Emgu CV Image Classification

2018-01-27 |

This code translated from C++(OpenCv) to C#(EmguCV), and it allows to classify 80 images.(https://docs.opencv.org/3.4.0/d5/de7/tutorial_dnn_googlenet.html)


  1. Firstly, download GoogLeNet model files: bvlc_googlenet.prototxt and bvlc_googlenet.caffemodel

  2. Also you need file with names of ILSVRC2012 classes: synset_words.txt.

Put these files into working directory of this program. Also, you should know that this is not a fully translation of OpenCV code. Some functions can be changed.


1) Add .prototxt and .caffemodel files to program

EgEmgu.CV.Dnn.Importer caffe = Emgu.CV.Dnn.Importer.CreateCaffeImporter("Text.prototxt", "Model.caffemodel");

2) Create net

Emgu.CV.Dnn.Net net = new Emgu.CV.Dnn.Net()

3) Pass the blob

 Mat blob = Emgu.CV.Dnn.DnnInvoke.BlobFromImage(resim_Mat, 0.78, size, scalar, true);
 net.SetInput(blob, "data");

Source Code:

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using Emgu.CV;
using Emgu.CV.Structure;
using System.Drawing;
using System.IO;

namespace imageClassification
    class Caffe

        void getMaxClass(ref Mat probBlob, ref int classId, ref double classProb)
            Mat probMat = probBlob.Reshape(1, 1); //reshape the blob to 1x1000 matrix
            Point classNumber = new Point();

            var tmp = new Point();
            double tmpdouble = 0;
            CvInvoke.MinMaxLoc(probMat, ref tmpdouble, ref classProb, ref tmp, ref classNumber);

            classId = classNumber.X;

        private List<string> readClassNames(string filename)
            List<string> classNames = File.ReadAllLines(filename).ToList<string>();
            return classNames;

        public string clsImg(Image<Bgr, byte> img)
            Emgu.CV.Dnn.Importer caffe = Emgu.CV.Dnn.Importer.CreateCaffeImporter("Text.prototxt", "Model.caffemodel");
            Emgu.CV.Dnn.Net net = new Emgu.CV.Dnn.Net();

            //Emgu.CV.Dnn.Net net = Emgu.CV.Dnn.DnnInvoke.ReadNetFromCaffe("Text.prototxt", "Model.caffemodel");
            //THIS COMMAND CAN BE USED FOR THREE LINES AT THE TOP. For Emgucv 3.4.3 or later versions. Thanks to JacobC. for this statement. 

            Mat prob;
            Mat img_Mat = img.Mat;

            Size size = new Size(224, 224);
            MCvScalar scalar = new MCvScalar(104, 117, 123);
            Mat blob = Emgu.CV.Dnn.DnnInvoke.BlobFromImage(img_Mat, 0.78, size, scalar, true);

            net.SetInput(blob, "data");
            prob = net.Forward("prob");
            // var detection_ou = net.Forward("detection_out");
            // var concat = net.Forward("concat");

            int classId = 0;
            double classProb = 0;

            getMaxClass(ref prob, ref classId, ref classProb);

            var classNames = readClassNames("synset_words.txt");

            var bestClass = classNames[classId];

            Console.WriteLine("Best: id:" + classId + ", val: " + bestClass);
            Console.WriteLine("Prob: " + classProb * 100 + "%");

            return bestClass;



  • EmguCV V3.x (http://www.emgu.com/wiki/index.php/Main_Page)
  • bvlc_googlenet.prototxt (https://github.com/opencv/opencv_extra/blob/master/testdata/dnn/bvlc_googlenet.prototxt)
  • bvlc_googlenet.caffemodel (https://github.com/BVLC/caffe/tree/master/models/bvlc_googlenet)


  • https://github.com/opencv/opencv/tree/master/samples/dnn
  • https://docs.opencv.org/3.4.0/d5/de7/tutorial_dnn_googlenet.html

This was the end of the blog post. You can reach me via email umusasadik at gmail com