OpenCV4入门教程138：使用图像分类模型实现图像分类

加载训练好的图像分类模型，然后进行推断，输出图片中可能的目标。

这个是darknet的一张测试图片：

src

使用的是googlenet Caffe模型。

一般需要三个文件：

模型参数：bvlc_googlenet.prototxt -> https://github.com/opencv/opencv_extra/blob/master/testdata/dnn/bvlc_googlenet.prototxt
模型配置文件即模型框架：bvlc_googlenet.caffemodel -> http://dl.caffe.berkeleyvision.org/
ImageNet标签文件：classification_classes_ILSVRC2012.txt -> https://github.com/opencv/opencv/tree/master/data

测试代码：

//use opencv_dnn module for image classification by using GoogLeNet trained network
#include 
#include 
#include 
#include 

using namespace cv;
using namespace cv::dnn;
using namespace std;
String modelTxt = "bvlc_googlenet.prototxt";
String modelBin = "bvlc_googlenet.caffemodel";
String labelFile = "classification_classes_ILSVRC2012.txt";

vector readClasslabels();

int main(int argc, char** argv) {
    Mat testImage = imread("dog.jpg");
    if (testImage.empty()) {
        printf("could not load image...\n");
        return -1;
    }
    // create googlenet with caffemodel text and bin
    Net net = dnn::readNetFromCaffe(modelTxt, modelBin);
    if (net.empty())
    {
        std::cerr  labels = readClasslabels();
    //GoogLeNet accepts only 224x224 RGB-images
    Mat inputBlob = blobFromImage(testImage, 1, Size(224, 224), Scalar(104, 117, 123));//mean: Scalar(104, 117, 123)
    // 支持1000个图像分类检测
    Mat prob;
    // 循环10+
    for (int i = 0; i  readClasslabels() {
    std::vector classNames;
    std::ifstream fp(labelFile);
    if (!fp.is_open())
    {
        std::cerr

测试结果：

终端输出为：

1
2
3

Attempting to upgrade input file specified using deprecated V1LayerParameter: bvlc_googlenet.caffemodel
Successfully upgraded file specified using deprecated V1LayerParameter
current image classification : malemute, Alaskan malamute, possible : 0.42

图片效果：

dog