C# OpenCvSharp DNN 部署yolov5不规则四边形目标检测

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效果

模型信息

项目

代码

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C# OpenCvSharp DNN 部署yolov5不规则四边形目标检测

效果

模型信息

Inputs
-------------------------
name：images
tensor：Float[1, 3, 1024, 1024]
---------------------------------------------------------------

Outputs
-------------------------
name：output
tensor：Float[1, 64512, 11]
---------------------------------------------------------------

项目

代码

using OpenCvSharp;
using OpenCvSharp.Dnn;
using System;
using System.Collections.Generic;
using System.Drawing;
using System.IO;
using System.Linq;
using System.Linq.Expressions;
using System.Numerics;
using System.Reflection;
using System.Windows.Forms;

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

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

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

float confThreshold;
float nmsThreshold;
float objThreshold;

float[,] anchors = new float[3, 6] {
{31, 30, 28, 49, 50, 31},
{46, 45, 58, 58, 74, 74},
{94, 94, 115, 115, 151, 151}
};

float[] stride = new float[3] { 8.0f, 16.0f, 32.0f };

string modelpath;

int inpHeight;
int inpWidth;

List<string> class_names;
int num_class;

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)
{
confThreshold = 0.5f;
nmsThreshold = 0.5f;
objThreshold = 0.5f;

modelpath = "model/best.onnx";

inpHeight = 1024;
inpWidth = 1024;

opencv_net = CvDnn.ReadNetFromOnnx(modelpath);

class_names = new List<string>();
StreamReader sr = new StreamReader("model/coco.names");
string line;
while ((line = sr.ReadLine()) != null)
{
class_names.Add(line);
}
num_class = class_names.Count();

image_path = "test_img/1.png";
pictureBox1.Image = new Bitmap(image_path);

}

float sigmoid(float x)
{
return (float)(1.0 / (1 + Math.Exp(-x)));
}

Mat ResizeImage(Mat srcimg, out int newh, out int neww, out int top, out int left)
{
int srch = srcimg.Rows, srcw = srcimg.Cols;
top = 0;
left = 0;
newh = inpHeight;
neww = inpWidth;
Mat dstimg = new Mat();
if (srch != srcw)
{
float hw_scale = (float)srch / srcw;
if (hw_scale > 1)
{
newh = inpHeight;
neww = (int)(inpWidth / hw_scale);
Cv2.Resize(srcimg, dstimg, new OpenCvSharp.Size(neww, newh), 0, 0, InterpolationFlags.Area);
left = (int)((inpWidth - neww) * 0.5);
Cv2.CopyMakeBorder(dstimg, dstimg, 0, 0, left, inpWidth - neww - left, BorderTypes.Constant);
}
else
{
newh = (int)(inpHeight * hw_scale);
neww = inpWidth;
Cv2.Resize(srcimg, dstimg, new OpenCvSharp.Size(neww, newh), 0, 0, InterpolationFlags.Area);
top = (int)((inpHeight - newh) * 0.5);
Cv2.CopyMakeBorder(dstimg, dstimg, top, inpHeight - newh - top, 0, 0, BorderTypes.Constant);
}
}
else
{
Cv2.Resize(srcimg, dstimg, new OpenCvSharp.Size(neww, newh));
}
return dstimg;
}

float IoU(BoxInfo polya, BoxInfo polyb, int max_w, int max_h)
{
List<List<OpenCvSharp.Point>> poly_array0 = new List<List<OpenCvSharp.Point>>();
List<List<OpenCvSharp.Point>> poly_array1 = new List<List<OpenCvSharp.Point>>();
poly_array0.Add(polya.pts);
poly_array1.Add(polyb.pts);

Mat _poly0 = Mat.Zeros(max_h, max_w, MatType.CV_8UC1);
Mat _poly1 = Mat.Zeros(max_h, max_w, MatType.CV_8UC1);
Mat _result = new Mat();

List<List<OpenCvSharp.Point>> _pts0 = new List<List<OpenCvSharp.Point>>();
List<int> _npts0 = new List<int>();

foreach (var item in poly_array0)
{
if (item.Count < 3)//invalid poly
return -1f;

_pts0.Add(item);
_npts0.Add(item.Count);

}

List<List<OpenCvSharp.Point>> _pts1 = new List<List<OpenCvSharp.Point>>();
List<int> _npts1 = new List<int>();

foreach (var item in poly_array1)
{
if (item.Count < 3)//invalid poly
return -1f;

_pts1.Add(item);
_npts1.Add(item.Count);

}

Cv2.FillPoly(_poly0, _pts0, new Scalar(1));
Cv2.FillPoly(_poly1, _pts1, new Scalar(1));

Cv2.BitwiseAnd(_poly0, _poly1, _result);

int _area0 = Cv2.CountNonZero(_poly0);
int _area1 = Cv2.CountNonZero(_poly1);
int _intersection_area = Cv2.CountNonZero(_result);
float _iou = (float)_intersection_area / (float)(_area0 + _area1 - _intersection_area);
return _iou;
}

void nms(List<BoxInfo> input_boxes, int max_w, int max_h)
{
input_boxes.Sort((a, b) => { return a.score > b.score ? -1 : 1; });

bool[] isSuppressed = new bool[input_boxes.Count];

for (int i = 0; i < input_boxes.Count(); ++i)
{
if (isSuppressed[i]) { continue; }
for (int j = i + 1; j < input_boxes.Count(); ++j)
{
if (isSuppressed[j]) { continue; }
float ovr = IoU(input_boxes[i], input_boxes[j], max_w, max_h);
if (ovr >= nmsThreshold)
{
isSuppressed[j] = true;
}
}
}

for (int i = isSuppressed.Length - 1; i >= 0; i--)
{
if (isSuppressed[i])
{
input_boxes.RemoveAt(i);
}
}

}

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);

int newh = 0, neww = 0, padh = 0, padw = 0;
Mat dstimg = ResizeImage(image, out newh, out neww, out padh, out padw);

BN_image = CvDnn.BlobFromImage(dstimg, 1 / 255.0, new OpenCvSharp.Size(inpWidth, inpHeight), new Scalar(0, 0, 0), true, false);

//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[3] { new Mat(), new Mat(), new Mat() };
string[] outBlobNames = opencv_net.GetUnconnectedOutLayersNames().ToArray();

dt1 = DateTime.Now;

opencv_net.Forward(outs, outBlobNames);

dt2 = DateTime.Now;

int num_proposal = outs[0].Size(1);
int nout = outs[0].Size(2);

if (outs[0].Dims > 2)
{
outs[0] = outs[0].Reshape(0, num_proposal);
}

float ratioh = 1.0f * image.Rows / newh, ratiow = 1.0f * image.Cols / neww;

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

List<BoxInfo> generate_boxes = new List<BoxInfo>();

int row_ind = 0;

for (int n = 0; n < 3; n++)
{

int num_grid_x = (int)(inpWidth / stride[n]);
int num_grid_y = (int)(inpHeight / stride[n]);

for (int q = 0; q < 3; q++) //anchor
{
float anchor_w = anchors[n, q * 2];
float anchor_h = anchors[n, q * 2 + 1];
for (int i = 0; i < num_grid_y; i++)
{
for (int j = 0; j < num_grid_x; j++)
{
float box_score = sigmoid(pdata[8]);
if (box_score > objThreshold)
{

Mat scores = outs[0].Row(row_ind).ColRange(9, 9 + num_class);
double minVal, max_class_socre;
OpenCvSharp.Point minLoc, classIdPoint;
// Get the value and location of the maximum score
Cv2.MinMaxLoc(scores, out minVal, out max_class_socre, out minLoc, out classIdPoint);

int class_idx = classIdPoint.X;
max_class_socre = sigmoid((float)max_class_socre) * box_score;
if (max_class_socre > confThreshold)
{
List<OpenCvSharp.Point> pts = new List<OpenCvSharp.Point>();
for (int k = 0; k < 8; k += 2)
{
float x = (pdata[k] + j) * stride[n]; //x
float y = (pdata[k + 1] + i) * stride[n]; //y
x = (x - padw) * ratiow;
y = (y - padh) * ratioh;
pts.Add(new OpenCvSharp.Point(x, y));
}

Rect r = Cv2.BoundingRect(pts);

generate_boxes.Add(new BoxInfo(pts, (float)max_class_socre, class_idx));
}
}
row_ind++;
pdata += nout;
}
}

}

nms(generate_boxes, image.Cols, image.Rows);

result_image = image.Clone();

for (int ii = 0; ii < generate_boxes.Count; ++ii)
{
int idx = generate_boxes[ii].label;

for (int jj = 0; jj < 4; jj++)
{
Cv2.Line(result_image, generate_boxes[ii].pts[jj], generate_boxes[ii].pts[(jj + 1) % 4], new Scalar(0, 0, 255), 2);
}

string label = class_names[idx] + ":" + generate_boxes[ii].score.ToString("0.00");

int xmin = (int)generate_boxes[ii].pts[0].X;
int ymin = (int)generate_boxes[ii].pts[0].Y - 10;

Cv2.PutText(result_image, label, new OpenCvSharp.Point(xmin, ymin - 5), HersheyFonts.HersheySimplex, 0.75, new Scalar(0, 0, 255), 1);
}

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.IO;
using System.Linq;
using System.Linq.Expressions;
using System.Numerics;
using System.Reflection;
using System.Windows.Forms;namespace OpenCvSharp_DNN_Demo
{public partial class frmMain : Form{public frmMain(){InitializeComponent();}string fileFilter = "*.*|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png";string image_path = "";DateTime dt1 = DateTime.Now;DateTime dt2 = DateTime.Now;float confThreshold;float nmsThreshold;float objThreshold;float[,] anchors = new float[3, 6] {{31, 30, 28, 49, 50, 31},{46, 45, 58, 58, 74, 74},{94, 94, 115, 115, 151, 151}};float[] stride = new float[3] { 8.0f, 16.0f, 32.0f };string modelpath;int inpHeight;int inpWidth;List<string> class_names;int num_class;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){confThreshold = 0.5f;nmsThreshold = 0.5f;objThreshold = 0.5f;modelpath = "model/best.onnx";inpHeight = 1024;inpWidth = 1024;opencv_net = CvDnn.ReadNetFromOnnx(modelpath);class_names = new List<string>();StreamReader sr = new StreamReader("model/coco.names");string line;while ((line = sr.ReadLine()) != null){class_names.Add(line);}num_class = class_names.Count();image_path = "test_img/1.png";pictureBox1.Image = new Bitmap(image_path);}float sigmoid(float x){return (float)(1.0 / (1 + Math.Exp(-x)));}Mat ResizeImage(Mat srcimg, out int newh, out int neww, out int top, out int left){int srch = srcimg.Rows, srcw = srcimg.Cols;top = 0;left = 0;newh = inpHeight;neww = inpWidth;Mat dstimg = new Mat();if (srch != srcw){float hw_scale = (float)srch / srcw;if (hw_scale > 1){newh = inpHeight;neww = (int)(inpWidth / hw_scale);Cv2.Resize(srcimg, dstimg, new OpenCvSharp.Size(neww, newh), 0, 0, InterpolationFlags.Area);left = (int)((inpWidth - neww) * 0.5);Cv2.CopyMakeBorder(dstimg, dstimg, 0, 0, left, inpWidth - neww - left, BorderTypes.Constant);}else{newh = (int)(inpHeight * hw_scale);neww = inpWidth;Cv2.Resize(srcimg, dstimg, new OpenCvSharp.Size(neww, newh), 0, 0, InterpolationFlags.Area);top = (int)((inpHeight - newh) * 0.5);Cv2.CopyMakeBorder(dstimg, dstimg, top, inpHeight - newh - top, 0, 0, BorderTypes.Constant);}}else{Cv2.Resize(srcimg, dstimg, new OpenCvSharp.Size(neww, newh));}return dstimg;}float IoU(BoxInfo polya, BoxInfo polyb, int max_w, int max_h){List<List<OpenCvSharp.Point>> poly_array0 = new List<List<OpenCvSharp.Point>>();List<List<OpenCvSharp.Point>> poly_array1 = new List<List<OpenCvSharp.Point>>();poly_array0.Add(polya.pts);poly_array1.Add(polyb.pts);Mat _poly0 = Mat.Zeros(max_h, max_w, MatType.CV_8UC1);Mat _poly1 = Mat.Zeros(max_h, max_w, MatType.CV_8UC1);Mat _result = new Mat();List<List<OpenCvSharp.Point>> _pts0 = new List<List<OpenCvSharp.Point>>();List<int> _npts0 = new List<int>();foreach (var item in poly_array0){if (item.Count < 3)//invalid polyreturn -1f;_pts0.Add(item);_npts0.Add(item.Count);}List<List<OpenCvSharp.Point>> _pts1 = new List<List<OpenCvSharp.Point>>();List<int> _npts1 = new List<int>();foreach (var item in poly_array1){if (item.Count < 3)//invalid polyreturn -1f;_pts1.Add(item);_npts1.Add(item.Count);}Cv2.FillPoly(_poly0, _pts0, new Scalar(1));Cv2.FillPoly(_poly1, _pts1, new Scalar(1));Cv2.BitwiseAnd(_poly0, _poly1, _result);int _area0 = Cv2.CountNonZero(_poly0);int _area1 = Cv2.CountNonZero(_poly1);int _intersection_area = Cv2.CountNonZero(_result);float _iou = (float)_intersection_area / (float)(_area0 + _area1 - _intersection_area);return _iou;}void nms(List<BoxInfo> input_boxes, int max_w, int max_h){input_boxes.Sort((a, b) => { return a.score > b.score ? -1 : 1; });bool[] isSuppressed = new bool[input_boxes.Count];for (int i = 0; i < input_boxes.Count(); ++i){if (isSuppressed[i]) { continue; }for (int j = i + 1; j < input_boxes.Count(); ++j){if (isSuppressed[j]) { continue; }float ovr = IoU(input_boxes[i], input_boxes[j], max_w, max_h);if (ovr >= nmsThreshold){isSuppressed[j] = true;}}}for (int i = isSuppressed.Length - 1; i >= 0; i--){if (isSuppressed[i]){input_boxes.RemoveAt(i);}}}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);int newh = 0, neww = 0, padh = 0, padw = 0;Mat dstimg = ResizeImage(image, out newh, out neww, out padh, out padw);BN_image = CvDnn.BlobFromImage(dstimg, 1 / 255.0, new OpenCvSharp.Size(inpWidth, inpHeight), new Scalar(0, 0, 0), true, false);//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[3] { new Mat(), new Mat(), new Mat() };string[] outBlobNames = opencv_net.GetUnconnectedOutLayersNames().ToArray();dt1 = DateTime.Now;opencv_net.Forward(outs, outBlobNames);dt2 = DateTime.Now;int num_proposal = outs[0].Size(1);int nout = outs[0].Size(2);if (outs[0].Dims > 2){outs[0] = outs[0].Reshape(0, num_proposal);}float ratioh = 1.0f * image.Rows / newh, ratiow = 1.0f * image.Cols / neww;float* pdata = (float*)outs[0].Data;List<BoxInfo> generate_boxes = new List<BoxInfo>();int row_ind = 0;for (int n = 0; n < 3; n++){int num_grid_x = (int)(inpWidth / stride[n]);int num_grid_y = (int)(inpHeight / stride[n]);for (int q = 0; q < 3; q++)    //anchor{float anchor_w = anchors[n, q * 2];float anchor_h = anchors[n, q * 2 + 1];for (int i = 0; i < num_grid_y; i++){for (int j = 0; j < num_grid_x; j++){float box_score = sigmoid(pdata[8]);if (box_score > objThreshold){Mat scores = outs[0].Row(row_ind).ColRange(9, 9 + num_class);double minVal, max_class_socre;OpenCvSharp.Point minLoc, classIdPoint;// Get the value and location of the maximum scoreCv2.MinMaxLoc(scores, out minVal, out max_class_socre, out minLoc, out classIdPoint);int class_idx = classIdPoint.X;max_class_socre = sigmoid((float)max_class_socre) * box_score;if (max_class_socre > confThreshold){List<OpenCvSharp.Point> pts = new List<OpenCvSharp.Point>();for (int k = 0; k < 8; k += 2){float x = (pdata[k] + j) * stride[n];  //xfloat y = (pdata[k + 1] + i) * stride[n];   //yx = (x - padw) * ratiow;y = (y - padh) * ratioh;pts.Add(new OpenCvSharp.Point(x, y));}Rect r = Cv2.BoundingRect(pts);generate_boxes.Add(new BoxInfo(pts, (float)max_class_socre, class_idx));}}row_ind++;pdata += nout;}}}}nms(generate_boxes, image.Cols, image.Rows);result_image = image.Clone();for (int ii = 0; ii < generate_boxes.Count; ++ii){int idx = generate_boxes[ii].label;for (int jj = 0; jj < 4; jj++){Cv2.Line(result_image, generate_boxes[ii].pts[jj], generate_boxes[ii].pts[(jj + 1) % 4], new Scalar(0, 0, 255), 2);}string label = class_names[idx] + ":" + generate_boxes[ii].score.ToString("0.00");int xmin = (int)generate_boxes[ii].pts[0].X;int ymin = (int)generate_boxes[ii].pts[0].Y - 10;Cv2.PutText(result_image, label, new OpenCvSharp.Point(xmin, ymin - 5), HersheyFonts.HersheySimplex, 0.75, new Scalar(0, 0, 255), 1);}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);}}
}