darknet源码解读-load_image_color

image load_image_color(char *filename, int w, int h)
{
    return load_image(filename, w, h, 3);
}

image load_image(char *filename, int w, int h, int c)
{
#ifdef OPENCV
    image out = load_image_cv(filename, c);
#else
    image out = load_image_stb(filename, c);
#endif

    if((h && w) && (h != out.h || w != out.w)){
		//按网络要求调整到(w,h)大小,前提是输入的w,h不要是0
        image resized = resize_image(out, w, h);
        free_image(out);
        out = resized;
    }
    return out;
}

因为自己的电脑安装了opencv，所以通过opencv提供库函数来加载图像。

image load_image_cv(char *filename, int channels)
{
    IplImage* src = 0;
    int flag = -1;
    if (channels == 0) flag = -1;
    else if (channels == 1) flag = 0;  //grayscale image
    else if (channels == 3) flag = 1;  //3-channel color image
    else {
        fprintf(stderr, "OpenCV can't force load with %d channels\n", channels);
    }
 
	//opencv api load image
    if( (src = cvLoadImage(filename, flag)) == 0 )
    {
        fprintf(stderr, "Cannot load image \"%s\"\n", filename);
        char buff[256];
        sprintf(buff, "echo %s >> bad.list", filename);
        system(buff);
        return make_image(10,10,3);
        //exit(0);
    }

	//将读取到的IplImage容器中的图片装入image结构中
    image out = ipl_to_image(src);
    cvReleaseImage(&src);
    rgbgr_image(out); //convert BGR to RGB
    
    return out;
}

调用ipl_to_image转换opencv读入的图像。

//convert OpenCV IplImage to image
image ipl_to_image(IplImage* src)
{
    int h = src->height;
    int w = src->width;
    int c = src->nChannels;
    image out = make_image(w, h, c); //create empty image container,(w,h,c)
    ipl_into_image(src, out); //convert IplImage format to image struct
    return out;
}

将IplImage容器中保存的原始图像存入到darknet的image结构中。

void ipl_into_image(IplImage* src, image im)
{
    unsigned char *data = (unsigned char *)src->imageData;
    int h = src->height;
    int w = src->width;
    int c = src->nChannels;
	//在我本机上调试的结果,此处widthStep为20
    int step = src->widthStep; //size of aligned image row in bytes
    int i, j, k;

    for(i = 0; i < h; ++i){
        for(k= 0; k < c; ++k){
            for(j = 0; j < w; ++j){
				//归一化后存入一维数组
                im.data[k*w*h + i*w + j] = data[i*step + j*c + k]/255.;
            }
        }
    }
}

注意存入到一维数组中的图像的顺序。