source: other-projects/is-sheet-music-encore/trunk/image-identification-dev-02/image-identification-development/src/MainMorph.java@ 33415

Last change on this file since 33415 was 33415, checked in by cpb16, 5 years ago

updated, after unable to commit due to setup.bash being out of date. Added mainMorph for morphological development
File size: 13.7 KB
Line 
1/*
2 StartAndEndPoint l1 = parseArray[i];
3 StartAndEndPoint l2 = parseArray[i+ 1];
4 //CHECK WHICH line starts after the other
5 //If l1 is starting after, then comparisons are based around l1.s
6 //System.out.println("l1: " + l1.getP1().x);
7 //System.out.println("l2: " + l2.getP1().x);
8
9 System.out.println("1.0: L1S: " + l1.getP1().x + " larger than L2S: " + l2.getP1().x);
10 if(l1.getP1().x > l2.getP1().x) {
11 System.out.println("1.1: Comparing L1S: " + l1.getP1().x + " less than L2E: " + l2.getP2().x);
12 if (l1.getP1().x < l2.getP2().x) {
13 //AND
14 System.out.println("1.2: Comparing L1S: " + l1.getP1().x + " larger than L2S: " + l2.getP1().x);
15 if (l1.getP1().x > l2.getP1().x) {
16 System.out.println("1: Success. NEXT");
17 //IT IS INTERSECTED
18 continue;
19 }
20 else {
21 //FAILED SECOND COMPARISON
22 System.out.println("1: Fail");
23 }
24 }
25 else {
26 System.out.println("Checking other line");
27 }
28 System.out.println("2.0: L2S: " + l2.getP1().x + " larger than L1S: " + l1.getP1().x);
29 }
30 //If l2 is starting after, then comparisons are based around l2.s
31 else if(l2.getP1().x > l1.getP1().x) {
32 System.out.println("2.1: Comparing L2S: " + l1.getP1().x + " less than L1E: " + l2.getP2().x);
33 if (l2.getP1().x < l1.getP2().x) {
34 //AND
35 System.out.println("2.2: Comparing L2S: " + l2.getP1().x + " larger than L1S: " + l1.getP1().x);
36 if (l2.getP1().x > l1.getP1().x) {
37 System.out.println("2: Success");
38 //IT IS INTERSECTED
39 //continue;
40 }
41 else {
42 //FAILED SECOND COMPARISON
43 System.out.println("2: Fail");
44 //return false;
45 }
46 }
47 else {
48 System.out.println("Failed second comparison RETURN FALSE");
49 return false;
50 }
51 //return false;
52 }
53 else{
54 System.out.println("NEITHER RETURN FALSE");
55 return false;
56 }
57 */
58
59import org.opencv.core.*;
60import org.opencv.core.Point;
61import org.opencv.highgui.HighGui;
62import org.opencv.imgcodecs.Imgcodecs;
63import org.opencv.imgproc.Imgproc;
64import org.opencv.photo.Photo;
65import static org.opencv.imgcodecs.Imgcodecs.imwrite;
66import java.awt.image.BufferedImage;
67import java.awt.image.DataBufferByte;
68import java.io.File;
69import java.util.ArrayList;
70import java.util.Collection;
71import java.util.Collections;
72import java.util.Comparator;
73import javax.imageio.ImageIO;
74
75//REFERENCES:
76//https://docs.opencv.org/3.4.3/d9/db0/tutorial_hough_lines.
77//https://stackoverflow.com/questions/43443309/count-red-pixel-in-a-given-image
78//https://www.wikihow.com/Calculate-Percentage-in-Java
79//https://riptutorial.com/opencv/example/21963/converting-an-mat-object-to-an-bufferedimage-object
80//https://beginnersbook.com/2013/12/java-arraylist-of-object-sort-example-comparable-and-comparator/
81//https://www.programiz.com/java-programming/examples/standard-deviation
82//https://www.geeksforgeeks.org/how-to-remove-duplicates-from-arraylist-in-java/
83//https://stackoverflow.com/questions/7988486/how-do-you-calculate-the-variance-median-and-standard-deviation-in-c-or-java/7988556
84//https://stackoverflow.com/questions/10396970/sort-a-list-that-contains-a-custom-class
85//https://stackoverflow.com/questions/37946482/crop-images-area-with-opencv-java
86//https://docs.opencv.org/3.4/dd/dd7/tutorial_morph_lines_detection.html
87
88
89
90//GOAL for 21st
91
92
93//Classifier 01
94//Have args so can call "java image-identification-classifier01 XX XX"
95//args can be parameters in algorthim such as threshold or theta?
96//Run on 5000 images.
97//Record success rates
98//All done with makefile
99
100
101//But first understand houghline transform
102//Know what the algorithm being used is doing.
103//MAke constants for this classifier
104//Make java be able to run on CMD line
105
106public class MainMorph {
107 //GLOBAL_CONSTANTS
108
109 static double THRESHOLD_C = 4;
110
111
112 //
113 static class StartAndEndPoint {
114 //PRIVATES
115 private Point _p1;
116 private Point _p2;
117 //CONSTRUCTOR
118 public StartAndEndPoint(Point p1, Point p2){
119 _p1 = p1;
120 _p2 = p2;
121 }
122 //GETTERS
123 public Point getP1(){
124 return _p1;
125 }
126 public Point getP2(){
127 return _p2;
128 }
129 //SETTERS
130 public void setP1(Point p1){
131 _p1 = p1;
132 }
133 public void setP2(Point p2){
134 _p2 = p2;
135 }
136
137 //ToString
138 public String toString(){
139 return "Start: " + _p1 + " End: " + _p2;
140 }
141
142 }
143 private static BufferedImage toBufferedImage(Mat mat){
144 //MOSTLY COPY PASTE!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
145 //MOSTLY COPY PASTE!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
146 //https://riptutorial.com/opencv/example/21963/converting-an-mat-object-to-an-bufferedimage-object
147 try{
148 int type = BufferedImage.TYPE_3BYTE_BGR;
149 int bufferSize = mat.channels() * mat.cols() * mat.rows();
150 byte[] b = new byte[bufferSize];
151 //get all the pixels
152 mat.get(0, 0, b);
153 BufferedImage image = new BufferedImage(mat.cols(), mat.rows(), type);
154 final byte[] targetPixels = ((DataBufferByte) image.getRaster().getDataBuffer()).getData();
155 System.arraycopy(b, 0, targetPixels, 0, b.length);
156 return image;
157 }
158 catch(Exception e){
159 System.err.println(e);
160 }
161 return null;
162 }
163
164 private static void showWaitDestroy(String winname, Mat img) {
165 HighGui.imshow(winname, img);
166 HighGui.moveWindow(winname, 500, 0);
167 HighGui.waitKey(0);
168 HighGui.destroyWindow(winname);
169 }
170 //MAIN
171 public static void main(String[] args) {
172
173 System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
174
175 try {
176 ArrayList<StartAndEndPoint> pointArrayList = new ArrayList<>();
177
178 //Variables
179 Mat edgesDetected = new Mat();
180 Mat mid = new Mat();
181 Mat edgesDetectedRGB = new Mat();
182 Mat clustersFoundRGB = new Mat();
183 String directory = "/Scratch/cpb16/is-sheet-music-encore/download-images/MU/";
184 String hiresDirectory = "/Scratch/cpb16/is-sheet-music-encore/hires-download-images/";
185
186 //!!!!!!!!!!!!!!!!!!!!!!!!!!!NOT!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
187 //mdp.39015097852365-2.png 176 lines Contents page.
188 //mdp.39015097852555-3.png 76 lines
189 //!!!!!!!!!!!!!!!!!!!!!!!!!!!NOTNOT!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
190 //coo.31924062612282-9.png 8 lines
191 //String default_file = directory+"NotSheetMusic/coo.31924062612282-9.png";
192 //String default_file = directory+"NotSheetMusic/mdp.39015097852365-2.png";
193 //String default_file ="TestImages/NotNot/mdp.39015080972303-3.png";
194 //String default_file =hiresDirectory+"BK/NotSheetMusic/aeu.ark+=13960=t2q53nq6w-6.png";
195 String default_file = "/Scratch/cpb16/is-sheet-music-encore/image-identification-terminal/TestImages/test-coo.31924062612282-9.png";
196 //String default_file =hiresDirectory+"BK/NotSheetMusic/aeu.ark+=13960=t9z03w65z-4.png";
197
198 //System.out.println(default_file);
199 //String default_file = "TestImages/NotSheetMusic01.png";
200 //String default_file = "TestImages/NotSheetMusic02.png";
201 //String default_file = "TestImages/SheetMusic01.png";
202 //String default_file = "TestImages/SheetMusic02.png";
203 //String default_file = "TestImages/vLine.png";
204 String filename = ((args.length > 0) ? args[0] : default_file);
205 File file = new File(filename);
206 if(!file.exists()){System.err.println("Image not found: "+ filename);}
207
208 int horizontalLineCount =0;
209
210 // Load an image
211 Mat original = Imgcodecs.imread(filename, Imgcodecs.IMREAD_GRAYSCALE);
212 // Edge detection
213
214 Imgproc.adaptiveThreshold(original, edgesDetected,255, Imgproc.ADAPTIVE_THRESH_GAUSSIAN_C,Imgproc.THRESH_BINARY_INV, 15, THRESHOLD_C);
215 //TEST PARAMETERSImgproc.adaptiveThreshold(original, edgesDetected,255, Imgproc.ADAPTIVE_THRESH_GAUSSIAN_C,Imgproc.THRESH_BINARY_INV, 531,1);
216
217
218
219 //****************MORPHOLOGY****************************************************************************************
220 //ADDIOTIONAL FILTERING TO STOP STREAKS
221 //LOOK INTO STREAKS MORPHOGOLY.
222 //****************MORPHOLOGY****************************************************************************************
223
224 //Mat kernel = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(4,8));
225 //Imgproc.morphologyEx(original, mid, Imgproc.MORPH_OPEN, kernel);
226 //Imgproc.adaptiveThreshold(mid, edgesDetected,255, Imgproc.ADAPTIVE_THRESH_GAUSSIAN_C,Imgproc.THRESH_BINARY_INV, 15, 2);
227
228 // Create the images that will use to extract the horizontal and vertical lines
229 Mat horizontal = original.clone();
230 Mat vertical = original.clone();
231 // Specify size on horizontal axis
232 int horizontal_size = horizontal.cols() / 30;
233 // Create structure element for extracting horizontal lines through morphology operations
234 Mat horizontalStructure = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(horizontal_size,1));
235 // Apply morphology operations
236 Imgproc.erode(horizontal, horizontal, horizontalStructure);
237 Imgproc.dilate(horizontal, horizontal, horizontalStructure);
238 // Show extracted horizontal lines
239 showWaitDestroy("horizontal" , horizontal);
240 // Specify size on vertical axis
241 int vertical_size = vertical.rows() / 30;
242 // Create structure element for extracting vertical lines through morphology operations
243 Mat verticalStructure = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size( 1,vertical_size));
244 // Apply morphology operations
245 Imgproc.erode(vertical, vertical, verticalStructure);
246 Imgproc.dilate(vertical, vertical, verticalStructure);
247 // Show extracted vertical lines
248 showWaitDestroy("vertical", vertical);
249 // Inverse vertical image
250 Core.bitwise_not(vertical, vertical);
251 showWaitDestroy("vertical_bit" , vertical);
252 // Extract edges and smooth image according to the logic
253 // 1. extract edges
254 // 2. dilate(edges)
255 // 3. src.copyTo(smooth)
256 // 4. blur smooth img
257 // 5. smooth.copyTo(src, edges)
258 // Step 1
259 Mat edges = new Mat();
260 Imgproc.adaptiveThreshold(vertical, edges, 255, Imgproc.ADAPTIVE_THRESH_MEAN_C, Imgproc.THRESH_BINARY, 3, -2);
261 showWaitDestroy("edges", edges);
262 // Step 2
263 Mat kernel = Mat.ones(2, 2, CvType.CV_8UC1);
264 Imgproc.dilate(edges, edges, kernel);
265 showWaitDestroy("dilate", edges);
266 // Step 3
267 Mat smooth = new Mat();
268 vertical.copyTo(smooth);
269 // Step 4
270 Imgproc.blur(smooth, smooth, new Size(2, 2));
271 // Step 5
272 smooth.copyTo(vertical, edges);
273 // Show final result
274 showWaitDestroy("smooth - final", vertical);
275 System.exit(0);
276
277
278
279
280 //****************MORPHOLOGY****************************************************************************************
281
282 BufferedImage toBeClassifiedImg = toBufferedImage(edgesDetectedRGB);
283
284
285 //Display Results
286 //HighGui.imshow("Source", original);
287 //HighGui.imshow("Just Edges", justEdges); //TESTING
288
289
290 HighGui.imshow("LINESFOUND", edgesDetectedRGB);
291 HighGui.resizeWindow("LINESFOUND", 1000,1000);
292
293 //HighGui.imshow("CLUSTERS FOUND", clustersFoundRGB);
294 //HighGui.imshow("Detected Lines (in red) - negative", edgesDetectedRGBProb);
295
296 //COUNT OF LINES CLASSIFICATION
297 //System.out.println("LINE CLUSTER RESULT: " + ClassifierLineClusterOLD(toBeClassifiedImg).get(0) + '\t' + "LinesFound: " + ClassifierLineClusterOLD(toBeClassifiedImg).get(1) + '\t' + "ClustersFound: " + ClassifierLineClusterOLD(toBeClassifiedImg).get(2));
298 //System.out.println("NEW CLUSTER RESULTS: " + ClassifierLineClusterPt(pointArrayList,clustersFoundRGB).get(0) + '\t' + "LinesFound: " + horizontalLineCount + '\t' + "ClustersFound: " + ClassifierLineClusterPt(pointArrayList,clustersFoundRGB).get(1));
299 //System.out.println(ClassifierLineClusterPt(pointArrayList, clustersFoundRGB));
300
301 //System.out.println("TEST: " + LineCountOrCluster(horizontalLineCount, pointArrayList, clustersFoundRGB));
302
303 // Wait and Exit
304 HighGui.waitKey();
305 System.exit(0);
306 }
307 catch(Exception e){
308 System.err.println(e);
309 }
310 }
311}
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