yolo源码解析（3）：视频检测流程

代码在自己电脑中！！！！不在服务器

根据前文所说yolo代码逻辑：

├── examples
│   ├── darknet.c(主程序)
│   │── xxx1.c
│   └── xxx2.c
│
├── include
│   ├── darknet.h
│
│
├── Makefile
│
│
└── src
    ├── yyy1.c
    ├── yyy2.h
    └──......

视频检测入口时darknet.c文件。

输入视频检测命令，如： ./darknet detector demo cfg/coco.data cfg/yolov3.cfg yolov3.weights ~/dataset/ca3.mp4 ,darknet.c中根据detector参数，调用detector.c中的 run_detector(int argc, char **argv); 函数.

run_detector函数内容如下

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

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

代码中定义了frame_skip等变量，默认值为0.然后继续调用demo函数，demo函数位于/darknet/src/demo.c文件中，内容如下。

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, );
    set_batch_network(net, );
    pthread_t detect_thread;
    pthread_t fetch_thread;

    srand();

    int i;
    demo_total = size_network(net);
    predictions = calloc(demo_frame, sizeof(float*));
    for (i = ; 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 = open_video_stream(filename, , , , );
    }else{
        cap = open_video_stream(, cam_index, w, h, frames);
    }

    if(!cap) error("Couldn't connect to webcam.\n");

    buff[] = get_image_from_stream(cap);
    buff[] = copy_image(buff[]);
    buff[] = copy_image(buff[]);
    buff_letter[] = letterbox_image(buff[], net->w, net->h);
    buff_letter[] = letterbox_image(buff[], net->w, net->h);
    buff_letter[] = letterbox_image(buff[], net->w, net->h);

    int count = ;
    if(!prefix){
        make_window("Demo", , , fullscreen);
    }

    demo_time = what_time_is_it_now();

    while(!demo_done){
        buff_index = (buff_index + ) %;
        if(pthread_create(&fetch_thread, , fetch_in_thread, )) error("Thread creation failed");
        if(pthread_create(&detect_thread, , detect_in_thread, )) error("Thread creation failed");
        if(!prefix){
            fps = ./(what_time_is_it_now() - demo_time);
            demo_time = what_time_is_it_now();
            display_in_thread();
        }else{
            char name[];
            sprintf(name, "%s_%08d", prefix, count);
            save_image(buff[(buff_index + )%], name);
        }
        pthread_join(fetch_thread, );
        pthread_join(detect_thread, );
        ++count;
    }
}

yolo视频处理的参考：https://blog.csdn.net/sinat_33718563/article/details/79964758

只用cpu的情况下处理视频是在太慢，添加GPU支持，编译时遇到问题

https://github.com/AlexeyAB/darknet/issues/894 参考解决方案

首先查看安装的cuda版本：

hpclib@liu:~$ cat /usr/local/cuda/version.txt
CUDA Version 9.0.

然后查看gedit  ~/.bashrc中的变量设置

export PATH=/usr/local/cuda-8.0/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64:$LD_LIBRARY_PATH

发现与当前版本不对应，改为9.0即可

编译通过。

然而检测时会出现如下错误

CUDA Error: out of memory darknet: ./src/cuda.c:: check_error: Assertion `' failed.
 已放弃 (核心已转储)

先用yolo3-tiny即可

./darknet detect cfg/yolov3-tiny.cfg yolov3-tiny.weights data/dog.jpg

如若扔出现此错误，加sudo试试

视频检测

./darknet detector demo cfg/coco.data cfg/yolov3-tiny.cfg yolov3-tiny.weights

二、mysql访问

首先安装软件包libmysqlclient-dev  sudo apt-get install libmysqlclient-dev

然后根据教程https://blog.csdn.net/tennysonsky/article/details/53984818

编写代码

#include <stdio.h>
#include <stdlib.h>
#include <mysql.h>

int main (int argc, char *argv[])
 {  

    MYSQL *conn;  

    // 步骤1： 初始化连接句柄
    conn = mysql_init(NULL);  

    if (conn == NULL) { // 如果返回NULl说明初始化失败
        printf("mysql_init failed!\n");
        return EXIT_FAILURE;
    }  

    // 步骤2：实际进行连接
    // 参数分别为，conn连接句柄，host是MySQL所在主机或地址，user用户名，password密码，database_name数据库名，后面的都是默认
    conn = mysql_real_connect(conn, "192.168.1.6", "root", "TJU55b425", "rdshare", , NULL, );  

    if (conn) { // 连接成功
        printf("Connection success!\n");
    } else {
        printf("Connection failed!\n");
    }  

    // 步骤3： 退出前关闭连接
    mysql_close(conn);  

    return ;
}  

编译 gcc -I/usr/include/mysql tmysqlest.c -L/usr/lib/mysql -lmysqlclient -o mysqltest  并执行：./mysqltest

成功连接。

然后考虑将代码添加到yolo源码中。