mirror of https://github.com/opencv/opencv.git
catree
7 years ago
parent
1187a7fa34
commit
afa5b0cc93
13 changed files with 560 additions and 103 deletions
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Before Width: | Height: | Size: 75 KiB After Width: | Height: | Size: 75 KiB |
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import java.util.List; |
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import org.opencv.core.Core; |
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import org.opencv.core.Mat; |
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import org.opencv.core.MatOfRect; |
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import org.opencv.core.Point; |
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import org.opencv.core.Rect; |
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import org.opencv.core.Scalar; |
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import org.opencv.core.Size; |
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import org.opencv.highgui.HighGui; |
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import org.opencv.imgproc.Imgproc; |
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import org.opencv.objdetect.CascadeClassifier; |
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import org.opencv.videoio.VideoCapture; |
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class ObjectDetection { |
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public void detectAndDisplay(Mat frame, CascadeClassifier faceCascade, CascadeClassifier eyesCascade) { |
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Mat frameGray = new Mat(); |
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Imgproc.cvtColor(frame, frameGray, Imgproc.COLOR_BGR2GRAY); |
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Imgproc.equalizeHist(frameGray, frameGray); |
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// -- Detect faces
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MatOfRect faces = new MatOfRect(); |
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faceCascade.detectMultiScale(frameGray, faces); |
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List<Rect> listOfFaces = faces.toList(); |
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for (Rect face : listOfFaces) { |
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Point center = new Point(face.x + face.width / 2, face.y + face.height / 2); |
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Imgproc.ellipse(frame, center, new Size(face.width / 2, face.height / 2), 0, 0, 360, |
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new Scalar(255, 0, 255)); |
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Mat faceROI = frameGray.submat(face); |
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// -- In each face, detect eyes
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MatOfRect eyes = new MatOfRect(); |
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eyesCascade.detectMultiScale(faceROI, eyes); |
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List<Rect> listOfEyes = eyes.toList(); |
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for (Rect eye : listOfEyes) { |
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Point eyeCenter = new Point(face.x + eye.x + eye.width / 2, face.y + eye.y + eye.height / 2); |
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int radius = (int) Math.round((eye.width + eye.height) * 0.25); |
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Imgproc.circle(frame, eyeCenter, radius, new Scalar(255, 0, 0), 4); |
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} |
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} |
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//-- Show what you got
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HighGui.imshow("Capture - Face detection", frame ); |
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} |
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public void run(String[] args) { |
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String filenameFaceCascade = args.length > 2 ? args[0] : "../../data/haarcascades/haarcascade_frontalface_alt.xml"; |
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String filenameEyesCascade = args.length > 2 ? args[1] : "../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml"; |
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int cameraDevice = args.length > 2 ? Integer.parseInt(args[2]) : 0; |
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CascadeClassifier faceCascade = new CascadeClassifier(); |
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CascadeClassifier eyesCascade = new CascadeClassifier(); |
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if (!faceCascade.load(filenameFaceCascade)) { |
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System.err.println("--(!)Error loading face cascade: " + filenameFaceCascade); |
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System.exit(0); |
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} |
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if (!eyesCascade.load(filenameEyesCascade)) { |
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System.err.println("--(!)Error loading eyes cascade: " + filenameEyesCascade); |
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System.exit(0); |
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} |
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VideoCapture capture = new VideoCapture(cameraDevice); |
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if (!capture.isOpened()) { |
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System.err.println("--(!)Error opening video capture"); |
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System.exit(0); |
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} |
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Mat frame = new Mat(); |
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while (capture.read(frame)) { |
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if (frame.empty()) { |
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System.err.println("--(!) No captured frame -- Break!"); |
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break; |
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} |
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//-- 3. Apply the classifier to the frame
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detectAndDisplay(frame, faceCascade, eyesCascade); |
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if (HighGui.waitKey(10) == 27) { |
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break;// escape
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} |
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} |
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System.exit(0); |
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} |
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} |
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public class ObjectDetectionDemo { |
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public static void main(String[] args) { |
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// Load the native OpenCV library
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System.loadLibrary(Core.NATIVE_LIBRARY_NAME); |
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new ObjectDetection().run(args); |
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} |
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} |
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import java.io.IOException; |
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import java.nio.file.Files; |
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import java.nio.file.Paths; |
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import java.util.ArrayList; |
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import java.util.List; |
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import org.opencv.core.Core; |
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import org.opencv.core.CvType; |
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import org.opencv.core.Mat; |
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import org.opencv.imgcodecs.Imgcodecs; |
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import org.opencv.photo.CalibrateDebevec; |
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import org.opencv.photo.MergeDebevec; |
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import org.opencv.photo.MergeMertens; |
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import org.opencv.photo.Photo; |
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import org.opencv.photo.TonemapDurand; |
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class HDRImaging { |
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public void loadExposureSeq(String path, List<Mat> images, List<Float> times) { |
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path += "/"; |
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List<String> lines; |
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try { |
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lines = Files.readAllLines(Paths.get(path + "list.txt")); |
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for (String line : lines) { |
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String[] splitStr = line.split("\\s+"); |
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if (splitStr.length == 2) { |
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String name = splitStr[0]; |
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Mat img = Imgcodecs.imread(path + name); |
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images.add(img); |
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float val = Float.parseFloat(splitStr[1]); |
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times.add(1/ val); |
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} |
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} |
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} catch (IOException e) { |
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e.printStackTrace(); |
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} |
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} |
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public void run(String[] args) { |
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String path = args.length > 0 ? args[0] : ""; |
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if (path.isEmpty()) { |
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System.out.println("Path is empty. Use the directory that contains images and exposure times."); |
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System.exit(0); |
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} |
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//! [Load images and exposure times]
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List<Mat> images = new ArrayList<>(); |
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List<Float> times = new ArrayList<>(); |
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loadExposureSeq(path, images, times); |
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//! [Load images and exposure times]
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//! [Estimate camera response]
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Mat response = new Mat(); |
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CalibrateDebevec calibrate = Photo.createCalibrateDebevec(); |
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Mat matTimes = new Mat(times.size(), 1, CvType.CV_32F); |
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float[] arrayTimes = new float[(int) (matTimes.total()*matTimes.channels())]; |
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for (int i = 0; i < times.size(); i++) { |
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arrayTimes[i] = times.get(i); |
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} |
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matTimes.put(0, 0, arrayTimes); |
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calibrate.process(images, response, matTimes); |
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//! [Estimate camera response]
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//! [Make HDR image]
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Mat hdr = new Mat(); |
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MergeDebevec mergeDebevec = Photo.createMergeDebevec(); |
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mergeDebevec.process(images, hdr, matTimes); |
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//! [Make HDR image]
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//! [Tonemap HDR image]
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Mat ldr = new Mat(); |
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TonemapDurand tonemap = Photo.createTonemapDurand(); |
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tonemap.process(hdr, ldr); |
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//! [Tonemap HDR image]
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//! [Perform exposure fusion]
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Mat fusion = new Mat(); |
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MergeMertens mergeMertens = Photo.createMergeMertens(); |
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mergeMertens.process(images, fusion); |
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//! [Perform exposure fusion]
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//! [Write results]
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fusion = fusion.mul(fusion, 255); |
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ldr = ldr.mul(ldr, 255); |
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Imgcodecs.imwrite("fusion.png", fusion); |
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Imgcodecs.imwrite("ldr.png", ldr); |
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Imgcodecs.imwrite("hdr.hdr", hdr); |
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//! [Write results]
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System.exit(0); |
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} |
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} |
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public class HDRImagingDemo { |
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public static void main(String[] args) { |
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// Load the native OpenCV library
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System.loadLibrary(Core.NATIVE_LIBRARY_NAME); |
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new HDRImaging().run(args); |
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} |
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} |
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@ -0,0 +1,61 @@ |
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from __future__ import print_function |
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import cv2 as cv |
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import argparse |
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def detectAndDisplay(frame): |
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frame_gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY) |
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frame_gray = cv.equalizeHist(frame_gray) |
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#-- Detect faces |
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faces = face_cascade.detectMultiScale(frame_gray) |
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for (x,y,w,h) in faces: |
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center = (x + w//2, y + h//2) |
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frame = cv.ellipse(frame, center, (w//2, h//2), 0, 0, 360, (255, 0, 255), 4) |
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faceROI = frame_gray[y:y+h,x:x+w] |
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#-- In each face, detect eyes |
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eyes = eyes_cascade.detectMultiScale(faceROI) |
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for (x2,y2,w2,h2) in eyes: |
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eye_center = (x + x2 + w2//2, y + y2 + h2//2) |
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radius = int(round((w2 + h2)*0.25)) |
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frame = cv.circle(frame, eye_center, radius, (255, 0, 0 ), 4) |
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cv.imshow('Capture - Face detection', frame) |
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parser = argparse.ArgumentParser(description='Code for Cascade Classifier tutorial.') |
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parser.add_argument('--face_cascade', help='Path to face cascade.', default='../../data/haarcascades/haarcascade_frontalface_alt.xml') |
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parser.add_argument('--eyes_cascade', help='Path to eyes cascade.', default='../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml') |
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parser.add_argument('--camera', help='Camera devide number.', type=int, default=0) |
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args = parser.parse_args() |
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face_cascade_name = args.face_cascade |
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eyes_cascade_name = args.eyes_cascade |
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face_cascade = cv.CascadeClassifier() |
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eyes_cascade = cv.CascadeClassifier() |
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#-- 1. Load the cascades |
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if not face_cascade.load(face_cascade_name): |
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print('--(!)Error loading face cascade') |
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exit(0) |
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if not eyes_cascade.load(eyes_cascade_name): |
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print('--(!)Error loading eyes cascade') |
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exit(0) |
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camera_device = args.camera |
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#-- 2. Read the video stream |
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cap = cv.VideoCapture(camera_device) |
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if not cap.isOpened: |
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print('--(!)Error opening video capture') |
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exit(0) |
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while True: |
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ret, frame = cap.read() |
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if frame is None: |
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print('--(!) No captured frame -- Break!') |
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break |
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detectAndDisplay(frame) |
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if cv.waitKey(10) == 27: |
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break |
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from __future__ import print_function |
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from __future__ import division |
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import cv2 as cv |
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import numpy as np |
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import argparse |
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import os |
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def loadExposureSeq(path): |
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images = [] |
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times = [] |
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with open(os.path.join(path, 'list.txt')) as f: |
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content = f.readlines() |
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for line in content: |
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tokens = line.split() |
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images.append(cv.imread(os.path.join(path, tokens[0]))) |
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times.append(1 / float(tokens[1])) |
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return images, np.asarray(times, dtype=np.float32) |
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parser = argparse.ArgumentParser(description='Code for High Dynamic Range Imaging tutorial.') |
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parser.add_argument('--input', type=str, help='Path to the directory that contains images and exposure times.') |
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args = parser.parse_args() |
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if not args.input: |
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parser.print_help() |
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exit(0) |
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## [Load images and exposure times] |
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images, times = loadExposureSeq(args.input) |
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## [Load images and exposure times] |
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## [Estimate camera response] |
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calibrate = cv.createCalibrateDebevec() |
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response = calibrate.process(images, times) |
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## [Estimate camera response] |
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## [Make HDR image] |
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merge_debevec = cv.createMergeDebevec() |
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hdr = merge_debevec.process(images, times, response) |
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## [Make HDR image] |
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## [Tonemap HDR image] |
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tonemap = cv.createTonemapDurand(2.2) |
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ldr = tonemap.process(hdr) |
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## [Tonemap HDR image] |
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## [Perform exposure fusion] |
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merge_mertens = cv.createMergeMertens() |
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fusion = merge_mertens.process(images) |
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## [Perform exposure fusion] |
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## [Write results] |
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cv.imwrite('fusion.png', fusion * 255) |
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cv.imwrite('ldr.png', ldr * 255) |
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cv.imwrite('hdr.hdr', hdr) |
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## [Write results] |
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