特征保存

int main( )
{
	//加载模型
	ncnn::Net squeezenet;
	squeezenet.load_param("mobilefacenet/mobilefacenet.param");
	squeezenet.load_model("mobilefacenet/mobilefacenet.bin");

	string readImgPartDir = "D:\faceData\";//读取图片路径
	string personName;//人名文件夹
	string imgName;//具体图片名（*.jpg）
	string readImg;//图片完成路径 = 读取图片路径+人名文件夹+具体图片名


	FILE* f = fopen("D:\Feature.txt", "wt");
	if (f == NULL)
	{
		printf("文件打开失败!
");
	}
	else
	{
		printf("文件打开成功!
");
	}

	std::ifstream fin("D:\数据\餐饮测试\faceData\0.txt");//打开原始样本图片文件列表  
	string readLineName;//从txt中读取的名字
	cv::Mat image;

	while (getline(fin, readLineName))
	{
		//cout << "readLineName = "<< readLineName << endl;

		imgName = readLineName.substr(readLineName.find_last_of("\") + 1);
		//cout << "imgName = " << imgName << endl;

		personName = readLineName.substr(0, readLineName.find_first_of("\"));
		//cout << "personName = " << personName << endl;

		readImg = readImgPartDir + personName + "\" + imgName;//输入图片
		//cout << "readImg = " << readImg << endl;

		image = cv::imread(readImg, 1);
		//cout << "channels = " << image.channels() << endl;
		//cout << "image w=" << image.cols << ",h=" << image.rows << endl;

		

		if (image.empty())
		{
			printf("--(!) No captured frame -- Break!");
			continue;                  
		}
		else
		{
			
			//float *featFace = new float[128];
			
			ncnn::Extractor ex = squeezenet.create_extractor();
			ncnn::Mat in = ncnn::Mat::from_pixels_resize(image.data, ncnn::Mat::PIXEL_BGR2RGB, image.cols, image.rows, 112, 112);

			ex.input("data", in);
			ncnn::Mat out;
			ex.extract("fc1", out);

			for (int j = 0; j < out.w; ++j)
			{
				//featFace[j] = out[j];
				std::fprintf(f, "%f ", out[j]);
				
			}

			std::fprintf(f, "%s", ",");
			std::fprintf(f, "%s", personName);
			std::fprintf(f, "%s", "
");

			//delete[] featFace;
		}
	
	}//end while

	fclose(f);
	return 0;
}