[opencvsharpdnn] implementation example of yolov3 and Caffe in opencvsharp

Recognition effect

Demo video

Usage method

This is a YoloV3 and Caffe Implementation usage in the model

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using OpenCVCSharpDNN.Impl;
using OpenCVCSharpDNN;
using System.IO;
using System.Drawing;


namespace OpenCVCSharp.Example
{
    class Program
    {
        static void Main(string[] args)
        {
            // Directory containing model and configuration files 
            string dir = System.IO.Path.Combine(Directory.GetCurrentDirectory(), "data");


            // YoloV3 Model 
            string model = System.IO.Path.Combine(dir, "yolov3.weights");
            string cfg = System.IO.Path.Combine(dir, "yolov3.cfg");
            string labelsYolo = System.IO.Path.Combine(dir, "coco.names");




            // Face detection model 
            string modelFace = System.IO.Path.Combine(dir, "yolov3-wider_16000.weights");
            string cfgFace = System.IO.Path.Combine(dir, "yolov3-face.cfg");


            // Gender classification model 
            string modelGenderCaffe = System.IO.Path.Combine(dir, "gender_net.caffemodel");
            string cfgGenderCaffe = System.IO.Path.Combine(dir, "deploy_gender.prototxt");


            // Picture path 
            string testImage = System.IO.Path.Combine(dir, "1.bmp");//friends.jpg




            using (NetYoloV3 yoloV3 = new NetYoloV3())
            using (NetYoloV3 yoloV3Faces = new NetYoloV3())
            using (NetCaffeAgeGender caffeGender = new NetCaffeAgeGender())
            using (Bitmap bitmap = new Bitmap(testImage))
            using (Bitmap resultImage = new Bitmap(testImage))
            {


                // Initialize model 
                yoloV3.Initialize(model, cfg, labelsYolo);
                yoloV3Faces.Initialize(modelFace, cfgFace, new string[] { "faces" });
                caffeGender.Initialize(modelGenderCaffe, cfgGenderCaffe, new string[] { "Male", "Female" });




                // obtain  YoloV3  Result 
                NetResult[] resultPersons = yoloV3.Detect(bitmap, labelsFilters: new string[] { "person" });// Tester 




                // obtain  YoloV3  The result of face detection 
                NetResult[] resultFaces = yoloV3Faces.Detect(bitmap);// Face detection 


                using (Graphics canvas = Graphics.FromImage(resultImage))
                {
                    Font font = new Font(FontFamily.GenericSansSerif, 15);


                    // Inferential gender , Draw labels and face bounding boxes 
                    foreach (NetResult item in resultFaces)
                    {
                        // Create regions of interest for each face 
                        using (Bitmap roi = (Bitmap)bitmap.Clone(item.Rectangle, bitmap.PixelFormat))
                        {
                            NetResult resultGender = caffeGender.Detect(roi).FirstOrDefault();// Detect face region and infer gender 
                            // Draw labels 
                            canvas.DrawString($"{resultGender.Label} {resultGender.Probability:0.0%}",
                                font,
                                new SolidBrush(Color.Green),
                                item.Rectangle.X - font.GetHeight(), item.Rectangle.Y - font.GetHeight());


                        }


                        canvas.DrawRectangle(new Pen(Color.Red, 2), item.Rectangle);
                    }


                    canvas.Save();
                }


                resultImage.Save(Path.Combine(dir, "result.jpg"));// Save the recognition results 


            }
        }
    }
}

Pre training model

You can download the pre training model at the following link ：

|YoloV3|

https://pjreddie.com/darknet/yolo/

|YoloV3 Faces|

http://mmlab.ie.cuhk.edu.hk/projects/WIDERFace/index.html  

|Caffe Age and Gender Classification|

https://talhassner.github.io/home/publication/2015_CVPR

Reference resources ：

https://github.com/julian9012/OpenCVCSharpDNN 

https://drive.google.com/drive/folders/1oj9p04mPjbbCbq1qSK8ChMjOhMLMpk42