[人工智能]blobFromImage

第1种
float* KDAI::blobFromImage(cv::Mat& img)
{
?? ?float* blob = new float[img.total() * 3];
?? ?int channels = 3;
?? ?int img_h = img.rows;
?? ?int img_w = img.cols;
?? ?for (size_t c = 0; c < channels; c++)
?? ?{
?? ??? ?for (size_t h = 0; h < img_h; h++)
?? ??? ?{
?? ??? ??? ?for (size_t w = 0; w < img_w; w++)
?? ??? ??? ?{
?? ??? ??? ??? ?blob[c * img_w * img_h + h * img_w + w] =
?? ??? ??? ??? ??? ?(float)img.at<cv::Vec3b>(h, w)[c];
?? ??? ??? ?}
?? ??? ?}
?? ?}
?? ?return blob;
}

// 第2种
float* KDAI::blobFromImage(cv::Mat& img)
{
?? ?float* blob = new float[img.total() * img.channels()];
?? ?cv::Mat blobImg = cv::dnn::blobFromImage(img);
?? ?memcpy(blob, blobImg.data, blobImg.total() * blobImg.channels() * sizeof(float));
?? ?return blob;
}

//第3种
float* KDAI::blobFromImage(cv::Mat& img)
{
?? ?std::vector<float> dst_data;
?? ?std::vector<cv::Mat> bgrChannels(3);
?? ?cv::split(img, bgrChannels);
?? ?for (auto i = 0; i < bgrChannels.size(); i++)
?? ?{
?? ??? ?std::vector<float> data = std::vector<float>(bgrChannels[i].reshape(1, 1));
?? ??? ?dst_data.insert(dst_data.end(), data.begin(), data.end());
?? ?}
?? ?float* blob = new float[dst_data.size()];
?? ?memcpy(blob, dst_data.data(), sizeof(float) * dst_data.size());
?? ?return blob;
}

// 第4种
float* KDAI::blobFromImage(cv::Mat& img)
{
?? ?float* blob = new float[img.total() * 3];
?? ?int channels = 3;
?? ?int img_h = img.rows;
?? ?int img_w = img.cols;
?? ?for (size_t h = 0; h < img_h; h++)
?? ?{
?? ??? ?for (size_t w = 0; w < img_w; w++)
?? ??? ?{
?? ??? ??? ?blob[0 * img_w * img_h + h * img_w + w] =(float)img.at<cv::Vec3b>(h, w)[0];
?? ??? ??? ?blob[1 * img_w * img_h + h * img_w + w] = (float)img.at<cv::Vec3b>(h, w)[1];
?? ??? ??? ?blob[2 * img_w * img_h + h * img_w + w] = (float)img.at<cv::Vec3b>(h, w)[2];
?? ??? ?}
?? ?}
?? ?return blob;
}