-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathGripPipeline.java
264 lines (235 loc) · 8.45 KB
/
GripPipeline.java
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
import java.io.File;
import java.io.FileWriter;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import java.util.stream.Collectors;
import java.util.HashMap;
import org.opencv.core.*;
import org.opencv.core.Core.*;
import org.opencv.features2d.FeatureDetector;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.*;
import org.opencv.objdetect.*;
/**
* GripPipeline class.
*
* <p>An OpenCV pipeline generated by GRIP.
*
* @author GRIP
*/
public class GripPipeline {
//Outputs
private Mat hsvThresholdOutput = new Mat();
private Mat blurOutput = new Mat();
private ArrayList<MatOfPoint> findContoursOutput = new ArrayList<MatOfPoint>();
private ArrayList<MatOfPoint> filterContoursOutput = new ArrayList<MatOfPoint>();
static {
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
}
/**
* This is the primary method that runs the entire pipeline and updates the outputs.
*/
public void process(Mat source0) {
// Step HSV_Threshold0:
Mat hsvThresholdInput = source0;
double[] hsvThresholdHue = {58.0870555354048, 99.95019301177184};
double[] hsvThresholdSaturation = {22.93165467625899, 124.45392491467575};
double[] hsvThresholdValue = {226.75968017115633, 254.73629887619228};
hsvThreshold(hsvThresholdInput, hsvThresholdHue, hsvThresholdSaturation, hsvThresholdValue, hsvThresholdOutput);
// Step Blur0:
Mat blurInput = hsvThresholdOutput;
BlurType blurType = BlurType.get("Median Filter");
double blurRadius = 3.693693693693695;
blur(blurInput, blurType, blurRadius, blurOutput);
// Step Find_Contours0:
Mat findContoursInput = blurOutput;
boolean findContoursExternalOnly = false;
findContours(findContoursInput, findContoursExternalOnly, findContoursOutput);
// Step Filter_Contours0:
ArrayList<MatOfPoint> filterContoursContours = findContoursOutput;
double filterContoursMinArea = 450.0;
double filterContoursMinPerimeter = 0.0;
double filterContoursMinWidth = 0.0;
double filterContoursMaxWidth = 1000.0;
double filterContoursMinHeight = 0.0;
double filterContoursMaxHeight = 1000.0;
double[] filterContoursSolidity = {0, 100};
double filterContoursMaxVertices = 1000000.0;
double filterContoursMinVertices = 0.0;
double filterContoursMinRatio = 0.0;
double filterContoursMaxRatio = 1000.0;
filterContours(filterContoursContours, filterContoursMinArea, filterContoursMinPerimeter, filterContoursMinWidth, filterContoursMaxWidth, filterContoursMinHeight, filterContoursMaxHeight, filterContoursSolidity, filterContoursMaxVertices, filterContoursMinVertices, filterContoursMinRatio, filterContoursMaxRatio, filterContoursOutput);
}
/**
* This method is a generated getter for the output of a HSV_Threshold.
* @return Mat output from HSV_Threshold.
*/
public Mat hsvThresholdOutput() {
return hsvThresholdOutput;
}
/**
* This method is a generated getter for the output of a Blur.
* @return Mat output from Blur.
*/
public Mat blurOutput() {
return blurOutput;
}
/**
* This method is a generated getter for the output of a Find_Contours.
* @return ArrayList<MatOfPoint> output from Find_Contours.
*/
public ArrayList<MatOfPoint> findContoursOutput() {
return findContoursOutput;
}
/**
* This method is a generated getter for the output of a Filter_Contours.
* @return ArrayList<MatOfPoint> output from Filter_Contours.
*/
public ArrayList<MatOfPoint> filterContoursOutput() {
return filterContoursOutput;
}
/**
* Segment an image based on hue, saturation, and value ranges.
*
* @param input The image on which to perform the HSL threshold.
* @param hue The min and max hue
* @param sat The min and max saturation
* @param val The min and max value
* @param output The image in which to store the output.
*/
private void hsvThreshold(Mat input, double[] hue, double[] sat, double[] val,
Mat out) {
Imgproc.cvtColor(input, out, Imgproc.COLOR_BGR2HSV);
Core.inRange(out, new Scalar(hue[0], sat[0], val[0]),
new Scalar(hue[1], sat[1], val[1]), out);
}
/**
* An indication of which type of filter to use for a blur.
* Choices are BOX, GAUSSIAN, MEDIAN, and BILATERAL
*/
enum BlurType{
BOX("Box Blur"), GAUSSIAN("Gaussian Blur"), MEDIAN("Median Filter"),
BILATERAL("Bilateral Filter");
private final String label;
BlurType(String label) {
this.label = label;
}
public static BlurType get(String type) {
if (BILATERAL.label.equals(type)) {
return BILATERAL;
}
else if (GAUSSIAN.label.equals(type)) {
return GAUSSIAN;
}
else if (MEDIAN.label.equals(type)) {
return MEDIAN;
}
else {
return BOX;
}
}
@Override
public String toString() {
return this.label;
}
}
/**
* Softens an image using one of several filters.
* @param input The image on which to perform the blur.
* @param type The blurType to perform.
* @param doubleRadius The radius for the blur.
* @param output The image in which to store the output.
*/
private void blur(Mat input, BlurType type, double doubleRadius,
Mat output) {
int radius = (int)(doubleRadius + 0.5);
int kernelSize;
switch(type){
case BOX:
kernelSize = 2 * radius + 1;
Imgproc.blur(input, output, new Size(kernelSize, kernelSize));
break;
case GAUSSIAN:
kernelSize = 6 * radius + 1;
Imgproc.GaussianBlur(input,output, new Size(kernelSize, kernelSize), radius);
break;
case MEDIAN:
kernelSize = 2 * radius + 1;
Imgproc.medianBlur(input, output, kernelSize);
break;
case BILATERAL:
Imgproc.bilateralFilter(input, output, -1, radius, radius);
break;
}
}
/**
* Sets the values of pixels in a binary image to their distance to the nearest black pixel.
* @param input The image on which to perform the Distance Transform.
* @param type The Transform.
* @param maskSize the size of the mask.
* @param output The image in which to store the output.
*/
private void findContours(Mat input, boolean externalOnly,
List<MatOfPoint> contours) {
Mat hierarchy = new Mat();
contours.clear();
int mode;
if (externalOnly) {
mode = Imgproc.RETR_EXTERNAL;
}
else {
mode = Imgproc.RETR_LIST;
}
int method = Imgproc.CHAIN_APPROX_SIMPLE;
Imgproc.findContours(input, contours, hierarchy, mode, method);
}
/**
* Filters out contours that do not meet certain criteria.
* @param inputContours is the input list of contours
* @param output is the the output list of contours
* @param minArea is the minimum area of a contour that will be kept
* @param minPerimeter is the minimum perimeter of a contour that will be kept
* @param minWidth minimum width of a contour
* @param maxWidth maximum width
* @param minHeight minimum height
* @param maxHeight maximimum height
* @param Solidity the minimum and maximum solidity of a contour
* @param minVertexCount minimum vertex Count of the contours
* @param maxVertexCount maximum vertex Count
* @param minRatio minimum ratio of width to height
* @param maxRatio maximum ratio of width to height
*/
private void filterContours(List<MatOfPoint> inputContours, double minArea,
double minPerimeter, double minWidth, double maxWidth, double minHeight, double
maxHeight, double[] solidity, double maxVertexCount, double minVertexCount, double
minRatio, double maxRatio, List<MatOfPoint> output) {
final MatOfInt hull = new MatOfInt();
output.clear();
//operation
for (int i = 0; i < inputContours.size(); i++) {
final MatOfPoint contour = inputContours.get(i);
final Rect bb = Imgproc.boundingRect(contour);
if (bb.width < minWidth || bb.width > maxWidth) continue;
if (bb.height < minHeight || bb.height > maxHeight) continue;
final double area = Imgproc.contourArea(contour);
if (area < minArea) continue;
if (Imgproc.arcLength(new MatOfPoint2f(contour.toArray()), true) < minPerimeter) continue;
Imgproc.convexHull(contour, hull);
MatOfPoint mopHull = new MatOfPoint();
mopHull.create((int) hull.size().height, 1, CvType.CV_32SC2);
for (int j = 0; j < hull.size().height; j++) {
int index = (int)hull.get(j, 0)[0];
double[] point = new double[] { contour.get(index, 0)[0], contour.get(index, 0)[1]};
mopHull.put(j, 0, point);
}
final double solid = 100 * area / Imgproc.contourArea(mopHull);
if (solid < solidity[0] || solid > solidity[1]) continue;
if (contour.rows() < minVertexCount || contour.rows() > maxVertexCount) continue;
final double ratio = bb.width / (double)bb.height;
if (ratio < minRatio || ratio > maxRatio) continue;
output.add(contour);
}
}
}