| | |
| | | { |
| | | int selected_num = 0; |
| | | detection_with_class* result_arr = calloc(dets_num, sizeof(detection_with_class)); |
| | | for (int i = 0; i < dets_num; ++i) { |
| | | int i; |
| | | for (i = 0; i < dets_num; ++i) { |
| | | int best_class = -1; |
| | | float best_class_prob = thresh; |
| | | for (int j = 0; j < dets[i].classes; ++j) { |
| | | int j; |
| | | for (j = 0; j < dets[i].classes; ++j) { |
| | | if (dets[i].prob[j] > best_class_prob ) { |
| | | best_class = j; |
| | | best_class_prob = dets[i].prob[j]; |
| | |
| | | |
| | | // text output |
| | | qsort(selected_detections, selected_detections_num, sizeof(*selected_detections), compare_by_lefts); |
| | | for (int i = 0; i < selected_detections_num; ++i) { |
| | | int i; |
| | | for (i = 0; i < selected_detections_num; ++i) { |
| | | const int best_class = selected_detections[i].best_class; |
| | | printf("%s: %.0f%%", names[best_class], selected_detections[i].det.prob[best_class] * 100); |
| | | if (ext_output) |
| | | printf("\t(left: %.0f\ttop: %.0f\tw: %0.f\th: %0.f)\n", |
| | | printf("\t(left: %4.0f top: %4.0f w: %4.0f h: %4.0f)\n", |
| | | (selected_detections[i].det.bbox.x - selected_detections[i].det.bbox.w / 2)*im.w, |
| | | (selected_detections[i].det.bbox.y - selected_detections[i].det.bbox.h / 2)*im.h, |
| | | selected_detections[i].det.bbox.w*im.w, selected_detections[i].det.bbox.h*im.h); |
| | | else |
| | | printf("\n"); |
| | | for (int j = 0; j < classes; ++j) { |
| | | int j; |
| | | for (j = 0; j < classes; ++j) { |
| | | if (selected_detections[i].det.prob[j] > thresh && j != best_class) { |
| | | printf("%s: %.0f%%\n", names[j], selected_detections[i].det.prob[j] * 100); |
| | | } |
| | |
| | | |
| | | // image output |
| | | qsort(selected_detections, selected_detections_num, sizeof(*selected_detections), compare_by_probs); |
| | | for (int i = 0; i < selected_detections_num; ++i) { |
| | | for (i = 0; i < selected_detections_num; ++i) { |
| | | int width = im.h * .006; |
| | | if (width < 1) |
| | | width = 1; |
| | |
| | | if (alphabet) { |
| | | char labelstr[4096] = { 0 }; |
| | | strcat(labelstr, names[selected_detections[i].best_class]); |
| | | for (int j = 0; j < classes; ++j) { |
| | | int j; |
| | | for (j = 0; j < classes; ++j) { |
| | | if (selected_detections[i].det.prob[j] > thresh && j != selected_detections[i].best_class) { |
| | | strcat(labelstr, ", "); |
| | | strcat(labelstr, names[j]); |
| | |
| | | |
| | | #ifdef OPENCV |
| | | |
| | | void draw_detections_cv_v3(IplImage* show_img, detection *dets, int num, float thresh, char **names, image **alphabet, int classes) |
| | | void draw_detections_cv_v3(IplImage* show_img, detection *dets, int num, float thresh, char **names, image **alphabet, int classes, int ext_output) |
| | | { |
| | | int i, j; |
| | | if (!show_img) return; |
| | | static int frame_id = 0; |
| | | frame_id++; |
| | | |
| | | for (i = 0; i < num; ++i) { |
| | | char labelstr[4096] = { 0 }; |
| | |
| | | strcat(labelstr, ", "); |
| | | strcat(labelstr, names[j]); |
| | | } |
| | | printf("%s: %.0f%%\n", names[j], dets[i].prob[j] * 100); |
| | | printf("%s: %.0f%% ", names[j], dets[i].prob[j] * 100); |
| | | } |
| | | } |
| | | if (class_id >= 0) { |
| | | int width = show_img->height * .006; |
| | | |
| | | /* |
| | | if(0){ |
| | | width = pow(prob, 1./2.)*10+1; |
| | | alphabet = 0; |
| | | } |
| | | */ |
| | | //if(0){ |
| | | //width = pow(prob, 1./2.)*10+1; |
| | | //alphabet = 0; |
| | | //} |
| | | |
| | | //printf("%d %s: %.0f%%\n", i, names[class_id], prob*100); |
| | | int offset = class_id * 123457 % classes; |
| | |
| | | color.val[1] = green * 256; |
| | | color.val[2] = blue * 256; |
| | | |
| | | // you should create directory: result_img |
| | | //static int copied_frame_id = -1; |
| | | //static IplImage* copy_img = NULL; |
| | | //if (copied_frame_id != frame_id) { |
| | | // copied_frame_id = frame_id; |
| | | // if(copy_img == NULL) copy_img = cvCreateImage(cvSize(show_img->width, show_img->height), show_img->depth, show_img->nChannels); |
| | | // cvCopy(show_img, copy_img, 0); |
| | | //} |
| | | //static int img_id = 0; |
| | | //img_id++; |
| | | //char image_name[1024]; |
| | | //sprintf(image_name, "result_img/img_%d_%d_%d.jpg", frame_id, img_id, class_id); |
| | | //CvRect rect = cvRect(pt1.x, pt1.y, pt2.x - pt1.x, pt2.y - pt1.y); |
| | | //cvSetImageROI(copy_img, rect); |
| | | //cvSaveImage(image_name, copy_img, 0); |
| | | //cvResetImageROI(copy_img); |
| | | |
| | | cvRectangle(show_img, pt1, pt2, color, width, 8, 0); |
| | | //printf("left=%d, right=%d, top=%d, bottom=%d, obj_id=%d, obj=%s \n", left, right, top, bot, class_id, names[class_id]); |
| | | if (ext_output) |
| | | printf(" (left: %4.0f top: %4.0f w: %4.0f h: %4.0f)\n", |
| | | (float)left, (float)right, b.w*show_img->width, b.h*show_img->height); |
| | | else |
| | | printf("\n"); |
| | | cvRectangle(show_img, pt_text_bg1, pt_text_bg2, color, width, 8, 0); |
| | | cvRectangle(show_img, pt_text_bg1, pt_text_bg2, color, CV_FILLED, 8, 0); // filled |
| | | CvScalar black_color; |
| | |
| | | sprintf(buff, "echo %s >> bad.list", filename); |
| | | system(buff); |
| | | return make_image(10,10,3); |
| | | //exit(0); |
| | | //exit(EXIT_FAILURE); |
| | | } |
| | | image out = ipl_to_image(src); |
| | | cvReleaseImage(&src); |
| | |
| | | src = get_webcam_frame(cap); |
| | | if (!src) return make_empty_image(0, 0, 0); |
| | | } while (src->width < 1 || src->height < 1 || src->nChannels < 1); |
| | | printf("Video stream: %d x %d \n", src->width, src->height); |
| | | } else |
| | | src = get_webcam_frame(cap); |
| | | } |
| | |
| | | unsigned char *data = stbi_load(filename, &w, &h, &c, channels); |
| | | if (!data) { |
| | | fprintf(stderr, "Cannot load image \"%s\"\nSTB Reason: %s\n", filename, stbi_failure_reason()); |
| | | exit(0); |
| | | char buff[256]; |
| | | sprintf(buff, "echo %s >> bad.list", filename); |
| | | system(buff); |
| | | return make_image(10, 10, 3); |
| | | //exit(EXIT_FAILURE); |
| | | } |
| | | if(channels) c = channels; |
| | | int i,j,k; |