7 - static_cast(box_pair_idx % 8); // For the first box, we calculate its margin coordinates box1x1 = box_pair->x1 - box_pair->boxRadius; @@ -607,5 +634,5 @@ void BAD::computeBAD(const cv::Mat &integral_img, #ifdef UPM_BAD_PARALLEL }); #endif - } // namespace upm + } // namespace upm ## NOLINT } From 2a7aef3d727760f065e901d278ab3b23bf2d428a Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Wed, 26 Jun 2024 16:22:34 -0700 Subject: [PATCH 45/61] added essential ransac iterations as params --- astrobee/config/localization.config | 3 +++ .../include/interest_point/essential.h | 25 ++++++++----------- localization/interest_point/src/essential.cc | 4 +-- .../localization_node/src/localization.cc | 1 + .../sparse_mapping/localization_parameters.h | 1 + .../include/sparse_mapping/tensor.h | 2 +- localization/sparse_mapping/src/sparse_map.cc | 4 +-- localization/sparse_mapping/src/tensor.cc | 4 +-- 8 files changed, 22 insertions(+), 22 deletions(-) diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index 6b9216ddca..68e23c41a8 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -28,6 +28,7 @@ brisk_num_ransac_iterations = 100 brisk_early_break_landmarks = 100 brisk_histogram_equalization = 1 brisk_check_essential_matrix = false +brisk_essential_ransac_iterations = 2000 brisk_add_similar_images = false brisk_add_best_previous_image = false brisk_hamming_distance = 90 @@ -49,6 +50,7 @@ teblid512_num_ransac_iterations = 1000 teblid512_early_break_landmarks = 100 teblid512_histogram_equalization = 3 teblid512_check_essential_matrix = true +teblid512_essential_ransac_iterations = 2000 teblid512_add_similar_images = true teblid512_add_best_previous_image = true teblid512_hamming_distance = 85 @@ -71,6 +73,7 @@ teblid256_num_ransac_iterations = 1000 teblid256_early_break_landmarks = 100 teblid256_histogram_equalization = 3 teblid256_check_essential_matrix = true +teblid256_essential_ransac_iterations = 2000 teblid256_add_similar_images = true teblid256_add_best_previous_image = true teblid256_hamming_distance = 85 diff --git a/localization/interest_point/include/interest_point/essential.h b/localization/interest_point/include/interest_point/essential.h index 0d86d4990c..89d37ae71a 100644 --- a/localization/interest_point/include/interest_point/essential.h +++ b/localization/interest_point/include/interest_point/essential.h @@ -27,22 +27,17 @@ namespace interest_point { // Performs a robust, ransac, solving for the essential matrix // between interest point measurements in x1 and x2. - bool RobustEssential(Eigen::Matrix3d const& k1, Eigen::Matrix3d const& k2, - Eigen::Matrix2Xd const& x1, Eigen::Matrix2Xd const& x2, - Eigen::Matrix3d * e, - std::vector * vec_inliers, - std::pair const& size1, - std::pair const& size2, - double * error_max, - double precision); +bool RobustEssential(Eigen::Matrix3d const& k1, Eigen::Matrix3d const& k2, Eigen::Matrix2Xd const& x1, + Eigen::Matrix2Xd const& x2, Eigen::Matrix3d* e, std::vector* vec_inliers, + std::pair const& size1, std::pair const& size2, double* error_max, + double precision, const int ransac_iterations = 4096); - // Solves for the RT (Rotation and Translation) from the essential - // matrix and x1 and x2. There are 4 possible, and this returns the - // best of the 4 solutions. - bool EstimateRTFromE(Eigen::Matrix3d const& k1, Eigen::Matrix3d const& k2, - Eigen::Matrix2Xd const& x1, Eigen::Matrix2Xd const& x2, - Eigen::Matrix3d const& e, std::vector const& vec_inliers, - Eigen::Matrix3d * r, Eigen::Vector3d * t); +// Solves for the RT (Rotation and Translation) from the essential +// matrix and x1 and x2. There are 4 possible, and this returns the +// best of the 4 solutions. +bool EstimateRTFromE(Eigen::Matrix3d const& k1, Eigen::Matrix3d const& k2, Eigen::Matrix2Xd const& x1, + Eigen::Matrix2Xd const& x2, Eigen::Matrix3d const& e, std::vector const& vec_inliers, + Eigen::Matrix3d* r, Eigen::Vector3d* t); } // end namespace interest_point diff --git a/localization/interest_point/src/essential.cc b/localization/interest_point/src/essential.cc index 7fae3debf0..9382ec9bb9 100644 --- a/localization/interest_point/src/essential.cc +++ b/localization/interest_point/src/essential.cc @@ -38,7 +38,7 @@ bool interest_point::RobustEssential(Eigen::Matrix3d const& k1, Eigen::Matrix3d std::pair const& size1, std::pair const& size2, double * error_max, - double precision) { + double precision, const int ransac_iterations) { CHECK(e) << "Missing e argument"; CHECK(vec_inliers) << "Missing vec inliers argument"; @@ -53,7 +53,7 @@ bool interest_point::RobustEssential(Eigen::Matrix3d const& k1, Eigen::Matrix3d x2, size2.first, size2.second, k1, k2); std::pair ransac_output = - openMVG::robust::ACRANSAC(kernel, *vec_inliers, 4096 /* iterations */, + openMVG::robust::ACRANSAC(kernel, *vec_inliers, ransac_iterations /* iterations */, e, precision, false); *error_max = ransac_output.first; diff --git a/localization/localization_node/src/localization.cc b/localization/localization_node/src/localization.cc index 948cfab96c..a81b76acb9 100644 --- a/localization/localization_node/src/localization.cc +++ b/localization/localization_node/src/localization.cc @@ -51,6 +51,7 @@ void Localizer::ReadParams(config_reader::ConfigReader& config) { LOAD_PARAM(loc_params.early_break_landmarks, config, prefix); LOAD_PARAM(loc_params.histogram_equalization, config, prefix); LOAD_PARAM(loc_params.check_essential_matrix, config, prefix); + LOAD_PARAM(loc_params.essential_ransac_iterations, config, prefix); LOAD_PARAM(loc_params.add_similar_images, config, prefix); LOAD_PARAM(loc_params.add_best_previous_image, config, prefix); LOAD_PARAM(loc_params.hamming_distance, config, prefix); diff --git a/localization/sparse_mapping/include/sparse_mapping/localization_parameters.h b/localization/sparse_mapping/include/sparse_mapping/localization_parameters.h index f16ea8db33..c37905c6e9 100644 --- a/localization/sparse_mapping/include/sparse_mapping/localization_parameters.h +++ b/localization/sparse_mapping/include/sparse_mapping/localization_parameters.h @@ -27,6 +27,7 @@ struct LocalizationParameters { int early_break_landmarks; int histogram_equalization; bool check_essential_matrix; + int essential_ransac_iterations; bool add_similar_images; bool add_best_previous_image; int hamming_distance; diff --git a/localization/sparse_mapping/include/sparse_mapping/tensor.h b/localization/sparse_mapping/include/sparse_mapping/tensor.h index a6b911e59f..e72cfc60ef 100644 --- a/localization/sparse_mapping/include/sparse_mapping/tensor.h +++ b/localization/sparse_mapping/include/sparse_mapping/tensor.h @@ -148,7 +148,7 @@ namespace sparse_mapping { void FindEssentialAndInliers(Eigen::Matrix2Xd const& keypoints1, Eigen::Matrix2Xd const& keypoints2, std::vector const& matches, camera::CameraParameters const& camera_params, std::vector* inlier_matches, std::vector* vec_inliers, - Eigen::Matrix3d* essential_matrix); + Eigen::Matrix3d* essential_matrix, const int ransac_iterations = 4096); void BuildMapFindEssentialAndInliers(const Eigen::Matrix2Xd & keypoints1, const Eigen::Matrix2Xd & keypoints2, diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index 5d26396c78..b6c3c37fa1 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -809,9 +809,9 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const std::vector inlier_matches; std::vector vec_inliers; Eigen::Matrix3d essential_matrix; - // TODO(rsoussan): Add param for num ransac iterations? Time this? (uses 4096 its...) FindEssentialAndInliers(test_keypoints, cid_to_keypoint_map_[cid], all_matches[i], camera_params_, - &inlier_matches, &vec_inliers, &essential_matrix); + &inlier_matches, &vec_inliers, &essential_matrix, + loc_params_.essential_ransac_iterations); all_matches[i] = inlier_matches; if (loc_params_.verbose_localization) std::cout << "Matches after essential filtering: " << all_matches[i].size() << std::endl; diff --git a/localization/sparse_mapping/src/tensor.cc b/localization/sparse_mapping/src/tensor.cc index bf003a1839..b3323277af 100644 --- a/localization/sparse_mapping/src/tensor.cc +++ b/localization/sparse_mapping/src/tensor.cc @@ -1936,7 +1936,7 @@ void ReadAffineCSV(std::string const& input_filename, void FindEssentialAndInliers(Eigen::Matrix2Xd const& keypoints1, Eigen::Matrix2Xd const& keypoints2, std::vector const& matches, camera::CameraParameters const& camera_params, std::vector* inlier_matches, std::vector* vec_inliers, - Eigen::Matrix3d* essential_matrix) { + Eigen::Matrix3d* essential_matrix, const int ransac_iterations) { // Initialize the outputs inlier_matches->clear(); @@ -1960,7 +1960,7 @@ void FindEssentialAndInliers(Eigen::Matrix2Xd const& keypoints1, Eigen::Matrix2X essential_matrix, vec_inliers, image_size, image_size, &error_max, - max_expected_error)) { + max_expected_error, ransac_iterations)) { VLOG(2) << " | Estimation of essential matrix failed!\n"; return; } From 29adb0e94fe56fef72468e2eb1b748181476c80c Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Wed, 26 Jun 2024 16:28:59 -0700 Subject: [PATCH 46/61] added returning scores in querydb call --- .../sparse_mapping/include/sparse_mapping/vocab_tree.h | 7 ++----- localization/sparse_mapping/src/sparse_map.cc | 3 ++- localization/sparse_mapping/src/tensor.cc | 3 ++- localization/sparse_mapping/src/vocab_tree.cc | 4 +++- 4 files changed, 9 insertions(+), 8 deletions(-) diff --git a/localization/sparse_mapping/include/sparse_mapping/vocab_tree.h b/localization/sparse_mapping/include/sparse_mapping/vocab_tree.h index 6f6782d82d..4690648b70 100644 --- a/localization/sparse_mapping/include/sparse_mapping/vocab_tree.h +++ b/localization/sparse_mapping/include/sparse_mapping/vocab_tree.h @@ -94,11 +94,8 @@ namespace sparse_mapping { void ResetDB(VocabDB* db); // Query similar images from database - void QueryDB(std::string const& descriptor, - VocabDB * vocab_db, - int num_similar, - cv::Mat const& descriptors, - std::vector * indices); + void QueryDB(std::string const& descriptor, VocabDB* vocab_db, int num_similar, cv::Mat const& descriptors, + std::vector* indices, std::vector* scores); void BuildDBforDBoW2(sparse_mapping::SparseMap* map, std::string const& descriptor, diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index b6c3c37fa1..2527fc3dd1 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -729,6 +729,7 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const std::vector* inlier_observations, std::vector* cid_list, const cv::Mat& image) { std::vector indices; + std::vector query_scores; // Query the vocab tree. if (cid_list == NULL) sparse_mapping::QueryDB(detector_.GetDetectorName(), @@ -738,7 +739,7 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const // them below. loc_params_.num_similar + loc_params_.num_extra_localization_db_images, test_descriptors, - &indices); + &indices, &query_scores); else indices = *cid_list; if (indices.empty()) { diff --git a/localization/sparse_mapping/src/tensor.cc b/localization/sparse_mapping/src/tensor.cc index b3323277af..e51fa3f94b 100644 --- a/localization/sparse_mapping/src/tensor.cc +++ b/localization/sparse_mapping/src/tensor.cc @@ -221,10 +221,11 @@ void MatchFeatures(const std::string & essential_file, ff_common::PrintProgressBar(stdout, static_cast(cid) / static_cast (s->cid_to_keypoint_map_.size() - 1)); std::vector indices, queried_indices; + std::vector scores; sparse_mapping::QueryDB(s->detector_.GetDetectorName(), &s->vocab_db_, s->loc_params().num_similar, s->cid_to_descriptor_map_[cid], - &queried_indices); + &queried_indices, &scores); if (!queried_indices.empty()) { // always include the next three images diff --git a/localization/sparse_mapping/src/vocab_tree.cc b/localization/sparse_mapping/src/vocab_tree.cc index db6bafacc3..ccad057f76 100644 --- a/localization/sparse_mapping/src/vocab_tree.cc +++ b/localization/sparse_mapping/src/vocab_tree.cc @@ -379,8 +379,9 @@ void MatDescrToVec(cv::Mat const& mat, DBoW2::BriefDescriptor * brief) { // at most num_similar such indices. void QueryDB(std::string const& descriptor, VocabDB * vocab_db, int num_similar, cv::Mat const& descriptors, - std::vector * indices) { + std::vector * indices, std::vector * scores) { indices->clear(); + scores->clear(); if (vocab_db->binary_db != NULL) { assert(IsBinaryDescriptor(descriptor)); @@ -398,6 +399,7 @@ void QueryDB(std::string const& descriptor, VocabDB * vocab_db, for (size_t j = 0; j < ret.size(); j++) { indices->push_back(ret[j].Id); + scores->push_back(ret[j].Score); } } else { // no database specified From f34d0d378ca84dd087a500829b1fa7f249ca1148 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Wed, 26 Jun 2024 17:29:26 -0700 Subject: [PATCH 47/61] added check for query score ratio --- astrobee/config/localization.config | 3 +++ localization/localization_node/src/localization.cc | 1 + .../include/sparse_mapping/localization_parameters.h | 3 ++- localization/sparse_mapping/src/sparse_map.cc | 8 ++++++++ 4 files changed, 14 insertions(+), 1 deletion(-) diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index 68e23c41a8..d174b1491e 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -23,6 +23,7 @@ visualize_localization_matches = false -- BRISK brisk_num_similar = 20 +brisk_min_query_score_ratio = 0 brisk_ransac_inlier_tolerance = 5 brisk_num_ransac_iterations = 100 brisk_early_break_landmarks = 100 @@ -45,6 +46,7 @@ brisk_detection_retries = 1 -- TEBLID512 teblid512_num_similar = 20 +teblid512_min_query_score_ratio = 0.45 teblid512_ransac_inlier_tolerance = 3 teblid512_num_ransac_iterations = 1000 teblid512_early_break_landmarks = 100 @@ -68,6 +70,7 @@ teblid512_detection_retries = 5 -- TEBLID256 teblid256_num_similar = 20 +teblid256_min_query_score_ratio = 0.45 teblid256_ransac_inlier_tolerance = 3 teblid256_num_ransac_iterations = 1000 teblid256_early_break_landmarks = 100 diff --git a/localization/localization_node/src/localization.cc b/localization/localization_node/src/localization.cc index a81b76acb9..c7afe87b58 100644 --- a/localization/localization_node/src/localization.cc +++ b/localization/localization_node/src/localization.cc @@ -46,6 +46,7 @@ void Localizer::ReadParams(config_reader::ConfigReader& config) { // Loc params sparse_mapping::LocalizationParameters loc_params; LOAD_PARAM(loc_params.num_similar, config, prefix); + LOAD_PARAM(loc_params.min_query_score_ratio, config, prefix); LOAD_PARAM(loc_params.ransac_inlier_tolerance, config, prefix); LOAD_PARAM(loc_params.num_ransac_iterations, config, prefix); LOAD_PARAM(loc_params.early_break_landmarks, config, prefix); diff --git a/localization/sparse_mapping/include/sparse_mapping/localization_parameters.h b/localization/sparse_mapping/include/sparse_mapping/localization_parameters.h index c37905c6e9..b261f81c27 100644 --- a/localization/sparse_mapping/include/sparse_mapping/localization_parameters.h +++ b/localization/sparse_mapping/include/sparse_mapping/localization_parameters.h @@ -22,6 +22,7 @@ namespace sparse_mapping { struct LocalizationParameters { int num_similar; + double min_query_score_ratio; int ransac_inlier_tolerance; int num_ransac_iterations; int early_break_landmarks; @@ -31,7 +32,7 @@ struct LocalizationParameters { bool add_similar_images; bool add_best_previous_image; int hamming_distance; - double goodness_ratio; + double goodness_ratio; bool use_clahe; int num_extra_localization_db_images; bool verbose_localization; diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index 2527fc3dd1..1fa90dadf4 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -760,6 +760,7 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const } if (add_cid) { indices.insert(indices.begin(), *best_previous_cid_); + query_scores.insert(query_scores.begin(), query_scores[0]); } best_previous_cid_ = boost::none; } @@ -788,6 +789,12 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const if (loc_params_.verbose_localization) std::cout << "Checking index: " << i << ", cid: " << cid << std::endl; similarity_rank.emplace_back(0); all_matches.emplace_back(std::vector()); + if (query_scores[i]/ static_cast(query_scores[0]) < loc_params_.min_query_score_ratio) { + if (loc_params_.verbose_localization) + std::cout << "Query score ratio too low: " << query_scores[i] / static_cast(query_scores[0]) + << std::endl; + continue; + } interest_point::FindMatches(test_descriptors, cid_to_descriptor_map_[cid], &all_matches[i], loc_params_.hamming_distance, loc_params_.goodness_ratio); @@ -840,6 +847,7 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const // Make new matching cid the next cid to match to if (add_cid) { indices.insert(indices.begin() + index, matching_cid); + query_scores.insert(query_scores.begin() + index, query_scores[0]); ++index; } } From 741d9f13f17c101b2c63af9d1fb829b70bb27421 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Thu, 27 Jun 2024 08:10:55 -0700 Subject: [PATCH 48/61] added dynamic threshold adjusting based on success rates --- astrobee/config/localization.config | 19 ++++++++++++-- .../include/interest_point/matching.h | 2 ++ .../include/localization_node/localization.h | 13 ++++++++++ .../localization_node/src/localization.cc | 25 ++++++++++++++++++- .../include/sparse_mapping/sparse_map.h | 1 + 5 files changed, 57 insertions(+), 3 deletions(-) diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index d174b1491e..55a3efd734 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -43,6 +43,10 @@ brisk_max_threshold = 110.0 brisk_min_features = 200 brisk_max_features = 800 brisk_detection_retries = 1 +-- Localizer Threshold Params +brisk_success_history_size = 10 +brisk_min_success_rate = 0 +brisk_max_success_rate = 1 -- TEBLID512 teblid512_num_similar = 20 @@ -62,12 +66,18 @@ teblid512_num_extra_localization_db_images = 0 -- Detection Params teblid512_min_threshold = 10.0 -teblid512_default_threshold = 20.0 +teblid512_default_threshold = 50.0 teblid512_max_threshold = 110.0 teblid512_min_features = 1000 teblid512_max_features = 3000 teblid512_detection_retries = 5 +-- Localizer Threshold Params +teblid512_success_history_size = 10 +teblid512_min_success_rate = 0.3 +teblid512_max_success_rate = 0.9 + + -- TEBLID256 teblid256_num_similar = 20 teblid256_min_query_score_ratio = 0.45 @@ -86,8 +96,13 @@ teblid256_num_extra_localization_db_images = 0 -- Detection Params teblid256_min_threshold = 10.0 -teblid256_default_threshold = 20.0 +teblid256_default_threshold = 50.0 teblid256_max_threshold = 110.0 teblid256_min_features = 1000 teblid256_max_features = 3000 teblid256_detection_retries = 5 + +-- Localizer Threshold Params +teblid256_success_history_size = 10 +teblid256_min_success_rate = 0.3 +teblid256_max_success_rate = 0.9 diff --git a/localization/interest_point/include/interest_point/matching.h b/localization/interest_point/include/interest_point/matching.h index 408e4e521d..e77b53dc99 100644 --- a/localization/interest_point/include/interest_point/matching.h +++ b/localization/interest_point/include/interest_point/matching.h @@ -82,6 +82,8 @@ namespace interest_point { friend bool operator== (FeatureDetector const& A, FeatureDetector const& B) { return (A.detector_name_ == B.detector_name_); } + + DynamicDetector& dynamic_detector() { return *detector_; } }; /** diff --git a/localization/localization_node/include/localization_node/localization.h b/localization/localization_node/include/localization_node/localization.h index 81147d45d8..5042caba3c 100644 --- a/localization/localization_node/include/localization_node/localization.h +++ b/localization/localization_node/include/localization_node/localization.h @@ -26,8 +26,16 @@ #include #include +#include + namespace localization_node { +struct ThresholdParams { + int success_history_size; + double min_success_rate; + double max_success_rate; +}; + class Localizer { public: explicit Localizer(sparse_mapping::SparseMap* map); @@ -35,7 +43,12 @@ class Localizer { bool Localize(cv_bridge::CvImageConstPtr image_ptr, ff_msgs::VisualLandmarks* vl, Eigen::Matrix2Xd* image_keypoints = NULL); private: + void AdjustThresholds(); + sparse_mapping::SparseMap* map_; + // Success params for adjusting keypoint thresholds + std::deque successes_; + ThresholdParams params_; }; }; // namespace localization_node diff --git a/localization/localization_node/src/localization.cc b/localization/localization_node/src/localization.cc index c7afe87b58..40b5f019d5 100644 --- a/localization/localization_node/src/localization.cc +++ b/localization/localization_node/src/localization.cc @@ -72,6 +72,11 @@ void Localizer::ReadParams(config_reader::ConfigReader& config) { LOAD_PARAM(min_features, config, prefix); LOAD_PARAM(max_features, config, prefix); + // Localizer threshold params + LOAD_PARAM(params_.success_history_size, config, prefix); + LOAD_PARAM(params_.min_success_rate, config, prefix); + LOAD_PARAM(params_.max_success_rate, config, prefix); + // This check must happen before the histogram_equalization flag is set into the map // to compare with what is there already. sparse_mapping::HistogramEqualizationCheck(map_->GetHistogramEqualization(), @@ -109,9 +114,13 @@ bool Localizer::Localize(cv_bridge::CvImageConstPtr image_ptr, ff_msgs::VisualLa std::vector observations; if (!map_->Localize(image_descriptors, *image_keypoints, &camera, &landmarks, &observations, nullptr, image_ptr->image)) { + successes_.emplace_back(0); + AdjustThresholds(); // LOG(INFO) << "Failed to localize image."; return false; } + successes_.emplace_back(1); + AdjustThresholds(); Eigen::Affine3d global_pose = camera.GetTransform().inverse(); Eigen::Quaterniond quat(global_pose.rotation()); @@ -134,4 +143,18 @@ bool Localizer::Localize(cv_bridge::CvImageConstPtr image_ptr, ff_msgs::VisualLa return true; } -}; // namespace localization_node +void Localizer::AdjustThresholds() { + if (successes_.size() < params_.success_history_size) return; + while (successes_.size() > params_.success_history_size) { + successes_.pop_front(); + } + const double average = + std::accumulate(successes_.cbegin(), successes_.cend(), 0) / static_cast(successes_.size()); + if (average < params_.min_success_rate) { + map_->detector().dynamic_detector().TooFew(); + } + if (average > params_.max_success_rate) { + map_->detector().dynamic_detector().TooMany(); + } +} +} // namespace localization_node diff --git a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h index cefa4b089f..6b88ab8d94 100644 --- a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h +++ b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h @@ -221,6 +221,7 @@ struct SparseMap { void PruneMap(void); std::string GetDetectorName() { return detector_.GetDetectorName(); } + interest_point::FeatureDetector& detector() { return detector_; } int GetHistogramEqualization() {return loc_params_.histogram_equalization;} const LocalizationParameters& loc_params() { return loc_params_; } From f2985ec12eef5825767b0ee092e27c55ba918c69 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Thu, 27 Jun 2024 08:12:58 -0700 Subject: [PATCH 49/61] adjusted params --- astrobee/config/localization.config | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index 55a3efd734..b67cfad8b2 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -68,8 +68,8 @@ teblid512_num_extra_localization_db_images = 0 teblid512_min_threshold = 10.0 teblid512_default_threshold = 50.0 teblid512_max_threshold = 110.0 -teblid512_min_features = 1000 -teblid512_max_features = 3000 +teblid512_min_features = 800 +teblid512_max_features = 2000 teblid512_detection_retries = 5 -- Localizer Threshold Params @@ -98,8 +98,8 @@ teblid256_num_extra_localization_db_images = 0 teblid256_min_threshold = 10.0 teblid256_default_threshold = 50.0 teblid256_max_threshold = 110.0 -teblid256_min_features = 1000 -teblid256_max_features = 3000 +teblid256_min_features = 800 +teblid256_max_features = 2000 teblid256_detection_retries = 5 -- Localizer Threshold Params From 394f156c2ba7c5e65a3481a4bea8b2f68708e443 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Thu, 27 Jun 2024 08:49:26 -0700 Subject: [PATCH 50/61] updated loc config --- astrobee/config/localization.config | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index b67cfad8b2..0b80e8cd01 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -66,11 +66,11 @@ teblid512_num_extra_localization_db_images = 0 -- Detection Params teblid512_min_threshold = 10.0 -teblid512_default_threshold = 50.0 -teblid512_max_threshold = 110.0 -teblid512_min_features = 800 +teblid512_default_threshold = 60.0 +teblid512_max_threshold = 100.0 +teblid512_min_features = 900 teblid512_max_features = 2000 -teblid512_detection_retries = 5 +teblid512_detection_retries = 1 -- Localizer Threshold Params teblid512_success_history_size = 10 @@ -96,11 +96,11 @@ teblid256_num_extra_localization_db_images = 0 -- Detection Params teblid256_min_threshold = 10.0 -teblid256_default_threshold = 50.0 -teblid256_max_threshold = 110.0 -teblid256_min_features = 800 +teblid256_default_threshold = 60.0 +teblid256_max_threshold = 100.0 +teblid256_min_features = 900 teblid256_max_features = 2000 -teblid256_detection_retries = 5 +teblid256_detection_retries = 1 -- Localizer Threshold Params teblid256_success_history_size = 10 From 179f31e1cbacf7db83dd9ca27e8c326058e89a98 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Thu, 27 Jun 2024 08:56:00 -0700 Subject: [PATCH 51/61] adjusted teblid dyn thresholds --- localization/interest_point/src/matching.cc | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/localization/interest_point/src/matching.cc b/localization/interest_point/src/matching.cc index 951c6ef7f3..81a7ec6532 100644 --- a/localization/interest_point/src/matching.cc +++ b/localization/interest_point/src/matching.cc @@ -206,14 +206,14 @@ namespace interest_point { teblid_->compute(image, *keypoints, *keypoints_description); } virtual void TooMany(void) { - dynamic_thresh_ *= 1.25; + dynamic_thresh_ *= 1.1; dynamic_thresh_ = static_cast(dynamic_thresh_); // for backwards compatibility if (dynamic_thresh_ > max_thresh_) dynamic_thresh_ = max_thresh_; brisk_->setThreshold(dynamic_thresh_); } virtual void TooFew(void) { - dynamic_thresh_ *= 0.8; + dynamic_thresh_ *= 0.9; dynamic_thresh_ = static_cast(dynamic_thresh_); // for backwards compatibility if (dynamic_thresh_ < min_thresh_) dynamic_thresh_ = min_thresh_; From 773b21aedefe3a9b8ffebedd4c0c7101629c789c Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Thu, 27 Jun 2024 09:24:04 -0700 Subject: [PATCH 52/61] added check for feature counts to dynamic thresholding --- astrobee/config/localization.config | 8 ++++---- .../interest_point/include/interest_point/matching.h | 3 +++ localization/interest_point/src/matching.cc | 3 ++- .../include/localization_node/localization.h | 2 ++ localization/localization_node/src/localization.cc | 7 +++++-- 5 files changed, 16 insertions(+), 7 deletions(-) diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index 0b80e8cd01..af1944e352 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -65,9 +65,9 @@ teblid512_use_clahe = true teblid512_num_extra_localization_db_images = 0 -- Detection Params -teblid512_min_threshold = 10.0 +teblid512_min_threshold = 20.0 teblid512_default_threshold = 60.0 -teblid512_max_threshold = 100.0 +teblid512_max_threshold = 110.0 teblid512_min_features = 900 teblid512_max_features = 2000 teblid512_detection_retries = 1 @@ -95,9 +95,9 @@ teblid256_use_clahe = true teblid256_num_extra_localization_db_images = 0 -- Detection Params -teblid256_min_threshold = 10.0 +teblid256_min_threshold = 20.0 teblid256_default_threshold = 60.0 -teblid256_max_threshold = 100.0 +teblid256_max_threshold = 110.0 teblid256_min_features = 900 teblid256_max_features = 2000 teblid256_detection_retries = 1 diff --git a/localization/interest_point/include/interest_point/matching.h b/localization/interest_point/include/interest_point/matching.h index e77b53dc99..21cb10328a 100644 --- a/localization/interest_point/include/interest_point/matching.h +++ b/localization/interest_point/include/interest_point/matching.h @@ -46,9 +46,12 @@ namespace interest_point { void GetDetectorParams(int & min_features, int & max_features, int & max_retries, double & min_thresh, double & default_thresh, double & max_thresh); + int last_keypoint_count(void) { return last_keypoint_count_; } + protected: unsigned int min_features_, max_features_, max_retries_; double min_thresh_, default_thresh_, max_thresh_, dynamic_thresh_; + int last_keypoint_count_; }; class FeatureDetector { diff --git a/localization/interest_point/src/matching.cc b/localization/interest_point/src/matching.cc index 81a7ec6532..6d9d351cf4 100644 --- a/localization/interest_point/src/matching.cc +++ b/localization/interest_point/src/matching.cc @@ -73,7 +73,7 @@ namespace interest_point { double min_thresh, double default_thresh, double max_thresh): min_features_(min_features), max_features_(max_features), max_retries_(max_retries), min_thresh_(min_thresh), default_thresh_(default_thresh), max_thresh_(max_thresh), - dynamic_thresh_(default_thresh) {} + dynamic_thresh_(default_thresh), last_keypoint_count_(0) {} void DynamicDetector::GetDetectorParams(int & min_features, int & max_features, int & max_retries, double & min_thresh, double & default_thresh, @@ -93,6 +93,7 @@ namespace interest_point { for (unsigned int i = 0; i < max_retries_; i++) { keypoints->clear(); DetectImpl(image, keypoints); + last_keypoint_count_ = keypoints->size(); if (keypoints->size() < min_features_) TooFew(); else if (keypoints->size() > max_features_) diff --git a/localization/localization_node/include/localization_node/localization.h b/localization/localization_node/include/localization_node/localization.h index 5042caba3c..fe6852ce98 100644 --- a/localization/localization_node/include/localization_node/localization.h +++ b/localization/localization_node/include/localization_node/localization.h @@ -34,6 +34,8 @@ struct ThresholdParams { int success_history_size; double min_success_rate; double max_success_rate; + int min_features; + int max_features; }; class Localizer { diff --git a/localization/localization_node/src/localization.cc b/localization/localization_node/src/localization.cc index 40b5f019d5..b1a4edfde0 100644 --- a/localization/localization_node/src/localization.cc +++ b/localization/localization_node/src/localization.cc @@ -76,6 +76,8 @@ void Localizer::ReadParams(config_reader::ConfigReader& config) { LOAD_PARAM(params_.success_history_size, config, prefix); LOAD_PARAM(params_.min_success_rate, config, prefix); LOAD_PARAM(params_.max_success_rate, config, prefix); + LOAD_PARAM(params_.min_features, config, prefix); + LOAD_PARAM(params_.max_features, config, prefix); // This check must happen before the histogram_equalization flag is set into the map // to compare with what is there already. @@ -150,10 +152,11 @@ void Localizer::AdjustThresholds() { } const double average = std::accumulate(successes_.cbegin(), successes_.cend(), 0) / static_cast(successes_.size()); - if (average < params_.min_success_rate) { + const int last_keypoint_count = map_->detector().dynamic_detector().last_keypoint_count(); + if (average < params_.min_success_rate && last_keypoint_count < params_.max_features) { map_->detector().dynamic_detector().TooFew(); } - if (average > params_.max_success_rate) { + if (average > params_.max_success_rate && last_keypoint_count > params_.min_features) { map_->detector().dynamic_detector().TooMany(); } } From 7fea5db890d94c23d8d37731d85237a9a21e0d35 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Thu, 27 Jun 2024 09:41:26 -0700 Subject: [PATCH 53/61] updated loc configs --- astrobee/config/localization.config | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index af1944e352..9fa59eed9b 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -68,8 +68,8 @@ teblid512_num_extra_localization_db_images = 0 teblid512_min_threshold = 20.0 teblid512_default_threshold = 60.0 teblid512_max_threshold = 110.0 -teblid512_min_features = 900 -teblid512_max_features = 2000 +teblid512_min_features = 1000 +teblid512_max_features = 3000 teblid512_detection_retries = 1 -- Localizer Threshold Params @@ -98,8 +98,8 @@ teblid256_num_extra_localization_db_images = 0 teblid256_min_threshold = 20.0 teblid256_default_threshold = 60.0 teblid256_max_threshold = 110.0 -teblid256_min_features = 900 -teblid256_max_features = 2000 +teblid256_min_features = 1000 +teblid256_max_features = 3000 teblid256_detection_retries = 1 -- Localizer Threshold Params From 06cfafa3d175d86ba32a470cdb9d07df8f8c0c42 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Thu, 27 Jun 2024 09:56:04 -0700 Subject: [PATCH 54/61] added dynamic hamming distance option --- astrobee/config/localization.config | 10 ++++++- .../include/localization_node/localization.h | 3 +++ .../localization_node/src/localization.cc | 27 ++++++++++++++++--- .../include/sparse_mapping/sparse_map.h | 3 ++- 4 files changed, 37 insertions(+), 6 deletions(-) diff --git a/astrobee/config/localization.config b/astrobee/config/localization.config index 9fa59eed9b..ab46b78f90 100644 --- a/astrobee/config/localization.config +++ b/astrobee/config/localization.config @@ -47,6 +47,9 @@ brisk_detection_retries = 1 brisk_success_history_size = 10 brisk_min_success_rate = 0 brisk_max_success_rate = 1 +brisk_adjust_hamming_distance = false +brisk_min_hamming_distance = 90 +brisk_max_hamming_distance = 90 -- TEBLID512 teblid512_num_similar = 20 @@ -76,7 +79,9 @@ teblid512_detection_retries = 1 teblid512_success_history_size = 10 teblid512_min_success_rate = 0.3 teblid512_max_success_rate = 0.9 - +teblid512_adjust_hamming_distance = false +teblid512_min_hamming_distance = 85 +teblid512_max_hamming_distance = 85 -- TEBLID256 teblid256_num_similar = 20 @@ -106,3 +111,6 @@ teblid256_detection_retries = 1 teblid256_success_history_size = 10 teblid256_min_success_rate = 0.3 teblid256_max_success_rate = 0.9 +teblid256_adjust_hamming_distance = false +teblid256_min_hamming_distance = 85 +teblid256_max_hamming_distance = 85 diff --git a/localization/localization_node/include/localization_node/localization.h b/localization/localization_node/include/localization_node/localization.h index fe6852ce98..d4a0837f45 100644 --- a/localization/localization_node/include/localization_node/localization.h +++ b/localization/localization_node/include/localization_node/localization.h @@ -36,6 +36,9 @@ struct ThresholdParams { double max_success_rate; int min_features; int max_features; + bool adjust_hamming_distance; + int min_hamming_distance; + int max_hamming_distance; }; class Localizer { diff --git a/localization/localization_node/src/localization.cc b/localization/localization_node/src/localization.cc index b1a4edfde0..574fc5c614 100644 --- a/localization/localization_node/src/localization.cc +++ b/localization/localization_node/src/localization.cc @@ -78,6 +78,9 @@ void Localizer::ReadParams(config_reader::ConfigReader& config) { LOAD_PARAM(params_.max_success_rate, config, prefix); LOAD_PARAM(params_.min_features, config, prefix); LOAD_PARAM(params_.max_features, config, prefix); + LOAD_PARAM(params_.adjust_hamming_distance, config, prefix); + LOAD_PARAM(params_.min_hamming_distance, config, prefix); + LOAD_PARAM(params_.max_hamming_distance, config, prefix); // This check must happen before the histogram_equalization flag is set into the map // to compare with what is there already. @@ -153,11 +156,27 @@ void Localizer::AdjustThresholds() { const double average = std::accumulate(successes_.cbegin(), successes_.cend(), 0) / static_cast(successes_.size()); const int last_keypoint_count = map_->detector().dynamic_detector().last_keypoint_count(); - if (average < params_.min_success_rate && last_keypoint_count < params_.max_features) { - map_->detector().dynamic_detector().TooFew(); + if (average < params_.min_success_rate) { + if (last_keypoint_count < params_.max_features) { + map_->detector().dynamic_detector().TooFew(); + } else if (params_.adjust_hamming_distance) { + const int current_hamming_distance = map_->loc_params().hamming_distance; + const int new_hamming_distance = current_hamming_distance + 3; + if (new_hamming_distance <= params_.max_hamming_distance) { + map_->loc_params().hamming_distance = new_hamming_distance; + } + } } - if (average > params_.max_success_rate && last_keypoint_count > params_.min_features) { - map_->detector().dynamic_detector().TooMany(); + if (average > params_.max_success_rate) { + if (last_keypoint_count > params_.min_features) { + map_->detector().dynamic_detector().TooMany(); + } else if (params_.adjust_hamming_distance) { + const int current_hamming_distance = map_->loc_params().hamming_distance; + const int new_hamming_distance = current_hamming_distance - 3; + if (new_hamming_distance >= params_.min_hamming_distance) { + map_->loc_params().hamming_distance = new_hamming_distance; + } + } } } } // namespace localization_node diff --git a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h index 6b88ab8d94..c33d588d9e 100644 --- a/localization/sparse_mapping/include/sparse_mapping/sparse_map.h +++ b/localization/sparse_mapping/include/sparse_mapping/sparse_map.h @@ -96,6 +96,8 @@ struct SparseMap { // Set loc params void SetLocParams(const LocalizationParameters& loc_params); + const LocalizationParameters& loc_params() const { return loc_params_; } + LocalizationParameters& loc_params() { return loc_params_; } void SetDetectorParams(int min_features, int max_features, int retries, double min_thresh, double default_thresh, double max_thresh); @@ -223,7 +225,6 @@ struct SparseMap { std::string GetDetectorName() { return detector_.GetDetectorName(); } interest_point::FeatureDetector& detector() { return detector_; } int GetHistogramEqualization() {return loc_params_.histogram_equalization;} - const LocalizationParameters& loc_params() { return loc_params_; } // stored in map file std::vector cid_to_filename_; From 29ef6ec02d9ef9ecf0653030b06fffd071d406f4 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Fri, 28 Jun 2024 14:55:28 -0700 Subject: [PATCH 55/61] some test fixes --- localization/sparse_mapping/test/test_build_db.cc | 4 ++-- localization/sparse_mapping/test/test_registration.cc | 4 ++-- localization/sparse_mapping/test/test_sparse_map.cc | 2 +- 3 files changed, 5 insertions(+), 5 deletions(-) diff --git a/localization/sparse_mapping/test/test_build_db.cc b/localization/sparse_mapping/test/test_build_db.cc index 1ea65875f4..d27ec3276c 100644 --- a/localization/sparse_mapping/test/test_build_db.cc +++ b/localization/sparse_mapping/test/test_build_db.cc @@ -80,7 +80,7 @@ void RunWithDB(std::string const& detector_name) { int num_similar = 6; std::string out_nvm = "output.nvm"; sparse_mapping::SparseMap map(features_out); - map.SetNumSimilar(num_similar); + map.loc_params().num_similar = num_similar; EXPECT_EQ(static_cast(map.vocab_db_.m_num_nodes), 3); map.DetectFeatures(); std::string essential_file = "essential.csv"; @@ -105,7 +105,7 @@ void RunWithDB(std::string const& detector_name) { // Localize features with database. sparse_mapping::SparseMap map2(out_nvm); - map2.SetNumSimilar(num_similar); + map2.loc_params().num_similar = num_similar; LOG(INFO) << "\n\n================================================\n"; LOG(INFO) << "\nLocalizing using the database\n"; diff --git a/localization/sparse_mapping/test/test_registration.cc b/localization/sparse_mapping/test/test_registration.cc index 386e9fb19d..21a348625c 100644 --- a/localization/sparse_mapping/test/test_registration.cc +++ b/localization/sparse_mapping/test/test_registration.cc @@ -103,8 +103,8 @@ class SparseMapTest : public ::testing::Test { EXPECT_GT(surf_map->GetNumLandmarks(), 30u); // should probably do some sanity check on the landmarks... - EXPECT_EQ(surf_map->GetRansacIterations(), 1000); - EXPECT_EQ(surf_map->GetRansacInlierTolerance(), 3); + EXPECT_EQ(surf_map->loc_params().num_ransac_iterations, 1000); + EXPECT_EQ(surf_map->loc_params().ransac_inlier_tolerance, 3); EXPECT_NEAR(surf_map->GetCameraParameters().GetFocalLength(), 258.5, 1e-5); } diff --git a/localization/sparse_mapping/test/test_sparse_map.cc b/localization/sparse_mapping/test/test_sparse_map.cc index f3089b402b..7b08f7122d 100644 --- a/localization/sparse_mapping/test/test_sparse_map.cc +++ b/localization/sparse_mapping/test/test_sparse_map.cc @@ -172,7 +172,7 @@ TEST_P(SparseMapTest, MapBuilding) { } } EXPECT_GT(map_loopback.GetNumLandmarks(), 30u); - EXPECT_EQ(map_loopback.GetRansacInlierTolerance(), 3); + EXPECT_EQ(map_loopback.loc_params().ransac_inlier_tolerance, 3); EXPECT_NEAR(map_loopback.GetCameraParameters().GetFocalLength(), 258.5, 1e-5); // Test Map Consistency? From 1fcaa8c459e9de5c4373da66a8f07964af4c3355 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Fri, 28 Jun 2024 15:17:55 -0700 Subject: [PATCH 56/61] more sparse map test fixes --- localization/sparse_mapping/src/sparse_map.cc | 1 + localization/sparse_mapping/test/test_build_db.cc | 4 ++++ 2 files changed, 5 insertions(+) diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index 1fa90dadf4..4fe223c475 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -750,6 +750,7 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const indices.push_back(cid); } + LOG(ERROR) << "Test!"; if (loc_params_.add_best_previous_image && best_previous_cid_) { bool add_cid = true; for (const auto cid : indices) { diff --git a/localization/sparse_mapping/test/test_build_db.cc b/localization/sparse_mapping/test/test_build_db.cc index d27ec3276c..48f52e61ef 100644 --- a/localization/sparse_mapping/test/test_build_db.cc +++ b/localization/sparse_mapping/test/test_build_db.cc @@ -110,7 +110,11 @@ void RunWithDB(std::string const& detector_name) { LOG(INFO) << "\nLocalizing using the database\n"; camera::CameraModel camera(Eigen::Vector3d(), Eigen::Matrix3d::Identity(), camera_params); + std::string img_file = data_dir + "/m0004033.jpg"; + map2.loc_params().check_essential_matrix = false; + map2.loc_params().add_similar_images = false; + map2.loc_params().add_best_previous_image = false; EXPECT_TRUE(map2.Localize(img_file, &camera)); Eigen::Affine3d closest = map2.GetFrameGlobalTransform(1); From 1e05d860fe006233d83c89f5bd7d3f6f11f6679b Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Fri, 28 Jun 2024 15:55:27 -0700 Subject: [PATCH 57/61] fixed test db --- localization/sparse_mapping/test/test_build_db.cc | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/localization/sparse_mapping/test/test_build_db.cc b/localization/sparse_mapping/test/test_build_db.cc index 48f52e61ef..2315b270e0 100644 --- a/localization/sparse_mapping/test/test_build_db.cc +++ b/localization/sparse_mapping/test/test_build_db.cc @@ -115,7 +115,9 @@ void RunWithDB(std::string const& detector_name) { map2.loc_params().check_essential_matrix = false; map2.loc_params().add_similar_images = false; map2.loc_params().add_best_previous_image = false; - EXPECT_TRUE(map2.Localize(img_file, &camera)); + map2.loc_params().goodness_ratio = 100000; + map2.loc_params().hamming_distance = 90; + ASSERT_TRUE(map2.Localize(img_file, &camera)); Eigen::Affine3d closest = map2.GetFrameGlobalTransform(1); Eigen::Affine3d closest2 = map2.GetFrameGlobalTransform(2); From ad8fd0d3d02c2f4724b376c3756d130be5f74219 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Fri, 28 Jun 2024 16:30:41 -0700 Subject: [PATCH 58/61] more test fixes --- localization/sparse_mapping/src/sparse_map.cc | 15 +++++++++++++-- .../sparse_mapping/test/test_sparse_map.cc | 3 +++ 2 files changed, 16 insertions(+), 2 deletions(-) diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index 4fe223c475..a54073dfe8 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -50,6 +50,10 @@ DEFINE_int32(num_similar, 20, "Use in localization this many images which " "are most similar to the image to localize."); +DEFINE_double(min_query_score_ratio, 0, + "Use in localization as a threshold for including " + "db images. Min ratio between best query and current query" + "db image scores for a map image to be matched with."); DEFINE_int32(num_ransac_iterations, 1000, "Use in localization this many ransac iterations."); DEFINE_int32(ransac_inlier_tolerance, 3, @@ -58,6 +62,10 @@ DEFINE_int32(early_break_landmarks, 100, "Break early when we have this many landmarks during localization."); DEFINE_bool(histogram_equalization, false, "If true, equalize the histogram for images to improve robustness to illumination conditions."); +DEFINE_int32(localization_hamming_distance, 85, + "Used for localization. A smaller value keeps fewer but more reliable binary descriptor matches."); +DEFINE_double(localization_goodness_ratio, 0.8, + "Used for localization. A smaller value keeps fewer but more reliable descriptor matches."); DEFINE_bool(use_clahe, false, "If true, use CLAHE if histogram equalization enabled."); DEFINE_int32(num_extra_localization_db_images, 0, @@ -232,6 +240,7 @@ SparseMap::SparseMap(bool bundler_format, std::string const& filename, std::vect void SparseMap::SetDefaultLocParams() { loc_params_.num_similar = FLAGS_num_similar; + loc_params_.min_query_score_ratio = FLAGS_min_query_score_ratio; loc_params_.num_ransac_iterations = FLAGS_num_ransac_iterations; loc_params_.ransac_inlier_tolerance = FLAGS_ransac_inlier_tolerance; loc_params_.early_break_landmarks = FLAGS_early_break_landmarks; @@ -240,6 +249,8 @@ void SparseMap::SetDefaultLocParams() { loc_params_.check_essential_matrix = FLAGS_localization_check_essential_matrix; loc_params_.add_similar_images = FLAGS_localization_add_similar_images; loc_params_.add_best_previous_image = FLAGS_localization_add_best_previous_image; + loc_params_.hamming_distance = FLAGS_localization_hamming_distance; + loc_params_.goodness_ratio = FLAGS_localization_goodness_ratio; loc_params_.num_extra_localization_db_images = FLAGS_num_extra_localization_db_images; loc_params_.verbose_localization = FLAGS_verbose_localization; loc_params_.visualize_localization_matches = FLAGS_visualize_localization_matches; @@ -750,7 +761,6 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const indices.push_back(cid); } - LOG(ERROR) << "Test!"; if (loc_params_.add_best_previous_image && best_previous_cid_) { bool add_cid = true; for (const auto cid : indices) { @@ -790,7 +800,8 @@ bool SparseMap::Localize(cv::Mat const& test_descriptors, Eigen::Matrix2Xd const if (loc_params_.verbose_localization) std::cout << "Checking index: " << i << ", cid: " << cid << std::endl; similarity_rank.emplace_back(0); all_matches.emplace_back(std::vector()); - if (query_scores[i]/ static_cast(query_scores[0]) < loc_params_.min_query_score_ratio) { + if (!query_scores.empty() && query_scores[0] != 0 && + query_scores[i] / static_cast(query_scores[0]) < loc_params_.min_query_score_ratio) { if (loc_params_.verbose_localization) std::cout << "Query score ratio too low: " << query_scores[i] / static_cast(query_scores[0]) << std::endl; diff --git a/localization/sparse_mapping/test/test_sparse_map.cc b/localization/sparse_mapping/test/test_sparse_map.cc index 7b08f7122d..ef130311d3 100644 --- a/localization/sparse_mapping/test/test_sparse_map.cc +++ b/localization/sparse_mapping/test/test_sparse_map.cc @@ -178,6 +178,9 @@ TEST_P(SparseMapTest, MapBuilding) { // Test Map Consistency? // check that each frame localizes to its own position camera::CameraModel guess(map_loopback.GetCameraParameters()); + map_loopback.loc_params().check_essential_matrix = false; + map_loopback.loc_params().add_similar_images = false; + map_loopback.loc_params().add_best_previous_image = false; for (size_t i = 0; i < map_loopback.GetNumFrames(); i++) { Eigen::Affine3d transform = map_loopback.GetFrameGlobalTransform(i); EXPECT_TRUE(map_loopback.Localize(map_loopback.GetFrameFilename(i), &guess)); From 0014e89c0b57dea6f422cb40863475a987899644 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Fri, 28 Jun 2024 16:58:27 -0700 Subject: [PATCH 59/61] added enum for hist equalization type, added more info to bad headers --- .../include/interest_point/BAD.h | 5 + .../include/sparse_mapping/sparse_mapping.h | 289 ++++++++---------- localization/sparse_mapping/src/sparse_map.cc | 12 +- .../sparse_mapping/src/sparse_mapping.cc | 3 +- 4 files changed, 138 insertions(+), 171 deletions(-) diff --git a/localization/interest_point/include/interest_point/BAD.h b/localization/interest_point/include/interest_point/BAD.h index 21ab65c7af..8cf3ae96aa 100644 --- a/localization/interest_point/include/interest_point/BAD.h +++ b/localization/interest_point/include/interest_point/BAD.h @@ -2,7 +2,12 @@ * @copyright 2021 Xoan Iago Suarez Canosa. All rights reserved. * Constact: iago.suarez@thegraffter.com * Software developed in the PhD: Low-level vision for resource-limited devices + * Repo link: https://github.com/iago-suarez/efficient-descriptors + * License: Apache 2 + * TODO(rsoussan): Remove this and BAD.cpp and switch to opencv TEBLID if opencv + * version upgraded. */ + #ifndef INTEREST_POINT_BAD_H_ #define INTEREST_POINT_BAD_H_ diff --git a/localization/sparse_mapping/include/sparse_mapping/sparse_mapping.h b/localization/sparse_mapping/include/sparse_mapping/sparse_mapping.h index f4c5f80fd6..f573acc273 100644 --- a/localization/sparse_mapping/include/sparse_mapping/sparse_mapping.h +++ b/localization/sparse_mapping/include/sparse_mapping/sparse_mapping.h @@ -69,172 +69,135 @@ namespace sparse_mapping { // cid_to_camera_transform - Index on CID. Contains affine transform // representing camera_t_global. - Eigen::Quaternion slerp_n(std::vector const& W, - std::vector > const& Q); - - bool IsBinaryDescriptor(std::string const& descriptor); - - // Logic for implementing if two histogram equalization flags are compatible - void HistogramEqualizationCheck(int histogram_equalization1, int histogram_equalization2); - - // Writes the NVM control network format. - void WriteNVM(std::vector const& cid_to_keypoint_map, - std::vector const& cid_to_filename, - std::vector > const& pid_to_cid_fid, - std::vector const& pid_to_xyz, - std::vector const& cid_to_cam_t_global, - double focal_length, - std::string const& output_filename); - // Reads the NVM control network format. - void ReadNVM(std::string const& input_filename, - std::vector * cid_to_keypoint_map, - std::vector * cid_to_filename, - std::vector > * pid_to_cid_fid, - std::vector * pid_to_xyz, - std::vector * cid_to_cam_t_global); - - // Adds yaml.gz or .txt extension, depending on descriptor - std::string ImageToFeatureFile(std::string const& image_file, - std::string const& detector_name); - - // The name of the file storing the list of images - std::string DBImagesFile(std::string const& db_name); - - // The name of the matches file - std::string MatchesFile(std::string const& map_file); - - // The name of the essential file - std::string EssentialFile(std::string const& map_file); - - // Write features yaml file - void WriteFeatures(std::string const& detector_name, - std::vector const& keypoints, - cv::Mat const& descriptors, - std::string const& output_filename); - - // Read features yaml file - bool ReadFeatures(std::string const& input_filename, - std::string const& detector_name, - std::vector * keypoints, - cv::Mat * descriptors); - - // Read SIFT features in Lowe's format - int ReadFeaturesSIFT(std::string const& filename, - cv::Mat * descriptors, - std::vector * keypoints); - - // Triangulate metric camera point - // unnormalized point means that the point is: - // [px (image loc) - cx (optical center), py - cy, f (f length in px)] - Eigen::Vector3d - TriangulatePoint(Eigen::Vector3d const& unnormalized_pt1, - Eigen::Vector3d const& unnormalized_pt2, - Eigen::Matrix3d const& cam2_r_cam1, - Eigen::Vector3d const& cam2_t_cam1, - double* error); - - // Decompose Fundamental Matrix into Essential Matrix given known - // Intrinsics Matrix. - void DecomposeFMatIntoEMat(Eigen::Matrix3d const& fundamental, - Eigen::Matrix3d const& intrinsics, - Eigen::Matrix3d * essential); - - // Decompose Essential Matrix into R and T - void DecomposeEMatIntoRT(Eigen::Matrix3d const& essential, - Eigen::Matrix2Xd const& unnormalized_pts1, - Eigen::Matrix2Xd const& unnormalized_pts2, - std::vector const& matches, - double focal_length1, // Camera 1 - double focal_length2, // Camera 2 - Eigen::Matrix3d * cam2_r_cam1, - Eigen::Vector3d * cam2_t_cam1); - - // Utility to return the type of entries in a given matrix - std::string CvMatTypeStr(cv::Mat const& Mat); - - void ListToListMap(std::vector const& big_list, - std::vector const& small_list, - std::map * map); - - void MergePids(int repeat_index, int num_unique, - std::vector > * pid_to_cid_fid); - - void PrintPidStats(std::vector > const& pid_to_cid_fid); - - // Extract control points and the images they correspond to from - // a hugin project file - void ParseHuginControlPoints(std::string const& hugin_file, - std::vector * images, - Eigen::MatrixXd * points); - - // Parse a file having on each line xyz coordinates - void ParseXYZ(std::string const& xyz_file, Eigen::MatrixXd * xyz); - - // Parse a CSV file, with the first line having column names. Return - // the results as columns in an std::map, with the column name being - // the key. We assume all values are numbers (non-numbers are set to - // 0). - void ParseCSV(std::string const& csv_file, - std::map< std::string, std::vector > *cols); - - // save size before protbuf, to save multiple protobufs in one file - bool WriteProtobufTo(const google::protobuf::MessageLite& message, - google::protobuf::io::ZeroCopyOutputStream* rawOutput); +enum HistogramEqualizationType { kNone = 0, kEqualizeHist = 1, kUnknown = 2, kCLAHE = 3 }; + +Eigen::Quaternion slerp_n(std::vector const& W, std::vector > const& Q); + +bool IsBinaryDescriptor(std::string const& descriptor); + +// Logic for implementing if two histogram equalization flags are compatible +void HistogramEqualizationCheck(int histogram_equalization1, int histogram_equalization2); + +// Writes the NVM control network format. +void WriteNVM(std::vector const& cid_to_keypoint_map, std::vector const& cid_to_filename, + std::vector > const& pid_to_cid_fid, std::vector const& pid_to_xyz, + std::vector const& cid_to_cam_t_global, double focal_length, + std::string const& output_filename); +// Reads the NVM control network format. +void ReadNVM(std::string const& input_filename, std::vector* cid_to_keypoint_map, + std::vector* cid_to_filename, std::vector >* pid_to_cid_fid, + std::vector* pid_to_xyz, std::vector* cid_to_cam_t_global); + +// Adds yaml.gz or .txt extension, depending on descriptor +std::string ImageToFeatureFile(std::string const& image_file, std::string const& detector_name); + +// The name of the file storing the list of images +std::string DBImagesFile(std::string const& db_name); + +// The name of the matches file +std::string MatchesFile(std::string const& map_file); + +// The name of the essential file +std::string EssentialFile(std::string const& map_file); + +// Write features yaml file +void WriteFeatures(std::string const& detector_name, std::vector const& keypoints, + cv::Mat const& descriptors, std::string const& output_filename); + +// Read features yaml file +bool ReadFeatures(std::string const& input_filename, std::string const& detector_name, + std::vector* keypoints, cv::Mat* descriptors); + +// Read SIFT features in Lowe's format +int ReadFeaturesSIFT(std::string const& filename, cv::Mat* descriptors, std::vector* keypoints); + +// Triangulate metric camera point +// unnormalized point means that the point is: +// [px (image loc) - cx (optical center), py - cy, f (f length in px)] +Eigen::Vector3d TriangulatePoint(Eigen::Vector3d const& unnormalized_pt1, Eigen::Vector3d const& unnormalized_pt2, + Eigen::Matrix3d const& cam2_r_cam1, Eigen::Vector3d const& cam2_t_cam1, double* error); + +// Decompose Fundamental Matrix into Essential Matrix given known +// Intrinsics Matrix. +void DecomposeFMatIntoEMat(Eigen::Matrix3d const& fundamental, Eigen::Matrix3d const& intrinsics, + Eigen::Matrix3d* essential); + +// Decompose Essential Matrix into R and T +void DecomposeEMatIntoRT(Eigen::Matrix3d const& essential, Eigen::Matrix2Xd const& unnormalized_pts1, + Eigen::Matrix2Xd const& unnormalized_pts2, std::vector const& matches, + double focal_length1, // Camera 1 + double focal_length2, // Camera 2 + Eigen::Matrix3d* cam2_r_cam1, Eigen::Vector3d* cam2_t_cam1); + +// Utility to return the type of entries in a given matrix +std::string CvMatTypeStr(cv::Mat const& Mat); + +void ListToListMap(std::vector const& big_list, std::vector const& small_list, + std::map* map); + +void MergePids(int repeat_index, int num_unique, std::vector >* pid_to_cid_fid); + +void PrintPidStats(std::vector > const& pid_to_cid_fid); + +// Extract control points and the images they correspond to from +// a hugin project file +void ParseHuginControlPoints(std::string const& hugin_file, std::vector* images, Eigen::MatrixXd* points); + +// Parse a file having on each line xyz coordinates +void ParseXYZ(std::string const& xyz_file, Eigen::MatrixXd* xyz); + +// Parse a CSV file, with the first line having column names. Return +// the results as columns in an std::map, with the column name being +// the key. We assume all values are numbers (non-numbers are set to +// 0). +void ParseCSV(std::string const& csv_file, std::map >* cols); - // save size before file, then write file into rawOutput - bool WriteFileTo(const char* filename, +// save size before protbuf, to save multiple protobufs in one file +bool WriteProtobufTo(const google::protobuf::MessageLite& message, google::protobuf::io::ZeroCopyOutputStream* rawOutput); - // read size before protbuf, to save multiple protobufs in one file - bool ReadProtobufFrom(google::protobuf::io::ZeroCopyInputStream* rawInput, - google::protobuf::MessageLite* message); - - // read a size before protobuf, then read a file and write it to filename - bool ReadFileFrom(google::protobuf::io::ZeroCopyInputStream* rawInput, const char* filename); - - // Apply a given transform to the specified xyz points, and adjust - // accordingly the cameras for consistency. - void TransformCamerasAndPoints(Eigen::Affine3d const& A, - std::vector *cid_to_cam_t, - std::vector *xyz); - - // Get the error threshold based on a multiple of a percentile - double GetErrThresh(const std::vector & errors, double factor); - - // Find the maximum angle between n rays intersecting at given - // point. Must compute the camera centers in the global coordinate - // system before calling this function. - double ComputeRaysAngle(int pid, - std::vector > const& pid_to_cid_fid, - std::vector const & cam_ctrs, - std::vector const& pid_to_xyz); - - // Filter points by reprojection error and other criteria - void FilterPID(double reproj_thresh, - camera::CameraParameters const& camera_params, - std::vector const& cid_to_cam_t_global, - std::vector const& cid_to_keypoint_map, - std::vector > * pid_to_cid_fid, - std::vector * pid_to_xyz, - bool print_stats = true, double multiple_of_median = 3.0); - - // Write the BAL format. - bool WriteBAL(const std::string& filename, - camera::CameraParameters const& camera_params, - std::vector > const& pid_to_cid_fid, - std::vector const& pid_to_xyz, - std::vector const& cid_to_cam_t_global, - std::vector const& cid_to_keypoint_map); - - // Given a data sequence having camera pose information for - // a set of timestamps, interpolate those poses at the timestamps - // given in out_time. We assume timestamps are always in increasing values. - void PoseInterpolation(std::vector const& images, - std::vector const& out_time, - std::map< std::string, std::vector > - const& data, - std::vector * cid_to_cam_t, - std::vector * good_images); +// save size before file, then write file into rawOutput +bool WriteFileTo(const char* filename, google::protobuf::io::ZeroCopyOutputStream* rawOutput); + +// read size before protbuf, to save multiple protobufs in one file +bool ReadProtobufFrom(google::protobuf::io::ZeroCopyInputStream* rawInput, google::protobuf::MessageLite* message); + +// read a size before protobuf, then read a file and write it to filename +bool ReadFileFrom(google::protobuf::io::ZeroCopyInputStream* rawInput, const char* filename); + +// Apply a given transform to the specified xyz points, and adjust +// accordingly the cameras for consistency. +void TransformCamerasAndPoints(Eigen::Affine3d const& A, std::vector* cid_to_cam_t, + std::vector* xyz); + +// Get the error threshold based on a multiple of a percentile +double GetErrThresh(const std::vector& errors, double factor); + +// Find the maximum angle between n rays intersecting at given +// point. Must compute the camera centers in the global coordinate +// system before calling this function. +double ComputeRaysAngle(int pid, std::vector > const& pid_to_cid_fid, + std::vector const& cam_ctrs, std::vector const& pid_to_xyz); + +// Filter points by reprojection error and other criteria +void FilterPID(double reproj_thresh, camera::CameraParameters const& camera_params, + std::vector const& cid_to_cam_t_global, + std::vector const& cid_to_keypoint_map, + std::vector >* pid_to_cid_fid, std::vector* pid_to_xyz, + bool print_stats = true, double multiple_of_median = 3.0); + +// Write the BAL format. +bool WriteBAL(const std::string& filename, camera::CameraParameters const& camera_params, + std::vector > const& pid_to_cid_fid, std::vector const& pid_to_xyz, + std::vector const& cid_to_cam_t_global, + std::vector const& cid_to_keypoint_map); + +// Given a data sequence having camera pose information for +// a set of timestamps, interpolate those poses at the timestamps +// given in out_time. We assume timestamps are always in increasing values. +void PoseInterpolation(std::vector const& images, std::vector const& out_time, + std::map > const& data, + std::vector* cid_to_cam_t, std::vector* good_images); } // namespace sparse_mapping diff --git a/localization/sparse_mapping/src/sparse_map.cc b/localization/sparse_mapping/src/sparse_map.cc index a54073dfe8..1325929338 100644 --- a/localization/sparse_mapping/src/sparse_map.cc +++ b/localization/sparse_mapping/src/sparse_map.cc @@ -256,7 +256,7 @@ void SparseMap::SetDefaultLocParams() { loc_params_.visualize_localization_matches = FLAGS_visualize_localization_matches; if (loc_params_.histogram_equalization && loc_params_.use_clahe) { clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); - loc_params_.histogram_equalization = 3; + loc_params_.histogram_equalization = HistogramEqualizationType::kCLAHE; } } @@ -455,16 +455,14 @@ void SparseMap::Load(const std::string & protobuf_file, bool localization) { loc_params_.histogram_equalization = map.histogram_equalization(); - assert(loc_params_.histogram_equalization == 0 || loc_params_.histogram_equalization == 1 || - loc_params_.histogram_equalization == 2 || loc_params_.histogram_equalization == 3); - - loc_params_.use_clahe = loc_params_.histogram_equalization == 3 ? true : false; + assert(loc_params_.histogram_equalization >=0 && loc_params_.histogram_equalization <= 3); + loc_params_.use_clahe = loc_params_.histogram_equalization == HistogramEqualizationType::kCLAHE ? true : false; if (loc_params_.use_clahe) clahe_ = cv::createCLAHE(2, cv::Size(8, 8)); // For backward compatibility with old maps, allow a map to have its // histogram_equalization flag unspecified, but it is best to avoid // that situation, and rebuild the map if necessary. - if (loc_params_.histogram_equalization == 2) + if (loc_params_.histogram_equalization == HistogramEqualizationType::kUnknown) std::cout << "Warning: Unknown value of histogram_equalization! " << "It is strongly suggested to rebuild this map to avoid " << "poor quality results." << std::endl; @@ -520,7 +518,7 @@ void SparseMap::Save(const std::string & protobuf_file) const { // For backward compatibility with old maps, allow a map to have its // histogram_equalization flag unspecified, but it is best to avoid // that situation, and rebuild the map if necessary. - if (loc_params_.histogram_equalization == 2) + if (loc_params_.histogram_equalization == HistogramEqualizationType::kUnknown) std::cout << "Warning: Unknown value of histogram_equalization! " << "It is strongly suggested to rebuild this map to avoid " << "poor quality results." << std::endl; diff --git a/localization/sparse_mapping/src/sparse_mapping.cc b/localization/sparse_mapping/src/sparse_mapping.cc index a3590c18b7..94642e2150 100644 --- a/localization/sparse_mapping/src/sparse_mapping.cc +++ b/localization/sparse_mapping/src/sparse_mapping.cc @@ -118,7 +118,8 @@ namespace sparse_mapping { void sparse_mapping::HistogramEqualizationCheck(int histogram_equalization1, int histogram_equalization2) { // Ignore if either has unknown equalization value - if (histogram_equalization1 == 2 || histogram_equalization2 == 2) { + if (histogram_equalization1 == HistogramEqualizationType::kUnknown || + histogram_equalization2 == HistogramEqualizationType::kUnknown) { return; } else if (histogram_equalization1 != histogram_equalization2) { LOG(FATAL) << "Incompatible values of histogram equalization detected."; From 7e9aeacd27859e14b4a736e604e8c7e041ca1d52 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Fri, 28 Jun 2024 17:10:47 -0700 Subject: [PATCH 60/61] updated loc analysis scripts to use teblid --- .../scripts/make_groundtruth.py | 2 +- .../localization_analysis/scripts/make_map.py | 27 ++++++++++--------- 2 files changed, 15 insertions(+), 14 deletions(-) diff --git a/tools/localization_analysis/scripts/make_groundtruth.py b/tools/localization_analysis/scripts/make_groundtruth.py index fa93646649..5d2274f71b 100755 --- a/tools/localization_analysis/scripts/make_groundtruth.py +++ b/tools/localization_analysis/scripts/make_groundtruth.py @@ -116,7 +116,7 @@ ) groundtruth_bag = map_name + ".bag" - groundtruth_map_file = map_name + ".brisk.vocabdb.map" + groundtruth_map_file = map_name + ".teblid512.vocabdb.map" groundtruth_pdf = "groundtruth.pdf" groundtruth_csv = "groundtruth.csv" make_groundtruth_command = ( diff --git a/tools/localization_analysis/scripts/make_map.py b/tools/localization_analysis/scripts/make_map.py index 437233d476..ede8dd16f7 100755 --- a/tools/localization_analysis/scripts/make_map.py +++ b/tools/localization_analysis/scripts/make_map.py @@ -89,7 +89,7 @@ def make_map( lu.run_command_and_save_output(merge_map_command, "merge_map.txt") bag_surf_map = merged_surf_map - # Link maps directory since conversion to BRISK map needs + # Link maps directory since conversion to TEBLID512 map needs # image files to appear to be in correct relative path build_map_command = ( "rosrun sparse_mapping build_map -info -output_map " + base_surf_map @@ -122,32 +122,33 @@ def make_map( os.symlink(bag_images, merged_bag_images) linked_map_images = True - # Convert SURF to BRISK map + # Convert SURF to TEBLID512 map # Get full path to output file to avoid permission errors when running # command in maps directory - rebuild_output_file = os.path.join(os.getcwd(), "rebuild_map_as_brisk_map.txt") - bag_brisk_map = map_name + ".brisk.map" - shutil.copyfile(bag_surf_map, bag_brisk_map) - bag_brisk_map_full_path = os.path.abspath(bag_brisk_map) + rebuild_output_file = os.path.join(os.getcwd(), "rebuild_map_as_teblid512_map.txt") + bag_teblid512_map = map_name + ".teblid512.map" + shutil.copyfile(bag_surf_map, bag_teblid512_map) + bag_teblid512_map_full_path = os.path.abspath(bag_teblid512_map) bag_path = os.getcwd() if merge_with_base_map: os.chdir("maps") rebuild_map_command = ( - "rosrun sparse_mapping build_map -rebuild -output_map " - + bag_brisk_map_full_path + "rosrun sparse_mapping build_map -rebuild -rebuild_detector TEBLID512 -output_map " + + bag_teblid512_map_full_path ) if histogram_equalization: - rebuild_map_command += " -histogram_equalization" + rebuild_map_command += " -histogram_equalization -use_clahe " lu.run_command_and_save_output(rebuild_map_command, rebuild_output_file) # Use bag_path since relative commands would now be wrt maps directory simlink if merge_with_base_map: os.chdir(bag_path) # Create vocabdb - bag_brisk_vocabdb_map = map_name + ".brisk.vocabdb.map" - shutil.copyfile(bag_brisk_map, bag_brisk_vocabdb_map) + bag_teblid512_vocabdb_map = map_name + ".teblid512.vocabdb.map" + shutil.copyfile(bag_teblid512_map, bag_teblid512_vocabdb_map) add_vocabdb_command = ( - "rosrun sparse_mapping build_map -vocab_db -output_map " + bag_brisk_vocabdb_map + "rosrun sparse_mapping build_map -vocab_db -output_map " + + bag_teblid512_vocabdb_map ) lu.run_command_and_save_output(add_vocabdb_command, "build_vocabdb.txt") @@ -192,7 +193,7 @@ def make_map( "--no-histogram_equalization", dest="histogram_equalization", action="store_false", - help="Do not apply histrogram equalization during map creation. Default behavior uses histogram equalization.", + help="Do not apply histrogram equalization during map creation. Default behavior uses histogram equalization using CLAHE.", ) parser.set_defaults(histogram_equalization=True) From bf1e0fb98be6c28781eaaa34d5d67e61601d8d41 Mon Sep 17 00:00:00 2001 From: Ryan Soussan Date: Fri, 28 Jun 2024 17:13:37 -0700 Subject: [PATCH 61/61] converted make brisk map to make teblid map --- .../build_map_from_multiple_bags.md | 8 ++-- ...ake_brisk_map.py => make_teblid512_map.py} | 38 ++++++++++--------- 2 files changed, 24 insertions(+), 22 deletions(-) rename localization/sparse_mapping/scripts/{make_brisk_map.py => make_teblid512_map.py} (72%) diff --git a/localization/sparse_mapping/build_map_from_multiple_bags.md b/localization/sparse_mapping/build_map_from_multiple_bags.md index 8352389a3c..7659a23c1e 100644 --- a/localization/sparse_mapping/build_map_from_multiple_bags.md +++ b/localization/sparse_mapping/build_map_from_multiple_bags.md @@ -51,13 +51,13 @@ First copy the map that should be registered then run: The creation of registration points is detailed in `build_map.md`, images from the map are used to manually select feature locations and 3D points for these features are selected using a 3D model of the mapped environment provided externally. -### 6. Build BRISK map for localization +### 6. Build TEBLID512 map for localization Use: -`rosrun sparse_mapping make_brisk_map.py surf_map_name -r robot_name -w world_name -d map_directory` -to rebuild the SURF map with BRISK features for use with localization. +`rosrun sparse_mapping make_teblid512_map.py surf_map_name -r robot_name -w world_name -d map_directory` +to rebuild the SURF map with TEBLID512 features for use with localization. -### 7. Verify BRISK map using localization +### 7. Verify TEBLID512 map using localization Use: `rosrun sparse_mapping run_graph_bag_and_plot_results bag_name brisk_map_name config_path --generate-image-features -r robot_config -w world_name` to test the map using localization. diff --git a/localization/sparse_mapping/scripts/make_brisk_map.py b/localization/sparse_mapping/scripts/make_teblid512_map.py similarity index 72% rename from localization/sparse_mapping/scripts/make_brisk_map.py rename to localization/sparse_mapping/scripts/make_teblid512_map.py index 073dcf4f1c..75766ab10f 100755 --- a/localization/sparse_mapping/scripts/make_brisk_map.py +++ b/localization/sparse_mapping/scripts/make_teblid512_map.py @@ -17,7 +17,7 @@ # License for the specific language governing permissions and limitations # under the License. """ -Generates a new brisk map with a vocab database using the provided surf map. +Generates a new teblid512 map with a vocab database using the provided surf map. """ import argparse @@ -28,7 +28,7 @@ import localization_common.utilities as lu -def make_brisk_map(surf_map, world, robot_name, map_directory=None): +def make_teblid512_map(surf_map, world, robot_name, map_directory=None): # Set environment variables home = os.path.expanduser("~") robot_config_file = os.path.join("config/robots", robot_name + ".config") @@ -38,34 +38,36 @@ def make_brisk_map(surf_map, world, robot_name, map_directory=None): os.environ["ASTROBEE_ROBOT"] = os.path.join(astrobee_path, robot_config_file) os.environ["ASTROBEE_WORLD"] = world - # Convert SURF to BRISK map + # Convert SURF to TEBLID512 map # Get full path to output file to avoid permission errors when running # command in maps directory map_name = lu.basename(surf_map) - build_brisk_map_output_file = os.path.join( - os.getcwd(), "rebuild_map_as_brisk_map.txt" + build_teblid512_map_output_file = os.path.join( + os.getcwd(), "rebuild_map_as_teblid512_map.txt" ) - brisk_map = map_name + ".brisk.map" - shutil.copyfile(surf_map, brisk_map) - brisk_map_full_path = os.path.abspath(brisk_map) + teblid512_map = map_name + ".teblid512.map" + shutil.copyfile(surf_map, teblid512_map) + teblid512_map_full_path = os.path.abspath(teblid512_map) path = os.getcwd() # Change to map directory so relative image locations are correct if necessary if map_directory: os.chdir(map_directory) - build_brisk_map_command = ( - "rosrun sparse_mapping build_map -rebuild -histogram_equalization -output_map " - + brisk_map_full_path + build_teblid512_map_command = ( + "rosrun sparse_mapping build_map -rebuild -histogram_equalization -use_clahe -output_map " + + teblid512_map_full_path + ) + lu.run_command_and_save_output( + build_teblid512_map_command, build_teblid512_map_output_file ) - lu.run_command_and_save_output(build_brisk_map_command, build_brisk_map_output_file) # Change back to original directory so final map is saved there if map_directory: os.chdir(path) # Create vocabdb - brisk_vocabdb_map = map_name + ".brisk.vocabdb.map" - shutil.copyfile(brisk_map, brisk_vocabdb_map) + teblid512_vocabdb_map = map_name + ".teblid512.vocabdb.map" + shutil.copyfile(teblid512_map, teblid512_vocabdb_map) add_vocabdb_command = ( - "rosrun sparse_mapping build_map -vocab_db -output_map " + brisk_vocabdb_map + "rosrun sparse_mapping build_map -vocab_db -output_map " + teblid512_vocabdb_map ) lu.run_command_and_save_output(add_vocabdb_command, "build_vocabdb.txt") @@ -75,7 +77,7 @@ def make_brisk_map(surf_map, world, robot_name, map_directory=None): description=__doc__, formatter_class=argparse.ArgumentDefaultsHelpFormatter ) parser.add_argument( - "surf_map", help="Input SURF map to generate the BRISK map for." + "surf_map", help="Input SURF map to generate the TEBLID512 map for." ) parser.add_argument("-w", "--world", default="iss") parser.add_argument("-r", "--robot-name", default="bumble") @@ -83,7 +85,7 @@ def make_brisk_map(surf_map, world, robot_name, map_directory=None): "-d", "--map-directory", default=None, - help="Location where surf map was created, needed to load images for BRISK map building since relative paths are used during map creation for the image locations. Defaults to current working directory.", + help="Location where surf map was created, needed to load images for TEBLID512 map building since relative paths are used during map creation for the image locations. Defaults to current working directory.", ) args = parser.parse_args() @@ -98,4 +100,4 @@ def make_brisk_map(surf_map, world, robot_name, map_directory=None): surf_map = os.path.abspath(args.surf_map) if args.map_directory: args.map_directory = os.path.abspath(args.map_directory) - make_brisk_map(surf_map, args.world, args.robot_name, args.map_directory) + make_teblid512_map(surf_map, args.world, args.robot_name, args.map_directory)