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164 lines
5.5 KiB
C++
164 lines
5.5 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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#include "test_precomp.hpp"
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//#define DEBUG_TEST
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#ifdef DEBUG_TEST
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#include <opencv2/highgui.hpp>
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#endif
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namespace opencv_test { namespace {
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//using namespace cv::tracking;
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#define TESTSET_NAMES testing::Values("david", "dudek", "faceocc2")
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const string TRACKING_DIR = "tracking";
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const string FOLDER_IMG = "data";
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const string FOLDER_OMIT_INIT = "initOmit";
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#include "test_trackers.impl.hpp"
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//[TESTDATA]
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PARAM_TEST_CASE(DistanceAndOverlap, string)
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{
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string dataset;
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virtual void SetUp()
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{
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dataset = GET_PARAM(0);
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}
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};
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TEST_P(DistanceAndOverlap, MIL)
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{
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TrackerTest<Tracker, Rect> test(TrackerMIL::create(), dataset, 30, .65f, NoTransform);
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test.run();
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}
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TEST_P(DistanceAndOverlap, Shifted_Data_MIL)
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{
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TrackerTest<Tracker, Rect> test(TrackerMIL::create(), dataset, 30, .6f, CenterShiftLeft);
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test.run();
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}
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/***************************************************************************************/
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//Tests with scaled initial window
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TEST_P(DistanceAndOverlap, Scaled_Data_MIL)
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{
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TrackerTest<Tracker, Rect> test(TrackerMIL::create(), dataset, 30, .7f, Scale_1_1);
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test.run();
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}
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TEST_P(DistanceAndOverlap, GOTURN)
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{
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std::string model = cvtest::findDataFile("dnn/gsoc2016-goturn/goturn.prototxt");
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std::string weights = cvtest::findDataFile("dnn/gsoc2016-goturn/goturn.caffemodel", false);
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cv::TrackerGOTURN::Params params;
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params.modelTxt = model;
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params.modelBin = weights;
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TrackerTest<Tracker, Rect> test(TrackerGOTURN::create(params), dataset, 35, .35f, NoTransform);
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test.run();
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}
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INSTANTIATE_TEST_CASE_P(Tracking, DistanceAndOverlap, TESTSET_NAMES);
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static bool checkIOU(const Rect& r0, const Rect& r1, double threshold)
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{
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int interArea = (r0 & r1).area();
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double iouVal = (interArea * 1.0 )/ (r0.area() + r1.area() - interArea);;
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if (iouVal > threshold)
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return true;
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else
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{
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std::cout <<"Unmatched IOU: expect IOU val ("<<iouVal <<") > the IOU threadhold ("<<threshold<<")! Box 0 is "
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<< r0 <<", and Box 1 is "<<r1<< std::endl;
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return false;
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}
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}
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static void checkTrackingAccuracy(cv::Ptr<Tracker>& tracker, double iouThreshold = 0.7)
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{
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// Template image
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Mat img0 = imread(findDataFile("tracking/bag/00000001.jpg"), 1);
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// Tracking image sequence.
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std::vector<Mat> imgs;
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imgs.push_back(imread(findDataFile("tracking/bag/00000002.jpg"), 1));
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imgs.push_back(imread(findDataFile("tracking/bag/00000003.jpg"), 1));
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imgs.push_back(imread(findDataFile("tracking/bag/00000004.jpg"), 1));
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imgs.push_back(imread(findDataFile("tracking/bag/00000005.jpg"), 1));
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imgs.push_back(imread(findDataFile("tracking/bag/00000006.jpg"), 1));
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cv::Rect roi(325, 164, 100, 100);
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std::vector<Rect> targetRois;
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targetRois.push_back(cv::Rect(278, 133, 99, 104));
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targetRois.push_back(cv::Rect(293, 88, 93, 110));
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targetRois.push_back(cv::Rect(287, 76, 89, 116));
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targetRois.push_back(cv::Rect(297, 74, 82, 122));
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targetRois.push_back(cv::Rect(311, 83, 78, 125));
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tracker->init(img0, roi);
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CV_Assert(targetRois.size() == imgs.size());
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for (int i = 0; i < (int)imgs.size(); i++)
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{
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bool res = tracker->update(imgs[i], roi);
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ASSERT_TRUE(res);
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ASSERT_TRUE(checkIOU(roi, targetRois[i], iouThreshold)) << cv::format("Fail at img %d.",i);
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}
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}
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TEST(GOTURN, accuracy)
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{
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std::string model = cvtest::findDataFile("dnn/gsoc2016-goturn/goturn.prototxt");
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std::string weights = cvtest::findDataFile("dnn/gsoc2016-goturn/goturn.caffemodel", false);
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cv::TrackerGOTURN::Params params;
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params.modelTxt = model;
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params.modelBin = weights;
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cv::Ptr<Tracker> tracker = TrackerGOTURN::create(params);
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// TODO! GOTURN have low accuracy. Try to remove this api at 5.x.
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checkTrackingAccuracy(tracker, 0.08);
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}
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TEST(DaSiamRPN, accuracy)
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{
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std::string model = cvtest::findDataFile("dnn/onnx/models/dasiamrpn_model.onnx", false);
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std::string kernel_r1 = cvtest::findDataFile("dnn/onnx/models/dasiamrpn_kernel_r1.onnx", false);
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std::string kernel_cls1 = cvtest::findDataFile("dnn/onnx/models/dasiamrpn_kernel_cls1.onnx", false);
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cv::TrackerDaSiamRPN::Params params;
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params.model = model;
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params.kernel_r1 = kernel_r1;
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params.kernel_cls1 = kernel_cls1;
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cv::Ptr<Tracker> tracker = TrackerDaSiamRPN::create(params);
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checkTrackingAccuracy(tracker, 0.7);
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}
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TEST(NanoTrack, accuracy_NanoTrack_V1)
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{
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std::string backbonePath = cvtest::findDataFile("dnn/onnx/models/nanotrack_backbone_sim.onnx", false);
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std::string neckheadPath = cvtest::findDataFile("dnn/onnx/models/nanotrack_head_sim.onnx", false);
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cv::TrackerNano::Params params;
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params.backbone = backbonePath;
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params.neckhead = neckheadPath;
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cv::Ptr<Tracker> tracker = TrackerNano::create(params);
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checkTrackingAccuracy(tracker);
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}
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TEST(NanoTrack, accuracy_NanoTrack_V2)
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{
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std::string backbonePath = cvtest::findDataFile("dnn/onnx/models/nanotrack_backbone_sim_v2.onnx", false);
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std::string neckheadPath = cvtest::findDataFile("dnn/onnx/models/nanotrack_head_sim_v2.onnx", false);
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cv::TrackerNano::Params params;
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params.backbone = backbonePath;
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params.neckhead = neckheadPath;
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cv::Ptr<Tracker> tracker = TrackerNano::create(params);
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checkTrackingAccuracy(tracker, 0.69);
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}
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}} // namespace opencv_test::
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