将预测保存到json或txt文件中，还将输出视频文件保存在yolov3对象检测中-Google Colab [英] Save prediction to json or txt file and also save output video file in yolov3 object detection - Google colab

问题描述

https://github.com/AlexeyAB/darknet/上的对象检测正在运行，并且输出将保存到.avi文件.我还想将预测保存到json或txt文件中.

Object detection on https://github.com/AlexeyAB/darknet/ is working and the output is saved to an .avi file. I also want to save the predictions to a json or txt file.

这是我运行的代码:

./darknet detector demo cfg/coco.data cfg/yolov3.cfg yolov3.weights -dont_show test_vid.mp4 -i 0 -out result.json -out_filename output.avi -ext_output -dont_show 

但是仅保存视频输出.我希望将预测也保存到json或txt文件中.我在这里做错了什么?还有其他方法吗?

But only the video output is saved. I want the predictions also to be saved to json or txt file. What am I doing wrong here? Is there any other way to do it?

我是计算机视觉的新手，因此需要一些帮助.谢谢

I'm new to computer vision and need some help with this. Thanks

推荐答案

查看演示在这里:

void demo(char *cfgfile, char *weightfile, float thresh, float hier_thresh, int cam_index, const char *filename, char **names, int classes, int avgframes,
    int frame_skip, char *prefix, char *out_filename, int mjpeg_port, int dontdraw_bbox, int json_port, int dont_show, int ext_output, int letter_box_in, int time_limit_sec, char *http_post_host,
    int benchmark, int benchmark_layers)

它没有名为-out的参数.

如果要使用演示，则在现有代码中，您有两个选择:

1. 将结果保存到视频文件:-out_filename res.avi
2. 使用软件浏览器或Web浏览器通过网络在线获取结果:-json_port 8070 -mjpeg_port 8090

1. Save results to video file: -out_filename res.avi
2. Get results online over the network by using your soft or Web-browser: -json_port 8070 -mjpeg_port 8090

对于现有代码，-out仅随detector test一起提供.来自此函数定义:

With existing code -out is provided with detector test only. From this function definition:

void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh,
    float hier_thresh, int dont_show, int ext_output, int save_labels, char *outfile, int letter_box, int benchmark_layers)

要处理图像列表data/train.txt并将检测结果保存到result.json文件:

To process a list of images data/train.txt and save results of detection to result.json file:

./darknet detector test cfg/coco.data cfg/yolov4.cfg yolov4.weights -ext_output -dont_show -out result.json < data/train.txt

请注意，这是为了对一组输入图像进行检测并将结果保存到json.

Note that, this is meant for doing detection on set of input images and save results to json.

在所有可能的地方此处命令以及标志和参数，它们的用法得到了很好的解释.

Check here for all possible commands along with flags and arguments, their usage is explained well.

如果要对输入视频进行检测并将预测另存为json，则有两个选择:

If you want to run detection on input video and save predictions as json, you have two options:

1. 使用opencv将视频转换为输入图像集，并使用以下命令:

./darknet detector test cfg/coco.data cfg/yolov4.cfg yolov4.weights -ext_output -dont_show -out result.json < data/train.txt

1. 更改代码以在演示中包含-out功能:

您需要将此参数包含在 demo中的演示函数中.h ， yolo.c ， detector.c ，

You need to include this argument to demo function in demo.h, yolo.c, detector.c, demo.c - 1 and demo.c - 2:

 `char *outfile`

将以下代码段添加到demo.c:

FILE* json_file = NULL;
if (outfile) {
    json_file = fopen(outfile, "wb");
    if(!json_file) {
      error("fopen failed");
    }
    char *tmp = "[\n";
    fwrite(tmp, sizeof(char), strlen(tmp), json_file);
}

在此处添加此代码段:

    if (json_file) {
        if (json_buf) {
            char *tmp = ", \n";
            fwrite(tmp, sizeof(char), strlen(tmp), json_file);
        }
        ++json_image_id;
        json_buf = detection_to_json(dets, nboxes, l.classes, names, json_image_id, input);

        fwrite(json_buf, sizeof(char), strlen(json_buf), json_file);
        free(json_buf);
    }

关闭json文件此处:

 if (json_file) {
        char *tmp = "\n]";
        fwrite(tmp, sizeof(char), strlen(tmp), json_file);
        fclose(json_file);
    }

这篇关于将预测保存到json或txt文件中，还将输出视频文件保存在yolov3对象检测中-Google Colab的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！