[C#]winform基于attentive_derain_net深度学习算法进行图像去雨部署实现

using System;
using System.Diagnostics;
using System.Windows.Forms;
using OpenCvSharp;

namespace FIRC
{
    public partial class Form1 : Form
    {
        Mat src = null;
        AGDManager dm = new AGDManager();
        public Form1()
        {
            InitializeComponent();
        }

        private void button1_Click(object sender, EventArgs e)
        {
            OpenFileDialog openFileDialog = new OpenFileDialog();
            openFileDialog.Filter = "图文件(*.*)|*.jpg;*.png;*.jpeg;*.bmp";
            openFileDialog.RestoreDirectory = true;
            openFileDialog.Multiselect = false;
            if (openFileDialog.ShowDialog() == DialogResult.OK)
            {
              
                src = Cv2.ImRead(openFileDialog.FileName);
                pictureBox1.Image = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(src);


            }


        }

        private void button2_Click(object sender, EventArgs e)
        {
            if(pictureBox1.Image==null)
            {
                return;
            }
            var resultImg = dm.Inference(src);

            pictureBox2.Image= OpenCvSharp.Extensions.BitmapConverter.ToBitmap(resultImg);



        }
      
          

        private void Form1_Load(object sender, EventArgs e)
        {
            dm.LoadWeights(Application.StartupPath+ "\\weights\\attentive_gan_derainnet_180x320.onnx");
        }

        private void button3_Click(object sender, EventArgs e)
        {
            VideoCapture capture = new VideoCapture(0);
            if (!capture.IsOpened())
            {
                Console.WriteLine("video not open!");
                return;
            }
            Mat frame = new Mat();
            var sw = new Stopwatch();
            int fps = 0;
            while (true)
            {

                capture.Read(frame);
                if (frame.Empty())
                {
                    Console.WriteLine("data is empty!");
                    break;
                }
                sw.Start();
                var resultImg = dm.Inference(frame);
                sw.Stop();
                fps = Convert.ToInt32(1 / sw.Elapsed.TotalSeconds);
                sw.Reset();
            
                Cv2.PutText(resultImg, "FPS=" + fps, new OpenCvSharp.Point(30, 30), HersheyFonts.HersheyComplex, 1.0, new Scalar(255, 0, 0), 3);
                //显示结果
                Cv2.ImShow("Result", resultImg);
                int key = Cv2.WaitKey(10);
                if (key == 27)
                    break;
            }

            capture.Release();
        }
    }
}