少有人走的路OpenCV是计算机视觉库，Tensorflow是深度学习框架。 OpenCV包含了大量的图像处理和计算机视觉的算法，但是在机器学习方面明显不足，ML模块只有SVM，MLP， kNN等有限的几种算法。dnn模块也是调用别的框架。 Tensorflow是专为深度学习而生，可以方便的实现各种深度学习算法。 二者不属于同一领域，做视觉用OpenCV，做深度学习用Tensorflow。或者二者结合做图像识别等等。
一、版本配置要求
1. Windows 7 和 VS2015
2. OpenCV3.3.1以上，本人使用的OpenCV 3.4.1，下载地址：https://github.com/opencv/opencv/releases
3.至于TensoFlow，鄙人只是想测试已经训练好的模型，那就可以不安装TensoFlow了，偷懒一下~！
二、模型下载和配置
| 序号 | .pb文件：预训练模型 | .pbtxt文件 | 备注 |
| 1 | ssd_mobilenet_v1_coco_11_06_2017 | ssd_mobilenet_v1_coco.pbtxt | |
| 2 | ssd_inception_v2_coco_2017_11_17 | ssd_inception_v2_coco_2017_11_17.pbtxt | |
| 3 | |||
| 4 | |||
/** @brief Reads a network model stored in <a href="https://www.tensorflow.org/">TensorFlow</a> framework's format. * @param model path to the .pb file with binary protobuf description of the network architecture * @param config path to the .pbtxt file that contains text graph definition in protobuf format. * Resulting Net object is built by text graph using weights from a binary one that * let us make it more flexible. * @returns Net object. */ CV_EXPORTS_W Net readNetFromTensorflow(const String &model, const String &config = String());
#include<opencv2\opencv.hpp>
#include<opencv2\dnn.hpp>
#include <iostream>
using namespace std;
using namespace cv;
const size_t inWidth = 300;
const size_t inHeight = 300;
const float WHRatio = inWidth / (float)inHeight;
const char* classNames[] = { "background","face" };//这个需要根据训练的类别定义
int main() {
Mat frame = cv::imread("2.jpg");
Size frame_size = frame.size();
String weights = "models\\ssd_inception_v2_coco_2017_11_17\\frozen_inference_graph.pb";
String prototxt = "models\\ssd_inception_v2_coco_2017_11_17.pbtxt";
dnn::Net net = cv::dnn::readNetFromTensorflow(weights, prototxt);
Size cropSize;
if (frame_size.width / (float)frame_size.height > WHRatio)
{
cropSize = Size(static_cast<int>(frame_size.height * WHRatio),
frame_size.height);
}
else
{
cropSize = Size(frame_size.width,
static_cast<int>(frame_size.width / WHRatio));
}
Rect crop(Point((frame_size.width - cropSize.width) / 2,
(frame_size.height - cropSize.height) / 2),
cropSize);
cv::Mat blob = cv::dnn::blobFromImage(frame, 1. / 255, Size(300, 300));
//cout << "blob size: " << blob.size << endl;
net.setInput(blob);
Mat output = net.forward();
//cout << "output size: " << output.size << endl;
Mat detectionMat(output.size[2], output.size[3], CV_32F, output.ptr<float>());
frame = frame(crop);
float confidenceThreshold = 0.20;
for (int i = 0; i < detectionMat.rows; i++)
{
float confidence = detectionMat.at<float>(i, 2);
if (confidence > confidenceThreshold)
{
size_t objectClass = (size_t)(detectionMat.at<float>(i, 1));
int xLeftBottom = static_cast<int>(detectionMat.at<float>(i, 3) * frame.cols);
int yLeftBottom = static_cast<int>(detectionMat.at<float>(i, 4) * frame.rows);
int xRightTop = static_cast<int>(detectionMat.at<float>(i, 5) * frame.cols);
int yRightTop = static_cast<int>(detectionMat.at<float>(i, 6) * frame.rows);
ostringstream ss;
ss << confidence;
String conf(ss.str());
Rect object((int)xLeftBottom, (int)yLeftBottom,
(int)(xRightTop - xLeftBottom),
(int)(yRightTop - yLeftBottom));
rectangle(frame, object, Scalar(0, 255, 0), 2);
String label = String(classNames[objectClass]) + ": " + conf;
int baseLine = 0;
Size labelSize = getTextSize(label, FONT_HERSHEY_SIMPLEX, 0.5, 1, &baseLine);
rectangle(frame, Rect(Point(xLeftBottom, yLeftBottom - labelSize.height),
Size(labelSize.width, labelSize.height + baseLine)),
Scalar(0, 255, 0), CV_FILLED);
putText(frame, label, Point(xLeftBottom, yLeftBottom),
FONT_HERSHEY_SIMPLEX, 0.5, Scalar(0, 0, 0));
}
}
imshow("image", frame);
waitKey(0);
return 0;
}
四、常见的错误和坑
OpenCV(3.4.1) Error: Unspecified error (FAILED: fs.is_open(). Can't open "models\ssd_inception_v2_coco_2017_1117\frozen_inference_graph.pb") in cv::dnn::ReadProtoFromBinaryFile, file C:\build\master_winpack-build-win64-vc14\opencv\modules\dnn\src\caffe\caffe_io.cpp, line 1126
OpenCV(3.4.1) Error: Unspecified error (Const input blob for weights not found) in cv::dnn::experimental_dnn_v4::`anonymous-namespace'::TFImporter::getConstBlob, file C:\build\master_winpack-build-win64-vc14\opencv\modules\dnn\src\tensorflow\tf_importer.cpp, line 579
五、参考资料：
本文转载自：
https://blog.csdn.net/guyuealian/article/details/80570120
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