【darknet训练细节】一个隐藏的超参数：scale

整体源码如下，该源码是利用yolo训练检测网络时，对输入数据作前处理的源代码，该代码段中包含了从外部传入的超参数（jitter），也有内部写死的超参数（scale）。下面将对该代码做详细的解析。

data load_data_detection(int n, char **paths, int m, int w, int h, int boxes, int classes, float jitter, float hue, float saturation, float exposure)
{
    char **random_paths = get_random_paths(paths, n, m);
    int i;
    data d = {0};
    d.shallow = 0;

    d.X.rows = n;
    d.X.vals = calloc(d.X.rows, sizeof(float*));
    d.X.cols = h*w*3;

    d.y = make_matrix(n, 5*boxes);
    for(i = 0; i < n; ++i){
        image orig = load_image_color(random_paths[i], 0, 0);
        image sized = make_image(w, h, orig.c);
        fill_image(sized, .5);

        float dw = jitter * orig.w;
        float dh = jitter * orig.h;

        float new_ar = (orig.w + rand_uniform(-dw, dw)) / (orig.h + rand_uniform(-dh, dh));
        //float scale = rand_uniform(.25, 2);
        float scale = 1;

        float nw, nh;

        if(new_ar < 1){
            nh = scale * h;