目录
效果
模型信息
项目
代码
数据集
下载
C# OpenVINO Nail Seg 指甲分割 指甲检测
效果
模型信息
Model Properties
————————-
date：2024-02-29T16:41:28.273760
author：Ultralytics
task：segment
version：8.1.18
stride：32
batch：1
imgsz：[640, 640]
names：{0: ‘Nail’}
—————————————————————
Inputs
————————-
name：images
tensor：Float[1, 3, 640, 640]
—————————————————————
Outputs
————————-
name：output0
tensor：Float[1, 37, 8400]
name：output1
tensor：Float[1, 32, 160, 160]
—————————————————————
项目
代码
using OpenCvSharp;
using Sdcb.OpenVINO;
using Sdcb.OpenVINO.Natives;
using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Drawing;
using System.IO;
using System.Text;
using System.Windows.Forms;
namespace OpenVINO_Seg
{
public partial class Form1 : Form
{
public Form1()
{
InitializeComponent();
}
string fileFilter = “*.*|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png”;
string image_path = “”;
string startupPath;
string model_path;
string classer_path;
Mat src;
SegmentationResult result_pro;
Mat result_image;
Result seg_result;
StringBuilder sb = new StringBuilder();
float[] det_result_array = new float[8400 * 37];
float[] proto_result_array = new float[32 * 160 * 160];
// 识别结果类型
public string[] class_names;
private void button1_Click(object sender, EventArgs e)
{
OpenFileDialog ofd = new OpenFileDialog();
ofd.Filter = fileFilter;
if (ofd.ShowDialog() != DialogResult.OK) return;
pictureBox1.Image = null;
image_path = ofd.FileName;
pictureBox1.Image = new Bitmap(image_path);
textBox1.Text = “”;
src = new Mat(image_path);
pictureBox2.Image = null;
}
unsafe private void button2_Click(object sender, EventArgs e)
{
if (pictureBox1.Image == null)
{
return;
}
pictureBox2.Image = null;
textBox1.Text = “”;
sb.Clear();
src = new Mat(image_path);
Model rawModel = OVCore.Shared.ReadModel(model_path);
PrePostProcessor pp = rawModel.CreatePrePostProcessor();
PreProcessInputInfo inputInfo = pp.Inputs.Primary;
inputInfo.TensorInfo.Layout = Sdcb.OpenVINO.Layout.NHWC;
inputInfo.ModelInfo.Layout = Sdcb.OpenVINO.Layout.NCHW;
Model m = pp.BuildModel();
CompiledModel cm = OVCore.Shared.CompileModel(m, “CPU”);
InferRequest ir = cm.CreateInferRequest();
Shape inputShape = m.Inputs[0].Shape;
float[] factors = new float[4];
factors[0] = 1f * src.Width / inputShape[2];
factors[1] = 1f * src.Height / inputShape[1];
factors[2] = src.Rows;
factors[3] = src.Cols;
result_pro = new SegmentationResult(class_names, factors,0.3f,0.5f);
Stopwatch stopwatch = new Stopwatch();
Mat resized = src.Resize(new OpenCvSharp.Size(inputShape[2], inputShape[1]));
Mat f32 = new Mat();
resized.ConvertTo(f32, MatType.CV_32FC3, 1.0 / 255);
using (Tensor input = Tensor.FromRaw(
new ReadOnlySpan((void*)f32.Data, (int)((long)f32.DataEnd – (long)f32.DataStart)),
new Shape(1, f32.Rows, f32.Cols, 3),
ov_element_type_e.F32))
{
ir.Inputs.Primary = input;
}
double preprocessTime = stopwatch.Elapsed.TotalMilliseconds;
stopwatch.Restart();
ir.Run();
double inferTime = stopwatch.Elapsed.TotalMilliseconds;
stopwatch.Restart();
using (Tensor output_det = ir.Outputs[0])
using (Tensor output_proto = ir.Outputs[1])
{
det_result_array = output_det.GetData().ToArray();
proto_result_array = output_proto.GetData().ToArray();
seg_result = result_pro.process_result(det_result_array, proto_result_array);
double postprocessTime = stopwatch.Elapsed.TotalMilliseconds;
stopwatch.Stop();
double totalTime = preprocessTime + inferTime + postprocessTime;
result_image = src.Clone();
Mat masked_img = new Mat();
// 将识别结果绘制到图片上
for (int i = 0; i {
Cv2.Rectangle(result_image, seg_result.rects[i], new Scalar(0, 0, 255), 2, LineTypes.Link8);
Cv2.Rectangle(result_image, new OpenCvSharp.Point(seg_result.rects[i].TopLeft.X, seg_result.rects[i].TopLeft.Y – 20),
new OpenCvSharp.Point(seg_result.rects[i].BottomRight.X, seg_result.rects[i].TopLeft.Y), new Scalar(0, 255, 255), -1);
Cv2.PutText(result_image, seg_result.classes[i] + “-” + seg_result.scores[i].ToString(“0.00”),
new OpenCvSharp.Point(seg_result.rects[i].X, seg_result.rects[i].Y – 5),
HersheyFonts.HersheySimplex, 0.6, new Scalar(0, 0, 0), 1);
Cv2.AddWeighted(result_image, 0.5, seg_result.masks[i], 0.5, 0, masked_img);
sb.AppendLine($”{seg_result.classes[i]}:{seg_result.scores[i]:P0}”);
}
if (seg_result.length > 0)
{
if (pictureBox2.Image != null)
{
pictureBox2.Image.Dispose();
}
pictureBox2.Image = new Bitmap(masked_img.ToMemoryStream());
sb.AppendLine($”Preprocess: {preprocessTime:F2}ms”);
sb.AppendLine($”Infer: {inferTime:F2}ms”);
sb.AppendLine($”Postprocess: {postprocessTime:F2}ms”);
sb.AppendLine($”Total: {totalTime:F2}ms”);
textBox1.Text = sb.ToString();
}
else
{
textBox1.Text = “无信息”;
}
masked_img.Dispose();
result_image.Dispose();
}
}
private void Form1_Load(object sender, EventArgs e)
{
image_path = “1.jpg”;
pictureBox1.Image = new Bitmap(image_path);
startupPath = Application.StartupPath;
model_path = startupPath + “nails_seg_s_yolov8.onnx”;
classer_path = startupPath + “lable.txt”;
List str = new List();
StreamReader sr = new StreamReader(classer_path);
string line;
while ((line = sr.ReadLine()) != null)
{
str.Add(line);
}
class_names = str.ToArray();
}
}
}
using OpenCvSharp;
using Sdcb.OpenVINO;
using Sdcb.OpenVINO.Natives;
using System;
using System.Collections.Generic;
using Sys服务器托管网tem.Diagnostics;
using System.Drawing;
using System.IO;
using System.Text;
using System.Windows.Forms;
namespace OpenVINO_Seg
{
public partial class Form1 : Form
{
public Form1()
{
InitializeComponent();
}
string fileFilter = "*.*|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png";
string image_path = "";
string startupPath;
string model_path;
string classer_path;
Mat src;
SegmentationResult result_pro;
Mat result_image;
Result seg_result;
StringBuilder sb = new StringBuilder();
float[] det_result_array = new float[8400 * 37];
float[] proto_result_array = new float[32 * 160 * 160];
// 识别结果类型
public string[] class_names;
private void button1_Click(object sender, EventArgs e)
{
OpenFileDialog ofd = new OpenFileDialog();
ofd.Filter = fileFilter;
if (ofd.ShowDialog() != DialogResult.OK) return;
pictureBox1.Image = null;
image_path = ofd.FileName;
pictureBox1.Image = new Bitmap(image_path);
textBox1.Text = "";
src = new Mat(image_path);
pictureBox2.Image = null;
}
unsafe private void button2_Click(object sender, EventArgs e)
{
if (pictureBox1.Image == null)
{
return;
}
pictureBox2.Image = null;
textBox1.Text = "";
sb.Clear();
src = new Mat(image_path);
Model rawModel = OVCore.Shared.ReadModel(model_path);
PrePostProcessor pp = rawModel.CreatePrePostProcessor();
PreProcessInputInfo inputInfo = pp.Inputs.Primary;
inputInfo.TensorInfo.Layout = Sdcb.OpenVINO.Layout.NHWC;
inputInfo.ModelInfo.Layout = Sdcb.OpenVINO.Layout.NCHW;
Model m = pp.BuildModel();
CompiledModel cm = OVCore.Shared.CompileModel(m, "CPU");
InferRequest ir = cm.CreateInferRequest();
Shape inputShape = m.Inputs[0].Shape;
float[] factors = new float[4];
factors[0] = 1f * src.Width / inputShape[2];
factors[1] = 1f * src.Height / inputSha服务器托管网pe[1];
factors[2] = src.Rows;
factors[3] = src.Cols;
result_pro = new SegmentationResult(class_names, factors,0.3f,0.5f);
Stopwatch stopwatch = new Stopwatch();
Mat resized = src.Resize(new OpenCvSharp.Size(inputShape[2], inputShape[1]));
Mat f32 = new Mat();
resized.ConvertTo(f32, MatType.CV_32FC3, 1.0 / 255);
using (Tensor input = Tensor.FromRaw(
new ReadOnlySpan((void*)f32.Data, (int)((long)f32.DataEnd - (long)f32.DataStart)),
new Shape(1, f32.Rows, f32.Cols, 3),
ov_element_type_e.F32))
{
ir.Inputs.Primary = input;
}
double preprocessTime = stopwatch.Elapsed.TotalMilliseconds;
stopwatch.Restart();
ir.Run();
double inferTime = stopwatch.Elapsed.TotalMilliseconds;
stopwatch.Restart();
using (Tensor output_det = ir.Outputs[0])
using (Tensor output_proto = ir.Outputs[1])
{
det_result_array = output_det.GetData().ToArray();
proto_result_array = output_proto.GetData().ToArray();
seg_result = result_pro.process_result(det_result_array, proto_result_array);
double postprocessTime = stopwatch.Elapsed.TotalMilliseconds;
stopwatch.Stop();
double totalTime = preprocessTime + inferTime + postprocessTime;
result_image = src.Clone();
Mat masked_img = new Mat();
// 将识别结果绘制到图片上
for (int i = 0; i 0)
{
if (pictureBox2.Image != null)
{
pictureBox2.Image.Dispose();
}
pictureBox2.Image = new Bitmap(masked_img.ToMemoryStream());
sb.AppendLine($"Preprocess: {preprocessTime:F2}ms");
sb.AppendLine($"Infer: {inferTime:F2}ms");
sb.AppendLine($"Postprocess: {postprocessTime:F2}ms");
sb.AppendLine($"Total: {totalTime:F2}ms");
textBox1.Text = sb.ToString();
}
else
{
textBox1.Text = "无信息";
}
masked_img.Dispose();
result_image.Dispose();
}
}
private void Form1_Load(object sender, EventArgs e)
{
image_path = "1.jpg";
pictureBox1.Image = new Bitmap(image_path);
startupPath = Application.StartupPath;
model_path = startupPath + "nails_seg_s_yolov8.onnx";
classer_path = startupPath + "lable.txt";
List str = new List();
StreamReader sr = new StreamReader(classer_path);
string line;
while ((line = sr.ReadLine()) != null)
{
str.Add(line);
}
class_names = str.ToArray();
}
}
}
数据集
下载
指甲数据集带标注信息下载
源码下载
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