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【darknet】批量测试工具

【darknet】批量测试工具

作者: yuanCruise | 来源:发表于2019-05-13 23:49 被阅读0次

在detector.c中增加如下所示代码段,即可进行批量图像测试

void test_batch_detector(char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh, float hier_thresh, char *outfile, int fullscreen)
{
    list *options = read_data_cfg(datacfg);
    char *name_list = option_find_str(options, "names", "data/names.list");//home/YL/darknet-master-v3/backup/yolov3_fisheye_fullimage/1_cls_cfg/hs.names
    char **names = get_labels(name_list);

    image **alphabet = load_alphabet();
    network *net = load_network(cfgfile, weightfile, 0);
    set_batch_network(net, 1);
    srand(2222222);
    double time;
    char buff[256];
    char *input = buff;
    float nms = .45;
    
    list *plist;
    char **paths;
    int m;
    int i =0;
    if(filename)
    {
        plist = get_paths(filename);
        paths = (char **)list_to_array(plist);
        m = plist->size;
        i = 0;
    }
    for(i=0;i<m;i++)
    {
        if(1)
        {
            strncpy(input,paths[i],256);
            printf("%s\n",paths[i]);
            printf("Total Img Num:%d\n",m);
            printf("Predict Img Index:%d\n",i); 
        }
        else
        {
            printf("Enter Image Path: ");
            fflush(stdout);
            input = fgets(input, 256, stdin);
            if (!input) return;
            strtok(input, "\n");
        }
        image im = load_image_color(input, 0, 0);
        image sized = letterbox_image(im, net->w, net->h);
        //image sized = resize_image(im, net->w, net->h);
        //image sized2 = resize_max(im, net->w);
        //image sized = crop_image(sized2, -((net->w - sized2.w)/2), -((net->h - sized2.h)/2), net->w, net->h);
        //resize_network(net, sized.w, sized.h);
        layer l = net->layers[net->n - 1];
        float *X = sized.data;
        time = what_time_is_it_now();
        network_predict(net, X);
        printf("%s: Predicted in %f seconds.\n", input, what_time_is_it_now() - time);
        int nboxes = 0;
        detection *dets = get_network_boxes(net, im.w, im.h, thresh, hier_thresh, 0, 1, &nboxes);
        //printf("%d\n", nboxes);
        //if (nms) do_nms_obj(boxes, probs, l.w*l.h*l.n, l.classes, nms);
        if (nms) do_nms_sort(dets, nboxes, l.classes, nms);
        draw_detections(im, dets, nboxes, thresh, names, alphabet, l.classes);
        free_detections(dets, nboxes);
        int count = i;
        char tmp[10];
        sprintf(tmp,"%d",count);
        printf("string itoa:%d\n",i);
        char tmp_out[256];
        strncpy(tmp_out,outfile,256);
        strcat(tmp_out,tmp);
        if (outfile)
        {
            save_image(im, outfile);
        }
        else 
        {
            save_image(im, "predictions");
#ifdef OPENCV
            //cvNamedWindow("predictions", CV_WINDOW_NORMAL);
            if (fullscreen) 
            {
                //cvSetWindowProperty("predictions", CV_WND_PROP_FULLSCREEN, CV_WINDOW_FULLSCREEN);
            }
            //show_image(im, "predictions");
            //cvWaitKey(0);
            //cvDestroyAllWindows();
#endif
        }
        free_image(im);
        free_image(sized);
        
    }
}

主函数也要做如下修改:

void run_detector(int argc, char **argv)
{
    char *prefix = find_char_arg(argc, argv, "-prefix", 0);
    float thresh = find_float_arg(argc, argv, "-thresh", .5);
    float hier_thresh = find_float_arg(argc, argv, "-hier", .5);
    int cam_index = find_int_arg(argc, argv, "-c", 0);
    int frame_skip = find_int_arg(argc, argv, "-s", 0);
    int avg = find_int_arg(argc, argv, "-avg", 3);
    if(argc < 4){
        fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
        return;
    }
    char *gpu_list = find_char_arg(argc, argv, "-gpus", 0);
    char *outfile = find_char_arg(argc, argv, "-out", 0);
    int *gpus = 0;
    int gpu = 0;
    int ngpus = 0;
    if(gpu_list){
        printf("%s\n", gpu_list);
        int len = strlen(gpu_list);
        ngpus = 1;
        int i;
        for(i = 0; i < len; ++i){
            if (gpu_list[i] == ',') ++ngpus;
        }
        gpus = calloc(ngpus, sizeof(int));
        for(i = 0; i < ngpus; ++i){
            gpus[i] = atoi(gpu_list);
            gpu_list = strchr(gpu_list, ',')+1;
        }
    } else {
        gpu = gpu_index;
        gpus = &gpu;
        ngpus = 1;
    }

    int clear = find_arg(argc, argv, "-clear");
    int fullscreen = find_arg(argc, argv, "-fullscreen");
    int width = find_int_arg(argc, argv, "-w", 0);
    int height = find_int_arg(argc, argv, "-h", 0);
    int fps = find_int_arg(argc, argv, "-fps", 0);
    //int class = find_int_arg(argc, argv, "-class", 0);

    char *datacfg = argv[3];
    char *cfg = argv[4];
    char *weights = (argc > 5) ? argv[5] : 0;
    char *filename = (argc > 6) ? argv[6]: 0;
    if(0==strcmp(argv[2], "test_batch")) test_batch_detector(datacfg, cfg, weights, filename, thresh, hier_thresh, outfile, fullscreen);
    else if (0 == strcmp(argv[2], "test")) test_detector(datacfg, cfg, weights, filename, thresh, hier_thresh, outfile, fullscreen);
    else if(0==strcmp(argv[2], "train")) train_detector(datacfg, cfg, weights, gpus, ngpus, clear);
    else if(0==strcmp(argv[2], "valid")) validate_detector(datacfg, cfg, weights, outfile);
    else if(0==strcmp(argv[2], "valid2")) validate_detector_flip(datacfg, cfg, weights, outfile);
    else if(0==strcmp(argv[2], "recall")) validate_detector_recall(cfg, weights);
    else if(0==strcmp(argv[2], "demo")) {
        list *options = read_data_cfg(datacfg);
        int classes = option_find_int(options, "classes", 20);
        char *name_list = option_find_str(options, "names", "data/names.list");
        char **names = get_labels(name_list);
        demo(cfg, weights, thresh, cam_index, filename, names, classes, frame_skip, prefix, avg, hier_thresh, width, height, fps, fullscreen);
    }
    //else if(0==strcmp(argv[2], "extract")) extract_detector(datacfg, cfg, weights, cam_index, filename, class, thresh, frame_skip);
    //else if(0==strcmp(argv[2], "censor")) censor_detector(datacfg, cfg, weights, cam_index, filename, class, thresh, frame_skip);
}

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