mirror of
https://github.com/opencv/opencv.git
synced 2024-11-25 11:40:44 +08:00
194 lines
5.6 KiB
C++
194 lines
5.6 KiB
C++
#if defined(__linux__) || defined(LINUX) || defined(__APPLE__) || defined(ANDROID)
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#include <opencv2/core/core.hpp>
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#include <opencv2/core/internal.hpp>
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#include <opencv2/imgproc/imgproc.hpp>
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#include <opencv2/highgui/highgui.hpp>
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#include <opencv2/objdetect/objdetect.hpp>
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#include "opencv2/contrib/detection_based_tracker.hpp"
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#include <vector>
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#include <iostream>
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#include <stdio.h>
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#define DEBUGLOGS 1
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#ifdef ANDROID
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#include <android/log.h>
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#define LOG_TAG "DETECTIONBASEDTRACKER__TEST_APPLICAT"
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#define LOGD0(...) ((void)__android_log_print(ANDROID_LOG_DEBUG, LOG_TAG, __VA_ARGS__))
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#define LOGI0(...) ((void)__android_log_print(ANDROID_LOG_INFO, LOG_TAG, __VA_ARGS__))
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#define LOGW0(...) ((void)__android_log_print(ANDROID_LOG_WARN, LOG_TAG, __VA_ARGS__))
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#define LOGE0(...) ((void)__android_log_print(ANDROID_LOG_ERROR, LOG_TAG, __VA_ARGS__))
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#else
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#include <stdio.h>
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#define LOGD0(_str, ...) do{printf(_str , ## __VA_ARGS__); printf("\n");fflush(stdout);} while(0)
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#define LOGI0(_str, ...) do{printf(_str , ## __VA_ARGS__); printf("\n");fflush(stdout);} while(0)
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#define LOGW0(_str, ...) do{printf(_str , ## __VA_ARGS__); printf("\n");fflush(stdout);} while(0)
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#define LOGE0(_str, ...) do{printf(_str , ## __VA_ARGS__); printf("\n");fflush(stdout);} while(0)
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#endif
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#if DEBUGLOGS
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#define LOGD(_str, ...) LOGD0(_str , ## __VA_ARGS__)
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#define LOGI(_str, ...) LOGI0(_str , ## __VA_ARGS__)
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#define LOGW(_str, ...) LOGW0(_str , ## __VA_ARGS__)
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#define LOGE(_str, ...) LOGE0(_str , ## __VA_ARGS__)
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#else
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#define LOGD(...) do{} while(0)
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#define LOGI(...) do{} while(0)
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#define LOGW(...) do{} while(0)
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#define LOGE(...) do{} while(0)
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#endif
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using namespace cv;
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using namespace std;
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#define ORIGINAL 0
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#define SHOULD_USE_EXTERNAL_BUFFERS 1
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static void usage()
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{
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LOGE0("usage: filepattern outfilepattern cascadefile");
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LOGE0("\t where ");
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LOGE0("\t filepattern --- pattern for the paths to the source images");
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LOGE0("\t (e.g.\"./Videos/FACESJPG2/Faces2_%%08d.jpg\" ");
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LOGE0("\t outfilepattern --- pattern for the paths for images which will be generated");
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LOGE0("\t (e.g.\"./resFaces2_%%08d.jpg\" ");
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LOGE0("\t cascadefile --- path to the cascade file");
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LOGE0("\t (e.g.\"opencv/data/lbpcascades/lbpcascade_frontalface.xml\" ");
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}
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class CascadeDetectorAdapter: public DetectionBasedTracker::IDetector
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{
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public:
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CascadeDetectorAdapter(cv::Ptr<cv::CascadeClassifier> detector):
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Detector(detector)
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{
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CV_Assert(!detector.empty());
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}
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void detect(const cv::Mat &Image, std::vector<cv::Rect> &objects)
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{
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Detector->detectMultiScale(Image, objects, 1.1, 3, 0, minObjSize, maxObjSize);
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}
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virtual ~CascadeDetectorAdapter()
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{}
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private:
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CascadeDetectorAdapter();
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cv::Ptr<cv::CascadeClassifier> Detector;
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};
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static int test_FaceDetector(int argc, char *argv[])
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{
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if (argc < 4)
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{
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usage();
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return -1;
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}
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const char* filepattern=argv[1];
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const char* outfilepattern=argv[2];
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const char* cascadefile=argv[3];
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LOGD0("filepattern='%s'", filepattern);
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LOGD0("outfilepattern='%s'", outfilepattern);
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LOGD0("cascadefile='%s'", cascadefile);
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vector<Mat> images;
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{
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char filename[256];
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for(int n=1; ; n++)
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{
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snprintf(filename, sizeof(filename), filepattern, n);
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LOGD("filename='%s'", filename);
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Mat m0;
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m0=imread(filename);
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if (m0.empty())
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{
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LOGI0("Cannot read the file --- break");
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break;
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}
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images.push_back(m0);
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}
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LOGD("read %d images", (int)images.size());
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}
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std::string cascadeFrontalfilename=cascadefile;
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cv::Ptr<cv::CascadeClassifier> cascade = new cv::CascadeClassifier(cascadeFrontalfilename);
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cv::Ptr<DetectionBasedTracker::IDetector> MainDetector = new CascadeDetectorAdapter(cascade);
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cascade = new cv::CascadeClassifier(cascadeFrontalfilename);
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cv::Ptr<DetectionBasedTracker::IDetector> TrackingDetector = new CascadeDetectorAdapter(cascade);
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DetectionBasedTracker::Parameters params;
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DetectionBasedTracker fd(MainDetector, TrackingDetector, params);
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fd.run();
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Mat gray;
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Mat m;
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int64 tprev=getTickCount();
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double freq=getTickFrequency();
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int num_images=images.size();
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for(int n=1; n <= num_images; n++)
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{
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int64 tcur=getTickCount();
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int64 dt=tcur-tprev;
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tprev=tcur;
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double t_ms=((double)dt)/freq * 1000.0;
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LOGD("\n\nSTEP n=%d from prev step %f ms\n", n, t_ms);
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m=images[n-1];
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CV_Assert(! m.empty());
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cvtColor(m, gray, CV_BGR2GRAY);
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fd.process(gray);
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vector<Rect> result;
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fd.getObjects(result);
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for(size_t i=0; i < result.size(); i++)
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{
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Rect r=result[i];
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CV_Assert(r.area() > 0);
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Point tl=r.tl();
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Point br=r.br();
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Scalar color=Scalar(0, 250, 0);
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rectangle(m, tl, br, color, 3);
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}
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}
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char outfilename[256];
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for(int n=1; n <= num_images; n++)
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{
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snprintf(outfilename, sizeof(outfilename), outfilepattern, n);
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LOGD("outfilename='%s'", outfilename);
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m=images[n-1];
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imwrite(outfilename, m);
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}
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fd.stop();
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return 0;
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}
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int main(int argc, char *argv[])
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{
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return test_FaceDetector(argc, argv);
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}
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#else // #if defined(__linux__) || defined(LINUX) || defined(__APPLE__) || defined(ANDROID)
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#include <stdio.h>
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int main()
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{
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printf("This sample works for UNIX or ANDROID only\n");
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return 0;
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}
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#endif
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