From a7608e12e7671f90e80f4bc868c1ad082a86354b Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Thu, 19 Oct 2023 15:57:17 +0000 Subject: [PATCH] update feature detector --- .../feature_detection/feature_detector.ipynb | 229 ++++++++++++++---- 1 file changed, 178 insertions(+), 51 deletions(-) diff --git a/scripts/experiments/deeplearning/feature_detection/feature_detector.ipynb b/scripts/experiments/deeplearning/feature_detection/feature_detector.ipynb index c88728ca..ab857f69 100644 --- a/scripts/experiments/deeplearning/feature_detection/feature_detector.ipynb +++ b/scripts/experiments/deeplearning/feature_detection/feature_detector.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -23,7 +23,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 37, "metadata": {}, "outputs": [ { @@ -31,7 +31,7 @@ "output_type": "stream", "text": [ "You can open the visualizer by visiting the following URL:\n", - "http://127.0.0.1:7019/static/\n" + "http://127.0.0.1:7022/static/\n" ] } ], @@ -41,7 +41,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -81,7 +81,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -97,7 +97,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -108,7 +108,7 @@ "" ] }, - "execution_count": 34, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -120,13 +120,13 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "bcf8495844134cc196393bb6c065d198", + "model_id": "97ab7bae17704f0981d5e03c29b9dfae", "version_major": 2, "version_minor": 0 }, @@ -152,7 +152,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "(37, 49)\n" + "(36, 50)\n" ] } ], @@ -175,7 +175,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -190,7 +190,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -198,50 +198,79 @@ "coordinates = jnp.einsum(\"j,kij->ki\", b.add_homogenous_ones(coordinate_in_object_frame), random_poses)\n", "pixel_coordinates = jnp.round(b.camera.project_cloud_to_pixels(coordinates, intrinsics)).astype(jnp.int32)\n", "\n", - "img = b.RENDERER.render_many(random_poses[:,None,...], jnp.array([13]))\n", - "rendered_points = img[jnp.arange(img.shape[0]), pixel_coordinates[:,1], pixel_coordinates[:,0], :3]\n", + "images = b.RENDERER.render_many(random_poses[:,None,...], jnp.array([13]))\n", + "rendered_points = images[jnp.arange(images.shape[0]), pixel_coordinates[:,1], pixel_coordinates[:,0], :3]\n", "distances = jnp.linalg.norm(rendered_points- coordinates[:,:3],axis=-1)" ] }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "1053\n", - "0.52650005\n", - "0.0003880836\n" + "884\n", + "0.44200003\n" ] - }, + } + ], + "source": [ + "valid_indices = distances < 0.01\n", + "print(valid_indices.sum())\n", + "print(valid_indices.sum() / valid_indices.shape[0])\n", + "i = distances.argsort()[10]\n", + "b.clear()\n", + "b.show_cloud(\"data\", img[i,:,:,:3].reshape(-1,3))\n", + "b.show_cloud(\"point2\", rendered_points[i].reshape(-1,3), color=b.RED)\n", + "b.show_cloud(\"point\", coordinates[i,:3].reshape(-1,3), color=b.BLUE)\n", + "coordinate_in_object_frame = b.apply_transform(coordinate.reshape(-1,3), b.t3d.inverse_pose(table_pose))[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ { "data": { "text/plain": [ - "" + "(884, 100, 100, 4)" ] }, - "execution_count": 38, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" - }, + } + ], + "source": [ + "images_subset = images[valid_indices]\n", + "pixel_coordinates_subset = pixel_coordinates[valid_indices]\n", + "images_subset.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4a8c4fdeaa7941c09a56683d0e53de8c", + "model_id": "ebfd0ae9044d4edba92b1afa938386f8", "version_major": 2, "version_minor": 0 }, - "image/png": 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", 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"text/html": [ "\n", "
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\n", " Figure\n", "
\n", - " \n", + " \n", "
\n", " " ], @@ -254,41 +283,125 @@ } ], "source": [ - "valid_indices = distances < 0.01\n", - "print(valid_indices.sum())\n", - "print(valid_indices.sum() / valid_indices.shape[0])\n", - "i = distances.argsort()[10]\n", - "b.clear()\n", - "b.show_cloud(\"data\", img[i,:,:,:3].reshape(-1,3))\n", - "b.show_cloud(\"point2\", rendered_points[i].reshape(-1,3), color=b.RED)\n", - "b.show_cloud(\"point\", coordinates[i,:3].reshape(-1,3), color=b.BLUE)\n", - "coordinate_in_object_frame = b.apply_transform(coordinate.reshape(-1,3), b.t3d.inverse_pose(table_pose))[0]\n", + "fig = plt.figure()\n", + "N = 25\n", + "for i in range(N):\n", + " ax = fig.add_subplot(5,5,i+1)\n", + " b.add_depth_image(ax, images_subset[i,...,2])\n", + " # ax.axis(\"on\")\n", + " ax.scatter(pixel_coordinates[i,0], pixel_coordinates[i,1], c='black', alpha=0.8,s=60, marker='x')\n", + "# plt.subplots_adjust(top = 0.0, bottom=0.0, hspace=0.1, wspace=0.4)\n", + "plt.subplots_adjust(wspace=0, hspace=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "# np.savez(\"training_data.npz\", images_subset, pixel_coordinates_subset)\n", + "# data = np.load(\"training_data.npz\")\n", + "# images_loaded = data[\"arr_0\"]\n", + "# pixel_coordinates_loaded = data[\"arr_1\"]\n", + "# print(images_loaded.shape, pixel_coordinates_loaded.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "# Image patch to voxel grid\n", "\n", - "print(distances[i])\n", - "fig = b.viz_depth_image(img[i,...,2])\n", - "fig.get_axes()[0].scatter(pixel_coordinates[i,0], pixel_coordinates[i,1], c='r', s=10)" + "i = distances.argsort()[j]\n", + "patch_width = 5\n", + "pixelx, pixely = pixel_coordinates_subset[i]\n", + "patch = images_subset[i, pixely-patch_width:pixely+patch_width, pixelx-patch_width:pixelx+patch_width, :3]\n", + "b.show_cloud(\"1\", (patch - patch[patch_width,patch_width]).reshape(-1,3))" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [], + "source": [ + "get_patch = lambda i: jax.lax.dynamic_slice(images_subset,\n", + " (i,pixel_coordinates_subset[i,1]-patch_width, pixel_coordinates_subset[i,0]-patch_width, 0),\n", + " (1,2*patch_width+1,2*patch_width+1,3))[0,...]\n", + "patches = jax.vmap(get_patch)(jnp.arange(images_subset.shape[0]))\n", + "patches_centered = patches - patches[:,patch_width,patch_width,:][...,None,None,:]" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [], + "source": [ + "b.show_cloud(\"1\", patches_centered[20].reshape(-1,3))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(884, 2)" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pixel_coordinates_subset.shape" ] }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 42, "metadata": {}, "outputs": [ + { + "data": { + "image/png": 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", + "image/png": 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"text/html": [ "\n", "
\n", "
\n", " Figure\n", "
\n", - " \n", + " \n", "
\n", " " ], @@ -301,16 +414,30 @@ } ], "source": [ - "fig = plt.figure()\n", - "N = 25\n", - "for j in range(N):\n", - " ax = fig.add_subplot(5,5,j+1)\n", - " i = distances.argsort()[j]\n", - " b.add_depth_image(ax, img[i,...,2])\n", - " # ax.axis(\"on\")\n", - " ax.scatter(pixel_coordinates[i,0], pixel_coordinates[i,1], c='black', alpha=0.8,s=60, marker='x')\n", - "# plt.subplots_adjust(top = 0.0, bottom=0.0, hspace=0.1, wspace=0.4)\n", - "plt.subplots_adjust(wspace=0, hspace=0)" + "b.viz_depth_image(img[i,...,2])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "b.show_cloud(\"!\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "K = 4\n", + "def predict_based_on_patch(patch, convolutional_kernel):\n", + " \"\"\"\n", + " patch: (K,K,3) point cloud patch\n", + " \"\"\"\n", + " centered_patch = patch - patch[K,K,:]\n" ] }, {