yolov3執行及儲存檢測視訊（包括攝像頭）
阿新 • • 發佈：2019-02-04
新程式碼：可用，如果不想在老程式碼上折騰更改，可以直接根據下面的新地址拉取程式碼。 （注意看Readme）
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由於以前上傳的專案有點點小問題，完整更新專案及說明如下連結。
---------------------更新20180703---------------------
老程式碼：同樣可用，就是儲存視訊時會閃爍，現在評論區出現了一個解決方案，歡迎大家嘗試（拉到文末檢視）。
最近一段時間配置運行了下YOLO3網路，官方專案地址：https://pjreddie.com/darknet/yolo/
假設你的專案路徑為./darknet，需要改動的主要有兩個檔案，分別是位於./darknet/src/路徑下的demo.c和image.c檔案。
（1）首先在image.c檔案中新增save_video函式的定義，程式碼及截圖位置如下：
void save_video(image p, CvVideoWriter *mVideoWriter) { image copy = copy_image(p); if(p.c == 3) rgbgr_image(copy); int x,y,k; IplImage *disp = cvCreateImage(cvSize(p.w,p.h), IPL_DEPTH_8U, p.c); int step = disp->widthStep; for(y = 0; y < p.h; ++y){ for(x = 0; x < p.w; ++x){ for(k= 0; k < p.c; ++k){ disp->imageData[y*step + x*p.c + k] = (unsigned char)(get_pixel(copy,x,y,k)*255); } } } cvWriteFrame(mVideoWriter,disp); cvReleaseImage(&disp); free_image(copy); }
對應位置截圖如下：
（2） 然後更改demo.c檔案程式碼，由於改動內容有多處，因此這裡帖是完整的demo.c檔案程式碼，每一組//*********rs20180415***********之間程式碼就是新新增的程式碼內容，可自行對比，包括設定你輸出檢測視訊的名稱和幀率。
#include "network.h" #include "detection_layer.h" #include "region_layer.h" #include "cost_layer.h" #include "utils.h" #include "parser.h" #include "box.h" #include "image.h" #include "demo.h" #include <sys/time.h> #define DEMO 1 //*********rs20180415*********** #define SAVEVIDEO //*********rs20180415*********** #ifdef OPENCV //*********rs20180415*********** #ifdef SAVEVIDEO static CvVideoWriter *mVideoWriter; #endif //*********rs20180415*********** static char **demo_names; static image **demo_alphabet; static int demo_classes; static network *net; static image buff [3]; static image buff_letter[3]; static int buff_index = 0; static CvCapture * cap; static IplImage * ipl; static float fps = 0; static float demo_thresh = 0; static float demo_hier = .5; static int running = 0; static int demo_frame = 3; static int demo_index = 0; static float **predictions; static float *avg; static int demo_done = 0; static int demo_total = 0; double demo_time; detection *get_network_boxes(network *net, int w, int h, float thresh, float hier, int *map, int relative, int *num); int size_network(network *net) { int i; int count = 0; for(i = 0; i < net->n; ++i){ layer l = net->layers[i]; if(l.type == YOLO || l.type == REGION || l.type == DETECTION){ count += l.outputs; } } return count; } void remember_network(network *net) { int i; int count = 0; for(i = 0; i < net->n; ++i){ layer l = net->layers[i]; if(l.type == YOLO || l.type == REGION || l.type == DETECTION){ memcpy(predictions[demo_index] + count, net->layers[i].output, sizeof(float) * l.outputs); count += l.outputs; } } } detection *avg_predictions(network *net, int *nboxes) { int i, j; int count = 0; fill_cpu(demo_total, 0, avg, 1); for(j = 0; j < demo_frame; ++j){ axpy_cpu(demo_total, 1./demo_frame, predictions[j], 1, avg, 1); } for(i = 0; i < net->n; ++i){ layer l = net->layers[i]; if(l.type == YOLO || l.type == REGION || l.type == DETECTION){ memcpy(l.output, avg + count, sizeof(float) * l.outputs); count += l.outputs; } } detection *dets = get_network_boxes(net, buff[0].w, buff[0].h, demo_thresh, demo_hier, 0, 1, nboxes); return dets; } void *detect_in_thread(void *ptr) { running = 1; float nms = .4; layer l = net->layers[net->n-1]; float *X = buff_letter[(buff_index+2)%3].data; network_predict(net, X); /* if(l.type == DETECTION){ get_detection_boxes(l, 1, 1, demo_thresh, probs, boxes, 0); } else */ remember_network(net); detection *dets = 0; int nboxes = 0; dets = avg_predictions(net, &nboxes); /* int i,j; box zero = {0}; int classes = l.classes; for(i = 0; i < demo_detections; ++i){ avg[i].objectness = 0; avg[i].bbox = zero; memset(avg[i].prob, 0, classes*sizeof(float)); for(j = 0; j < demo_frame; ++j){ axpy_cpu(classes, 1./demo_frame, dets[j][i].prob, 1, avg[i].prob, 1); avg[i].objectness += dets[j][i].objectness * 1./demo_frame; avg[i].bbox.x += dets[j][i].bbox.x * 1./demo_frame; avg[i].bbox.y += dets[j][i].bbox.y * 1./demo_frame; avg[i].bbox.w += dets[j][i].bbox.w * 1./demo_frame; avg[i].bbox.h += dets[j][i].bbox.h * 1./demo_frame; } //copy_cpu(classes, dets[0][i].prob, 1, avg[i].prob, 1); //avg[i].objectness = dets[0][i].objectness; } */ if (nms > 0) do_nms_obj(dets, nboxes, l.classes, nms); printf("\033[2J"); printf("\033[1;1H"); printf("\nFPS:%.1f\n",fps); printf("Objects:\n\n"); image display = buff[(buff_index+2) % 3]; draw_detections(display, dets, nboxes, demo_thresh, demo_names, demo_alphabet, demo_classes); free_detections(dets, nboxes); demo_index = (demo_index + 1)%demo_frame; running = 0; return 0; } void *fetch_in_thread(void *ptr) { int status = fill_image_from_stream(cap, buff[buff_index]); letterbox_image_into(buff[buff_index], net->w, net->h, buff_letter[buff_index]); if(status == 0) demo_done = 1; return 0; } void *display_in_thread(void *ptr) { show_image_cv(buff[(buff_index + 1)%3], "Demo", ipl); int c = cvWaitKey(1); if (c != -1) c = c%256; if (c == 27) { demo_done = 1; return 0; } else if (c == 82) { demo_thresh += .02; } else if (c == 84) { demo_thresh -= .02; if(demo_thresh <= .02) demo_thresh = .02; } else if (c == 83) { demo_hier += .02; } else if (c == 81) { demo_hier -= .02; if(demo_hier <= .0) demo_hier = .0; } return 0; } void *display_loop(void *ptr) { while(1){ display_in_thread(0); } } void *detect_loop(void *ptr) { while(1){ detect_in_thread(0); } } void demo(char *cfgfile, char *weightfile, float thresh, int cam_index, const char *filename, char **names, int classes, int delay, char *prefix, int avg_frames, float hier, int w, int h, int frames, int fullscreen) { //demo_frame = avg_frames; image **alphabet = load_alphabet(); demo_names = names; demo_alphabet = alphabet; demo_classes = classes; demo_thresh = thresh; demo_hier = hier; printf("Demo\n"); net = load_network(cfgfile, weightfile, 0); set_batch_network(net, 1); pthread_t detect_thread; pthread_t fetch_thread; srand(2222222); int i; demo_total = size_network(net); predictions = calloc(demo_frame, sizeof(float*)); for (i = 0; i < demo_frame; ++i){ predictions[i] = calloc(demo_total, sizeof(float)); } avg = calloc(demo_total, sizeof(float)); if(filename){ printf("video file: %s\n", filename); cap = cvCaptureFromFile(filename); //*********rs20180415*********** #ifdef SAVEVIDEO if(cap){ int mfps = cvGetCaptureProperty(cap,CV_CAP_PROP_FPS); //local video file，needn't change mVideoWriter=cvCreateVideoWriter("Output.avi",CV_FOURCC('M','J','P','G'),mfps,cvSize(cvGetCaptureProperty(cap,CV_CAP_PROP_FRAME_WIDTH),cvGetCaptureProperty(cap,CV_CAP_PROP_FRAME_HEIGHT)),1); } #endif //*********rs20180415*********** }else{ cap = cvCaptureFromCAM(cam_index); //*********rs20180415*********** #ifdef SAVEVIDEO if(cap){ //int mfps = cvGetCaptureProperty(cap,CV_CAP_PROP_FPS); //webcam video file，need change. int mfps = 25; //the output video FPS，you can set here. mVideoWriter=cvCreateVideoWriter("Output_webcam.avi",CV_FOURCC('M','J','P','G'),mfps,cvSize(cvGetCaptureProperty(cap,CV_CAP_PROP_FRAME_WIDTH),cvGetCaptureProperty(cap,CV_CAP_PROP_FRAME_HEIGHT)),1); } #endif //*********rs20180415*********** if(w){ cvSetCaptureProperty(cap, CV_CAP_PROP_FRAME_WIDTH, w); } if(h){ cvSetCaptureProperty(cap, CV_CAP_PROP_FRAME_HEIGHT, h); } if(frames){ cvSetCaptureProperty(cap, CV_CAP_PROP_FPS, frames); } } if(!cap) error("Couldn't connect to webcam.\n"); buff[0] = get_image_from_stream(cap); buff[1] = copy_image(buff[0]); buff[2] = copy_image(buff[0]); buff_letter[0] = letterbox_image(buff[0], net->w, net->h); buff_letter[1] = letterbox_image(buff[0], net->w, net->h); buff_letter[2] = letterbox_image(buff[0], net->w, net->h); ipl = cvCreateImage(cvSize(buff[0].w,buff[0].h), IPL_DEPTH_8U, buff[0].c); int count = 0; if(!prefix){ cvNamedWindow("Demo", CV_WINDOW_NORMAL); if(fullscreen){ cvSetWindowProperty("Demo", CV_WND_PROP_FULLSCREEN, CV_WINDOW_FULLSCREEN); } else { cvMoveWindow("Demo", 0, 0); cvResizeWindow("Demo", 1352, 1013); } } demo_time = what_time_is_it_now(); while(!demo_done){ buff_index = (buff_index + 1) %3; if(pthread_create(&fetch_thread, 0, fetch_in_thread, 0)) error("Thread creation failed"); if(pthread_create(&detect_thread, 0, detect_in_thread, 0)) error("Thread creation failed"); if(!prefix){ //*********rs20180415*********** #ifdef SAVEVIDEO save_video(buff[0],mVideoWriter); #endif //*********rs20180415*********** fps = 1./(what_time_is_it_now() - demo_time); demo_time = what_time_is_it_now(); display_in_thread(0); }else{ char name[256]; sprintf(name, "%s_%08d", prefix, count); //*********rs20180415*********** #ifdef SAVEVIDEO save_video(buff[0],mVideoWriter); #else save_image(buff[(buff_index + 1)%3], name); #endif //*********rs20180415*********** } pthread_join(fetch_thread, 0); pthread_join(detect_thread, 0); ++count; } } /* void demo_compare(char *cfg1, char *weight1, char *cfg2, char *weight2, float thresh, int cam_index, const char *filename, char **names, int classes, int delay, char *prefix, int avg_frames, float hier, int w, int h, int frames, int fullscreen) { demo_frame = avg_frames; predictions = calloc(demo_frame, sizeof(float*)); image **alphabet = load_alphabet(); demo_names = names; demo_alphabet = alphabet; demo_classes = classes; demo_thresh = thresh; demo_hier = hier; printf("Demo\n"); net = load_network(cfg1, weight1, 0); set_batch_network(net, 1); pthread_t detect_thread; pthread_t fetch_thread; srand(2222222); if(filename){ printf("video file: %s\n", filename); cap = cvCaptureFromFile(filename); }else{ cap = cvCaptureFromCAM(cam_index); if(w){ cvSetCaptureProperty(cap, CV_CAP_PROP_FRAME_WIDTH, w); } if(h){ cvSetCaptureProperty(cap, CV_CAP_PROP_FRAME_HEIGHT, h); } if(frames){ cvSetCaptureProperty(cap, CV_CAP_PROP_FPS, frames); } } if(!cap) error("Couldn't connect to webcam.\n"); layer l = net->layers[net->n-1]; demo_detections = l.n*l.w*l.h; int j; avg = (float *) calloc(l.outputs, sizeof(float)); for(j = 0; j < demo_frame; ++j) predictions[j] = (float *) calloc(l.outputs, sizeof(float)); boxes = (box *)calloc(l.w*l.h*l.n, sizeof(box)); probs = (float **)calloc(l.w*l.h*l.n, sizeof(float *)); for(j = 0; j < l.w*l.h*l.n; ++j) probs[j] = (float *)calloc(l.classes+1, sizeof(float)); buff[0] = get_image_from_stream(cap); buff[1] = copy_image(buff[0]); buff[2] = copy_image(buff[0]); buff_letter[0] = letterbox_image(buff[0], net->w, net->h); buff_letter[1] = letterbox_image(buff[0], net->w, net->h); buff_letter[2] = letterbox_image(buff[0], net->w, net->h); ipl = cvCreateImage(cvSize(buff[0].w,buff[0].h), IPL_DEPTH_8U, buff[0].c); int count = 0; if(!prefix){ cvNamedWindow("Demo", CV_WINDOW_NORMAL); if(fullscreen){ cvSetWindowProperty("Demo", CV_WND_PROP_FULLSCREEN, CV_WINDOW_FULLSCREEN); } else { cvMoveWindow("Demo", 0, 0); cvResizeWindow("Demo", 1352, 1013); } } demo_time = what_time_is_it_now(); while(!demo_done){ buff_index = (buff_index + 1) %3; if(pthread_create(&fetch_thread, 0, fetch_in_thread, 0)) error("Thread creation failed"); if(pthread_create(&detect_thread, 0, detect_in_thread, 0)) error("Thread creation failed"); if(!prefix){ fps = 1./(what_time_is_it_now() - demo_time); demo_time = what_time_is_it_now(); display_in_thread(0); }else{ char name[256]; sprintf(name, "%s_%08d", prefix, count); save_image(buff[(buff_index + 1)%3], name); } pthread_join(fetch_thread, 0); pthread_join(detect_thread, 0); ++count; } } */ #else void demo(char *cfgfile, char *weightfile, float thresh, int cam_index, const char *filename, char **names, int classes, int delay, char *prefix, int avg, float hier, int w, int h, int frames, int fullscreen) { fprintf(stderr, "Demo needs OpenCV for webcam images.\n"); } #endif
我在執行的過程，碰到了很多問題，比如在通過攝像頭實時檢測時，遇到了下面這個問題，這個錯誤不致命，就是可執行檢測但是儲存不了檢測視訊，錯誤提示如下：
HIGHGUI ERROR： V4L/V4L2：VIDIOC_S_CROP
HIGHGUI ERROR： V4L/V4L2：getting property #5 is not supported
GLib-GIOMessage: Using the 'memory' GSettings backend. Your settings will not be saved or shared with other applications.
解決辦法：
（1）第一個問題
HIGHGUI ERROR： V4L/V4L2：VIDIOC_S_CROP
HIGHGUI ERROR： V4L/V4L2：getting property #5 is not supported
我自己測試了下，是程式碼問題，上面給的程式碼已更改，主要在通過攝像頭獲取視訊幀率時採用了：//int mfps = cvGetCaptureProperty(cap,CV_CAP_PROP_FPS); 指令，這樣是不行的，測試本地時可以，所以這裡給幀率設定了一個常數：int mfps = 25;可以結合demo.c檔案對應著看，給了相應的註釋。
（2）第二個問題
GLib-GIOMessage: Using the 'memory' GSettings backend. Your settings will not be saved or shared with other applications.
需要新增一個路徑，操作如下：
在ubuntu終端執行：
sudo gedit /etc/profile
然後在開啟的檔案內(需要sudo許可權)新增下面內容：
export GIO_EXTRA_MODULES=/usr/lib/x86_64-linux-gnu/gio/modules/
最後是上面的更改立即生效：
source .bashrc
補充：這個程式好像儲存出來的視訊確實有點點問題，最終的視訊是一閃一閃的。暫時解決方案：將被檢測視訊的每張圖片分別儲存為單張圖片，然後單獨合成一個視訊就行了（正常），需要兩步操作，整合在一起遇到了問題，歡迎交流。
操作：（1）在darket目錄下手動新建一個資料夾“picture”，用於存放被檢測的單張結果圖片。
（2）將圖片合成視訊，C++和python利用opencv很簡單，百度以下都是的。你只需要更改兩個檔案即可，demo.c與image.c，下載連結為：https://pan.baidu.com/s/14s8vaF4Wac0hJY7S7hbz5A
有問題加我主頁微信聯絡。
補充：20181021，新上傳的程式碼可用。老程式碼也可用，就是儲存的視訊有點點閃爍，評論區貌似出現了一個解決方法，大家可以嘗試下。（我自己工作了，現在沒有這個實驗環境）
