于仕琪开源库libfacedetection+vs2017配置过程

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我是靠谱客的博主腼腆期待，这篇文章主要介绍于仕琪开源库libfacedetection+vs2017配置过程，现在分享给大家，希望可以做个参考。

于仕琪老师的开源库效果很好，好像是前一段时间刚刚开源，特在这里贴一下的我的配置过程以供参考。
1.首先你要下载cmake来编译开源库，以及下载于老师的libfacedetection
2.用cmake编译，推荐使用命令行。以下路径是我存放路径，根据自己实际情况进行更改

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cd C:Softwarelibdetectlibfacedetection-master
mkdir bulid
cd bulid
cmake -G "Visual Studio 15 2017 Win64" -T host=x64 ..
**后面还有两个..不要忘记
cmake --build . --config Release

以上配置的Release x64版本的，如果你要使用opencv,也要配置Release版本的
3.在vs里面新建一个项目，视图-其他窗口-属性管理器，选择Microsoft.Cpp.x64.user
在这里插入图片描述
首先配置vc++,包含目录和库目录，其实配置方式和opencv一样。
包含目录：C:Softwarelibdetectlibfacedetection-mastersrc
库目录：C:Softwarelibdetectlibfacedetection-masterbulidRelease
链接器-输入-附加依赖项，添加facedetection.lib
4.运行于老师的example

复制代码

#include <stdio.h>
#include <opencv2/opencv.hpp>
#include "facedetectcnn.h"

//define the buffer size. Do not change the size!
#define DETECT_BUFFER_SIZE 0x20000
using namespace cv;

int main()
{

//load an image and convert it to gray (single-channel)
	Mat image = imread("keliamoniz2.jpg");
	if (image.empty())
	{
		fprintf(stderr, "Can not load the image file n");
		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 !!!
	pResults = facedetect_cnn(pBuffer, (unsigned char*)(image.ptr(0)), image.cols, image.rows, (int)image.step);

printf("%d faces detected.n", (pResults ? *pResults : 0));
	Mat result_cnn = image.clone();
	//print the detection results
	for (int i = 0; i < (pResults ? *pResults : 0); i++)
	{
		short * p = ((short*)(pResults + 1)) + 142 * i;
		int x = p[0];
		int y = p[1];
		int w = p[2];
		int h = p[3];
		int confidence = p[4];
		int angle = p[5];

printf("face_rect=[%d, %d, %d, %d], confidence=%d, angle=%dn", x, y, w, h, confidence, angle);
		rectangle(result_cnn, Rect(x, y, w, h), Scalar(0, 255, 0), 2);
	}
	imshow("result_cnn", result_cnn);

waitKey();

//release the buffer
	free(pBuffer);

return 0;
}

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#include <stdio.h>
#include <opencv2/opencv.hpp>
#include "facedetectcnn.h"

//define the buffer size. Do not change the size!
#define DETECT_BUFFER_SIZE 0x20000
using namespace cv;

int main()
{
	

	//load an image and convert it to gray (single-channel)
	Mat image = imread("keliamoniz2.jpg");
	if (image.empty())
	{
		fprintf(stderr, "Can not load the image file n");
		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 !!!
	pResults = facedetect_cnn(pBuffer, (unsigned char*)(image.ptr(0)), image.cols, image.rows, (int)image.step);

	printf("%d faces detected.n", (pResults ? *pResults : 0));
	Mat result_cnn = image.clone();
	//print the detection results
	for (int i = 0; i < (pResults ? *pResults : 0); i++)
	{
		short * p = ((short*)(pResults + 1)) + 142 * i;
		int x = p[0];
		int y = p[1];
		int w = p[2];
		int h = p[3];
		int confidence = p[4];
		int angle = p[5];

		printf("face_rect=[%d, %d, %d, %d], confidence=%d, angle=%dn", x, y, w, h, confidence, angle);
		rectangle(result_cnn, Rect(x, y, w, h), Scalar(0, 255, 0), 2);
	}
	imshow("result_cnn", result_cnn);

	waitKey();

	//release the buffer
	free(pBuffer);

	return 0;
}