chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
@@ -0,0 +1,16 @@
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{
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"missing_consts": {
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"Video" : {
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"private" : [
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["CV_LKFLOW_INITIAL_GUESSES", 4 ],
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["CV_LKFLOW_GET_MIN_EIGENVALS", 8 ]
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]
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}
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},
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"func_arg_fix" : {
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"calcOpticalFlowPyrLK" : { "prevPts" : {"ctype" : "vector_Point2f"},
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"nextPts" : {"ctype" : "vector_Point2f"},
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"status" : {"ctype" : "vector_uchar"},
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"err" : {"ctype" : "vector_float"} }
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}
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}
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@@ -0,0 +1,43 @@
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package org.opencv.test.video;
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import org.opencv.test.OpenCVTestCase;
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public class BackgroundSubtractorMOGTest extends OpenCVTestCase {
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public void testApplyMatMat() {
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fail("Not yet implemented");
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/*
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BackgroundSubtractorMOG backGroundSubtract = new BackgroundSubtractorMOG();
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Point bottomRight = new Point(rgbLena.cols() / 2, rgbLena.rows() / 2);
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Point topLeft = new Point(0, 0);
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Scalar color = new Scalar(128);
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Mat mask = new Mat(rgbLena.size(), CvType.CV_16UC3, new Scalar(1));
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Imgproc.rectangle(rgbLena, bottomRight, topLeft, color, Imgproc.FILLED);
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backGroundSubtract.apply(rgbLena, mask);
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Mat truth = new Mat(rgbLena.size(), rgbLena.type(), new Scalar(0));
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Imgproc.rectangle(truth, bottomRight, topLeft, color, Imgproc.FILLED);
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assertMatEqual(truth, rgbLena);
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*/
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}
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public void testApplyMatMatDouble() {
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fail("Not yet implemented");
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}
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public void testBackgroundSubtractorMOG() {
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fail("Not yet implemented");
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}
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public void testBackgroundSubtractorMOGIntIntDouble() {
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fail("Not yet implemented");
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}
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public void testBackgroundSubtractorMOGIntIntDoubleDouble() {
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fail("Not yet implemented");
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}
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}
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@@ -0,0 +1,38 @@
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package org.opencv.test.video;
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import org.opencv.test.OpenCVTestCase;
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import org.opencv.video.KalmanFilter;
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public class KalmanFilterTest extends OpenCVTestCase {
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public void testCorrect() {
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fail("Not yet implemented");
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}
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public void testKalmanFilter() {
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KalmanFilter kf = new KalmanFilter();
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assertNotNull(kf);
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}
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public void testKalmanFilterIntInt() {
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fail("Not yet implemented");
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}
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public void testKalmanFilterIntIntInt() {
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fail("Not yet implemented");
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}
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public void testKalmanFilterIntIntIntInt() {
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fail("Not yet implemented");
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}
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public void testPredict() {
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fail("Not yet implemented");
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}
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public void testPredictMat() {
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fail("Not yet implemented");
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}
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}
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@@ -0,0 +1,105 @@
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package org.opencv.test.video;
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import java.io.File;
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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.CvException;
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import org.opencv.core.Mat;
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import org.opencv.core.Rect;
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import org.opencv.dnn.Dnn;
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import org.opencv.dnn.Net;
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import org.opencv.test.OpenCVTestCase;
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import org.opencv.video.Tracker;
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import org.opencv.video.TrackerGOTURN;
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import org.opencv.video.TrackerGOTURN_Params;
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import org.opencv.video.TrackerNano;
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import org.opencv.video.TrackerNano_Params;
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import org.opencv.video.TrackerVit;
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import org.opencv.video.TrackerVit_Params;
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import org.opencv.video.TrackerMIL;
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public class TrackerCreateTest extends OpenCVTestCase {
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private final static String ENV_OPENCV_DNN_TEST_DATA_PATH = "OPENCV_DNN_TEST_DATA_PATH";
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private final static String ENV_OPENCV_TEST_DATA_PATH = "OPENCV_TEST_DATA_PATH";
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private String testDataPath;
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private String modelsDataPath;
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@Override
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protected void setUp() throws Exception {
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super.setUp();
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// relys on https://developer.android.com/reference/java/lang/System
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isTestCaseEnabled = System.getProperties().getProperty("java.vm.name") != "Dalvik";
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if (!isTestCaseEnabled) {
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return;
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}
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testDataPath = System.getenv(ENV_OPENCV_TEST_DATA_PATH);
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if (testDataPath == null) {
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throw new Exception(ENV_OPENCV_TEST_DATA_PATH + " has to be defined!");
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}
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modelsDataPath = System.getenv(ENV_OPENCV_DNN_TEST_DATA_PATH);
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if (modelsDataPath == null) {
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modelsDataPath = testDataPath;
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}
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if (isTestCaseEnabled) {
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testDataPath = System.getenv(ENV_OPENCV_DNN_TEST_DATA_PATH);
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if (testDataPath == null)
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testDataPath = System.getenv(ENV_OPENCV_TEST_DATA_PATH);
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if (testDataPath == null)
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throw new Exception(ENV_OPENCV_TEST_DATA_PATH + " has to be defined!");
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}
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}
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public void testCreateTrackerGOTURN() {
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Net net;
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try {
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String protoFile = new File(testDataPath, "dnn/gsoc2016-goturn/goturn.prototxt").toString();
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String weightsFile = new File(modelsDataPath, "dnn/gsoc2016-goturn/goturn.caffemodel").toString();
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net = Dnn.readNetFromCaffe(protoFile, weightsFile);
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} catch (CvException e) {
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return;
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}
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Tracker tracker = TrackerGOTURN.create(net);
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assert(tracker != null);
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}
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public void testCreateTrackerNano() {
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Net backbone;
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Net neckhead;
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try {
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String backboneFile = new File(modelsDataPath, "dnn/onnx/models/nanotrack_backbone_sim_v2.onnx").toString();
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String neckheadFile = new File(modelsDataPath, "dnn/onnx/models/nanotrack_head_sim_v2.onnx").toString();
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backbone = Dnn.readNet(backboneFile);
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neckhead = Dnn.readNet(neckheadFile);
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} catch (CvException e) {
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return;
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}
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Tracker tracker = TrackerNano.create(backbone, neckhead);
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assert(tracker != null);
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}
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public void testCreateTrackerVit() {
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Net net;
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try {
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String backboneFile = new File(modelsDataPath, "dnn/onnx/models/vitTracker.onnx").toString();
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net = Dnn.readNet(backboneFile);
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} catch (CvException e) {
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return;
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}
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Tracker tracker = TrackerVit.create(net);
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assert(tracker != null);
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}
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public void testCreateTrackerMIL() {
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Tracker tracker = TrackerMIL.create();
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assert(tracker != null);
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Mat mat = new Mat(100, 100, CvType.CV_8UC1);
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Rect rect = new Rect(10, 10, 30, 30);
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tracker.init(mat, rect); // should not crash (https://github.com/opencv/opencv/issues/19915)
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}
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}
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@@ -0,0 +1,99 @@
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package org.opencv.test.video;
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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.MatOfByte;
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import org.opencv.core.MatOfFloat;
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import org.opencv.core.MatOfPoint2f;
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import org.opencv.core.Point;
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import org.opencv.core.Size;
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import org.opencv.test.OpenCVTestCase;
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import org.opencv.video.Video;
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public class VideoTest extends OpenCVTestCase {
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private MatOfFloat err = null;
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private int h;
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private MatOfPoint2f nextPts = null;
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private MatOfPoint2f prevPts = null;
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private int shift1;
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private int shift2;
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private MatOfByte status = null;
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private Mat subLena1 = null;
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private Mat subLena2 = null;
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private int w;
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@Override
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protected void setUp() throws Exception {
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super.setUp();
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shift1 = 10;
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shift2 = 17;
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w = (int)(rgbLena.cols() / 2);
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h = (int)(rgbLena.rows() / 2);
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subLena1 = rgbLena.submat(shift1, h + shift1, shift1, w + shift1);
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subLena2 = rgbLena.submat(shift2, h + shift2, shift2, w + shift2);
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prevPts = new MatOfPoint2f(new Point(11d, 8d), new Point(5d, 5d), new Point(10d, 10d));
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nextPts = new MatOfPoint2f();
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status = new MatOfByte();
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err = new MatOfFloat();
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}
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public void testCalcGlobalOrientation() {
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fail("Not yet implemented");
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}
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public void testCalcMotionGradientMatMatMatDoubleDouble() {
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fail("Not yet implemented");
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}
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public void testCalcMotionGradientMatMatMatDoubleDoubleInt() {
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fail("Not yet implemented");
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}
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public void testCalcOpticalFlowFarneback() {
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fail("Not yet implemented");
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}
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public void testCalcOpticalFlowPyrLKMatMatListOfPointListOfPointListOfByteListOfFloat() {
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Video.calcOpticalFlowPyrLK(subLena1, subLena2, prevPts, nextPts, status, err);
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assertEquals(3, Core.countNonZero(status));
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}
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public void testCalcOpticalFlowPyrLKMatMatListOfPointListOfPointListOfByteListOfFloatSize() {
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Size sz = new Size(3, 3);
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Video.calcOpticalFlowPyrLK(subLena1, subLena2, prevPts, nextPts, status, err, sz, 3);
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assertEquals(0, Core.countNonZero(status));
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}
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public void testCalcOpticalFlowPyrLKMatMatListOfPointListOfPointListOfByteListOfFloatSizeIntTermCriteriaDoubleIntDouble() {
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fail("Not yet implemented");
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}
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public void testCamShift() {
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fail("Not yet implemented");
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}
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public void testEstimateRigidTransform() {
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fail("Not yet implemented");
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}
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public void testMeanShift() {
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fail("Not yet implemented");
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}
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public void testSegmentMotion() {
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fail("Not yet implemented");
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}
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public void testUpdateMotionHistory() {
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fail("Not yet implemented");
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}
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}
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