C# OpenCV 部署RecRecNet广角图像畸变矫正

C# OpenCV 部署RecRecNet广角图像畸变矫正

目录

说明

效果

模型信息

项目

代码

下载

说明

ICCV2023 - RecRecNet: Rectangling Rectified Wide-Angle Images by Thin-Plate Spline Model and DoF-based Curriculum Learning

参考：

https://github.com/KangLiao929/RecRecNet

https://github.com/hpc203/recrecnet-opencv-dnn

效果

模型信息

Model Properties
-------------------------
---------------------------------------------------------------

Inputs
-------------------------
name：input
tensor：Float[1, 3, 256, 256]
---------------------------------------------------------------

Outputs
-------------------------
name：output
tensor：Float[1, 162]
---------------------------------------------------------------

项目

代码

using OpenCvSharp;
using OpenCvSharp.Dnn;
using System;
using System.Collections.Generic;
using System.Drawing;
using System.Linq;
using System.Windows.Forms;

namespace OpenCvSharp_DNN_Demo
{
    public partial class frmMain : Form
    {
        public frmMain()
        {
            InitializeComponent();
        }

        string fileFilter = "图片|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png";
        string image_path = "";

        DateTime dt1 = DateTime.Now;
        DateTime dt2 = DateTime.Now;

        int inpHeight;
        int inpWidth;
        string modelpath;

        int grid_h = 8;
        int grid_w = 8;
        Mat grid;
        Mat W_inv;

        Net opencv_net;
        Mat BN_image;

        Mat image;
        Mat result_image;

        private void button1_Click(object sender, EventArgs e)
        {
            OpenFileDialog ofd = new OpenFileDialog();
            ofd.Filter = fileFilter;
            if (ofd.ShowDialog() != DialogResult.OK) return;

            pictureBox1.Image = null;
            pictureBox2.Image = null;
            textBox1.Text = "";

            image_path = ofd.FileName;
            pictureBox1.Image = new Bitmap(image_path);
            image = new Mat(image_path);
        }

        private void Form1_Load(object sender, EventArgs e)
        {
            modelpath = "model/model_deploy.onnx";

            inpHeight = 256;
            inpWidth = 256;

            opencv_net = CvDnn.ReadNetFromOnnx(modelpath);

            Common.get_norm_rigid_mesh_inv_grid(ref grid, ref W_inv, inpHeight, inpWidth, grid_h, grid_w);

            image_path = "test_img/10.jpg";
            pictureBox1.Image = new Bitmap(image_path);

        }

        private unsafe void button2_Click(object sender, EventArgs e)
        {
            if (image_path == "")
            {
                return;
            }
            textBox1.Text = "检测中，请稍等……";
            pictureBox2.Image = null;
            Application.DoEvents();

            image = new Mat(image_path);
            dt1 = DateTime.Now;

            Mat img = new Mat();

            Cv2.Resize(image, img, new OpenCvSharp.Size(inpWidth, inpHeight));

            img.ConvertTo(img, MatType.CV_32FC3, 1.0f / 127.5f, -1.0f);

            BN_image = CvDnn.BlobFromImage(img);

            //配置图片输入数据
            opencv_net.SetInput(BN_image);

            //模型推理，读取推理结果
            Mat[] outs = new Mat[1] { new Mat() };
            string[] outBlobNames = opencv_net.GetUnconnectedOutLayersNames().ToArray();

            opencv_net.Forward(outs, outBlobNames);

            dt2 = DateTime.Now;

            float* offset = (float*)outs[0].Data;

            Mat tp = new Mat();
            Mat ori_mesh_np_x = new Mat();
            Mat ori_mesh_np_y = new Mat();
            Common.get_ori_rigid_mesh_tp(tp, ori_mesh_np_x, ori_mesh_np_y, offset, inpHeight, inpWidth, grid_h, grid_w);
            Mat T = W_inv * tp;   
            T = T.T();    

            Mat T_g = T * grid;

            Mat output_tps = Common._interpolate(BN_image, T_g, new OpenCvSharp.Size(inpWidth, inpHeight));
            Mat rectangling_np = (output_tps + 1) * 127.5;
            rectangling_np.ConvertTo(rectangling_np, MatType.CV_8UC3);
            Mat input_np = (img + 1) * 127.5;

            List outputs = new List();
            outputs.Add(rectangling_np);
            outputs.Add(input_np);
            outputs.Add(ori_mesh_np_x);
            outputs.Add(ori_mesh_np_y);

            Mat input_with_mesh = Common.draw_mesh_on_warp(outputs[1], outputs[2], outputs[3]);

            Cv2.CvtColor(outputs[0], outputs[0], ColorConversionCodes.BGR2RGB);

            Cv2.ImShow("mesh", input_with_mesh);

            result_image = outputs[0].Clone();
            pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());
            textBox1.Text = "推理耗时:" + (dt2 - dt1).TotalMilliseconds + "ms";

        }

        private void pictureBox2_DoubleClick(object sender, EventArgs e)
        {
            Common.ShowNormalImg(pictureBox2.Image);
        }

        private void pictureBox1_DoubleClick(object sender, EventArgs e)
        {
            Common.ShowNormalImg(pictureBox1.Image);
        }
    }
}
 

  1. using OpenCvSharp;
  2. using OpenCvSharp.Dnn;
  3. using System;
  4. using System.Collections.Generic;
  5. using System.Drawing;
  6. using System.Linq;
  7. using System.Windows.Forms;
  8.  
  9. namespace OpenCvSharp_DNN_Demo
  10. {
  11.     public partial class frmMain : Form
  12.     {
  13.         public frmMain()
  14.         {
  15.             InitializeComponent();
  16.         }
  17.  
  18.         string fileFilter = "图片|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png";
  19.         string image_path = "";
  20.  
  21.         DateTime dt1 = DateTime.Now;
  22.         DateTime dt2 = DateTime.Now;
  23.  
  24.         int inpHeight;
  25.         int inpWidth;
  26.         string modelpath;
  27.  
  28.         int grid_h = 8;
  29.         int grid_w = 8;
  30.         Mat grid;
  31.         Mat W_inv;
  32.  
  33.         Net opencv_net;
  34.         Mat BN_image;
  35.  
  36.         Mat image;
  37.         Mat result_image;
  38.  
  39.         private void button1_Click(object sender, EventArgs e)
  40.         {
  41.             OpenFileDialog ofd = new OpenFileDialog();
  42.             ofd.Filter = fileFilter;
  43.             if (ofd.ShowDialog() != DialogResult.OK) return;
  44.  
  45.             pictureBox1.Image = null;
  46.             pictureBox2.Image = null;
  47.             textBox1.Text = "";
  48.  
  49.             image_path = ofd.FileName;
  50.             pictureBox1.Image = new Bitmap(image_path);
  51.             image = new Mat(image_path);
  52.         }
  53.  
  54.         private void Form1_Load(object sender, EventArgs e)
  55.         {
  56.             modelpath = "model/model_deploy.onnx";
  57.  
  58.             inpHeight = 256;
  59.             inpWidth = 256;
  60.  
  61.             opencv_net = CvDnn.ReadNetFromOnnx(modelpath);
  62.  
  63.             Common.get_norm_rigid_mesh_inv_grid(ref grid, ref W_inv, inpHeight, inpWidth, grid_h, grid_w);
  64.  
  65.             image_path = "test_img/10.jpg";
  66.             pictureBox1.Image = new Bitmap(image_path);
  67.  
  68.         }
  69.  
  70.         private unsafe void button2_Click(object sender, EventArgs e)
  71.         {
  72.             if (image_path == "")
  73.             {
  74.                 return;
  75.             }
  76.             textBox1.Text = "检测中，请稍等……";
  77.             pictureBox2.Image = null;
  78.             Application.DoEvents();
  79.  
  80.             image = new Mat(image_path);
  81.             dt1 = DateTime.Now;
  82.  
  83.             Mat img = new Mat();
  84.  
  85.             Cv2.Resize(image, img, new OpenCvSharp.Size(inpWidth, inpHeight));
  86.  
  87.             img.ConvertTo(img, MatType.CV_32FC3, 1.0f / 127.5f, -1.0f);
  88.  
  89.             BN_image = CvDnn.BlobFromImage(img);
  90.  
  91.             //配置图片输入数据
  92.             opencv_net.SetInput(BN_image);
  93.  
  94.             //模型推理，读取推理结果
  95.             Mat[] outs = new Mat[1] { new Mat() };
  96.             string[] outBlobNames = opencv_net.GetUnconnectedOutLayersNames().ToArray();
  97.  
  98.             opencv_net.Forward(outs, outBlobNames);
  99.  
  100.             dt2 = DateTime.Now;
  101.  
  102.             float* offset = (float*)outs[0].Data;
  103.  
  104.             Mat tp = new Mat();
  105.             Mat ori_mesh_np_x = new Mat();
  106.             Mat ori_mesh_np_y = new Mat();
  107.             Common.get_ori_rigid_mesh_tp(tp, ori_mesh_np_x, ori_mesh_np_y, offset, inpHeight, inpWidth, grid_h, grid_w);
  108.             Mat T = W_inv * tp;   
  109.             T = T.T();    
  110.  
  111.             Mat T_g = T * grid;
  112.  
  113.             Mat output_tps = Common._interpolate(BN_image, T_g, new OpenCvSharp.Size(inpWidth, inpHeight));
  114.             Mat rectangling_np = (output_tps + 1) * 127.5;
  115.             rectangling_np.ConvertTo(rectangling_np, MatType.CV_8UC3);
  116.             Mat input_np = (img + 1) * 127.5;
  117.  
  118.             List<Mat> outputs = new List<Mat>();
  119.             outputs.Add(rectangling_np);
  120.             outputs.Add(input_np);
  121.             outputs.Add(ori_mesh_np_x);
  122.             outputs.Add(ori_mesh_np_y);
  123.  
  124.             Mat input_with_mesh = Common.draw_mesh_on_warp(outputs[1], outputs[2], outputs[3]);
  125.  
  126.             Cv2.CvtColor(outputs[0], outputs[0], ColorConversionCodes.BGR2RGB);
  127.  
  128.             Cv2.ImShow("mesh", input_with_mesh);
  129.  
  130.             result_image = outputs[0].Clone();
  131.             pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());
  132.             textBox1.Text = "推理耗时:" + (dt2 - dt1).TotalMilliseconds + "ms";
  133.  
  134.         }
  135.  
  136.         private void pictureBox2_DoubleClick(object sender, EventArgs e)
  137.         {
  138.             Common.ShowNormalImg(pictureBox2.Image);
  139.         }
  140.  
  141.         private void pictureBox1_DoubleClick(object sender, EventArgs e)
  142.         {
  143.             Common.ShowNormalImg(pictureBox1.Image);
  144.         }
  145.     }
  146. }

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