Function main

example/detect-image.cpp:47–127

using namespace cv;

int main(int argc, char* argv[])
{
    if(argc != 2)
    {
        printf("Usage: %s <image_file_name>\n", argv[0]);
        return -1;
    }

	//load an image and convert it to gray (single-channel)
	Mat image = imread(argv[1]); 
	if(image.empty())
	{
		fprintf(stderr, "Can not load the image file %s.\n", argv[1]);
		return -1;
	}

	int * pResults = NULL; 
    //pBuffer is used in the detection functions.
    //If you call functions in multiple threads, please create one buffer for each thread!
    unsigned char * pBuffer = (unsigned char *)malloc(DETECT_BUFFER_SIZE);
    if(!pBuffer)
    {
        fprintf(stderr, "Can not alloc buffer.\n");
        return -1;
    }
	

	///////////////////////////////////////////
	// CNN face detection 
	// Best detection rate
	//////////////////////////////////////////
	//!!! The input image must be a BGR one (three-channel) instead of RGB
	//!!! DO NOT RELEASE pResults !!!
    TickMeter cvtm;
    cvtm.start();

	pResults = facedetect_cnn(pBuffer, (unsigned char*)(image.ptr(0)), image.cols, image.rows, (int)image.step);
    
    cvtm.stop();    
    printf("time = %gms\n", cvtm.getTimeMilli());
    
    printf("%d faces detected.\n", (pResults ? *pResults : 0));
	Mat result_image = image.clone();
	//print the detection results
	for(int i = 0; i < (pResults ? *pResults : 0); i++)
	{
        short * p = ((short*)(pResults+1))+142*i;
		int confidence = p[0];
		int x = p[1];
		int y = p[2];
		int w = p[3];
		int h = p[4];
        
        //show the score of the face. Its range is [0-100]
        char sScore[256];
        snprintf(sScore, 256, "%d", confidence);
        cv::putText(result_image, sScore, cv::Point(x, y-3), cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0, 255, 0), 1);
        //draw face rectangle