1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
| 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 = "*.*|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png";
string image_path = "";
DateTime dt1 = DateTime.Now;
DateTime dt2 = DateTime.Now;
float confThreshold;
float nmsThreshold;
int num_stride = 3;
float[] strides = 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 = 0.8f;
nmsThreshold = 0.5f;
modelpath = "model/yolo_free_huge_widerface_192x320.onnx";
inpHeight = 192;
inpWidth = 320;
opencv_net = CvDnn.ReadNetFromOnnx(modelpath);
class_names = new List<string>();
class_names.Add("face");
num_class = 1;
image_path = "test_img/1.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);
float ratio = Math.Min(1.0f * inpHeight / image.Rows, 1.0f * inpWidth / image.Cols);
int neww = (int)(image.Cols * ratio);
int newh = (int)(image.Rows * ratio);
Mat dstimg = new Mat();
Cv2.Resize(image, dstimg, new OpenCvSharp.Size(neww, newh));
Cv2.CopyMakeBorder(dstimg, dstimg, 0, inpHeight - newh, 0, inpWidth - neww, BorderTypes.Constant);
BN_image = CvDnn.BlobFromImage(dstimg);
opencv_net.SetInput(BN_image);
Mat[] outs = new Mat[1] { 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);
float* pdata = (float*)outs[0].Data;
List<float> confidences = new List<float>();
List<Rect> boxes = new List<Rect>();
List<int> classIds = new List<int>();
for (int n = 0; n < num_stride; n++)
{
int num_grid_x = (int)Math.Ceiling(inpWidth / strides[n]);
int num_grid_y = (int)Math.Ceiling(inpHeight / strides[n]);
for (int i = 0; i < num_grid_y; i++)
{
for (int j = 0; j < num_grid_x; j++)
{
float box_score = pdata[4];
int max_ind = 0;
float max_class_socre = 0;
for (int k = 0; k < num_class; k++)
{
if (pdata[k + 5] > max_class_socre)
{
max_class_socre = pdata[k + 5];
max_ind = k;
}
}
max_class_socre = max_class_socre * box_score;
max_class_socre = (float)Math.Sqrt(max_class_socre);
if (max_class_socre > confThreshold)
{
float cx = (0.5f + j + pdata[0]) * strides[n];
float cy = (0.5f + i + pdata[1]) * strides[n];
float w = (float)(Math.Exp(pdata[2]) * strides[n]);
float h = (float)(Math.Exp(pdata[3]) * strides[n]);
float xmin = (float)((cx - 0.5 * w) / ratio);
float ymin = (float)((cy - 0.5 * h) / ratio);
float xmax = (float)((cx + 0.5 * w) / ratio);
float ymax = (float)((cy + 0.5 * h) / ratio);
int left = (int)((cx - 0.5 * w) / ratio);
int top = (int)((cy - 0.5 * h) / ratio);
int width = (int)(w / ratio);
int height = (int)(h / ratio);
confidences.Add(max_class_socre);
boxes.Add(new Rect(left, top, width, height));
classIds.Add(max_ind);
}
pdata += nout;
}
}
}
int[] indices;
CvDnn.NMSBoxes(boxes, confidences, confThreshold, nmsThreshold, out indices);
result_image = image.Clone();
for (int ii = 0; ii < indices.Length; ++ii)
{
int idx = indices[ii];
Rect box = boxes[idx];
Cv2.Rectangle(result_image, new OpenCvSharp.Point(box.X, box.Y), new OpenCvSharp.Point(box.X + box.Width, box.Y + box.Height), new Scalar(0, 0, 255), 2);
string label = class_names[classIds[idx]] + ":" + confidences[idx].ToString("0.00");
Cv2.PutText(result_image, label, new OpenCvSharp.Point(box.X, box.Y - 5), HersheyFonts.HersheySimplex, 1, new Scalar(0, 0, 255), 2);
}
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);
}
}
}
|
