C# OpenCV 部署RecRecNet广角图像畸变矫正

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<Mat> outputs = new List<Mat>();
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);
}
}
}

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<Mat> outputs = new List<Mat>();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);}}
}