目录
C# OpenCvSharp DNN 部署yolov5旋转目标检测
效果
模型信息
Inputs
-------------------------
name：images
tensor：Float[1, 3, 1024, 1024]
---------------------------------------------------------------
Outputs
-------------------------
name：output
tensor：Float[1, 107520, 9]
---------------------------------------------------------------
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, 10] {
{27, 26, 20, 40, 44, 19, 34, 34, 25, 47},
{55, 24, 44, 38, 31, 61, 50, 50, 63, 45},
{65, 62, 88, 60, 84, 79, 113, 85, 148, 122}
};
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;
}
void nms_angle(List<BoxInfo> input_boxes)
{
input_boxes.Sort((a, b) => { return a.score > b.score ? -1 : 1; });
float[] vArea = new float[input_boxes.Count];
for (int i = 0; i < input_boxes.Count; ++i)
{
vArea[i] = input_boxes[i].box.Size.Height* input_boxes[i].box.Size.Width;
}
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; }
Point2f[] intersectingRegion;
Cv2.RotatedRectangleIntersection(input_boxes[i].box, input_boxes[j].box, out intersectingRegion);
if (intersectingRegion.Length==0) { continue; }
float inter = (float)Cv2.ContourArea(intersectingRegion);
float ovr = inter / (vArea[i] + vArea[j] - inter);
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 < 5; 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[6]);
if (box_score > objThreshold)
{
Mat scores = outs[0].Row(row_ind).ColRange(7, 7 + 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)
{
float cx = (sigmoid(pdata[0]) * 2.0f - 0.5f + j) * stride[n]; //cx
float cy = (sigmoid(pdata[1]) * 2.0f - 0.5f + i) * stride[n]; //cy
float w = (float)(Math.Pow(sigmoid(pdata[2]) * 2.0f, 2.0f) * anchor_w); //w
float h = (float)(Math.Pow(sigmoid(pdata[3]) * 2.0f, 2.0f) * anchor_h); //h
cx = (cx - padw) * ratiow;
cy = (cy - padh) * ratioh;
w *= ratiow;
h *= ratioh;
float angle = (float)(Math.Acos(sigmoid(pdata[4])) * 180 / Math.PI);
RotatedRect box = new RotatedRect(new Point2f(cx, cy), new Size2f(w, h), angle);
generate_boxes.Add(new BoxInfo(box, (float)max_class_socre, class_idx));
}
}
row_ind++;
pdata += nout;
}
}
}
}
nms_angle(generate_boxes);
result_image = image.Clone();
for (int i = 0; i < generate_boxes.Count(); ++i)
{
RotatedRect rectInput = generate_boxes[i].box;
Point2f[] vertices =rectInput.Points();
for (int j = 0; j < 4; j++)
{
Cv2.Line(result_image, (OpenCvSharp.Point)vertices[j], (OpenCvSharp.Point)vertices[(j + 1) % 4], new Scalar(0, 0, 255), 2);
}
int xmin = (int)vertices[0].X;
int ymin = (int)vertices[0].Y - 10;
int idx = generate_boxes[i].label;
string label = class_names[idx] + ":" + generate_boxes[i].score.ToString("0.00");
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, 10] {
{27, 26, 20, 40, 44, 19, 34, 34, 25, 47},
{55, 24, 44, 38, 31, 61, 50, 50, 63, 45},
{65, 62, 88, 60, 84, 79, 113, 85, 148, 122}
};
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;
}
void nms_angle(List<BoxInfo> input_boxes)
{
input_boxes.Sort((a, b) => { return a.score > b.score ? -1 : 1; });
float[] vArea = new float[input_boxes.Count];
for (int i = 0; i < input_boxes.Count; ++i)
{
vArea[i] = input_boxes[i].box.Size.Height* input_boxes[i].box.Size.Width;
}
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; }
Point2f[] intersectingRegion;
Cv2.RotatedRectangleIntersection(input_boxes[i].box, input_boxes[j].box, out intersectingRegion);
if (intersectingRegion.Length==0) { continue; }
float inter = (float)Cv2.ContourArea(intersectingRegion);
float ovr = inter / (vArea[i] + vArea[j] - inter);
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 < 5; 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[6]);
if (box_score > objThreshold)
{
Mat scores = outs[0].Row(row_ind).ColRange(7, 7 + 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)
{
float cx = (sigmoid(pdata[0]) * 2.0f - 0.5f + j) * stride[n]; //cx
float cy = (sigmoid(pdata[1]) * 2.0f - 0.5f + i) * stride[n]; //cy
float w = (float)(Math.Pow(sigmoid(pdata[2]) * 2.0f, 2.0f) * anchor_w); //w
float h = (float)(Math.Pow(sigmoid(pdata[3]) * 2.0f, 2.0f) * anchor_h); //h
cx = (cx - padw) * ratiow;
cy = (cy - padh) * ratioh;
w *= ratiow;
h *= ratioh;
float angle = (float)(Math.Acos(sigmoid(pdata[4])) * 180 / Math.PI);
RotatedRect box = new RotatedRect(new Point2f(cx, cy), new Size2f(w, h), angle);
generate_boxes.Add(new BoxInfo(box, (float)max_class_socre, class_idx));
}
}
row_ind++;
pdata += nout;
}
}
}
}
nms_angle(generate_boxes);
result_image = image.Clone();
for (int i = 0; i < generate_boxes.Count(); ++i)
{
RotatedRect rectInput = generate_boxes[i].box;
Point2f[] vertices =rectInput.Points();
for (int j = 0; j < 4; j++)
{
Cv2.Line(result_image, (OpenCvSharp.Point)vertices[j], (OpenCvSharp.Point)vertices[(j + 1) % 4], new Scalar(0, 0, 255), 2);
}
int xmin = (int)vertices[0].X;
int ymin = (int)vertices[0].Y - 10;
int idx = generate_boxes[i].label;
string label = class_names[idx] + ":" + generate_boxes[i].score.ToString("0.00");
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);
}
}
}