C# OpenVINO 人脸识别

效果

耗时

Preprocess: 1.41ms
Infer: 4.38ms
Postprocess: 0.03ms
Total: 5.82ms

项目

代码

using OpenCvSharp;
using Sdcb.OpenVINO;
using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Drawing;
using System.Text;
using System.Windows.Forms;namespace Sdcb.OpenVINO_人脸检测
{public partial class Form1 : Form{public Form1(){InitializeComponent();}string fileFilter = "*.*|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png";string image_path = "";string startupPath;string model_path;Mat src;StringBuilder sb = new StringBuilder();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;}private void button2_Click(object sender, EventArgs e){pictureBox2.Image = null;textBox1.Text = "";Model m = SharedOVCore.Instance.ReadModel(model_path);CompiledModel cm = SharedOVCore.Instance.CompileModel(m, "CPU");InferRequest ir = cm.CreateInferRequest();NCHW modelInputSize = m.Inputs.Primary.Shape.ToNCHW();Console.WriteLine(modelInputSize);Stopwatch sw = Stopwatch.StartNew();Mat image = src.Clone();Mat resized = image.Resize(new OpenCvSharp.Size(modelInputSize.Width, modelInputSize.Height));Mat normalized = Common.Normalize(resized);float[] extracted = Common.ExtractMat(normalized);using (Tensor tensor = Tensor.FromArray(extracted, modelInputSize.ToShape())){ir.Inputs.Primary = tensor;}double preprocessTime = sw.Elapsed.TotalMilliseconds;sw.Restart();ir.Run();double inferTime = sw.Elapsed.TotalMilliseconds;sw.Restart();Tensor output = ir.Outputs.Primary;Shape outputShape = output.Shape;Span<float> result = output.GetData<float>();List<DetectionResult> results = new List<DetectionResult>();for (int i = 0; i < outputShape[2]; ++i){float confidence = result[i * 7 + 2];int clsId = (int)result[i * 7 + 1];if (confidence > 0.5){int x1 = (int)(result[i * 7 + 3] * image.Width);int y1 = (int)(result[i * 7 + 4] * image.Height);int x2 = (int)(result[i * 7 + 5] * image.Width);int y2 = (int)(result[i * 7 + 6] * image.Height);results.Add(new DetectionResult(clsId, confidence, new Rect(x1, y1, x2 - x1, y2 - y1)));}}double postprocessTime = sw.Elapsed.TotalMilliseconds;double totalTime = preprocessTime + inferTime + postprocessTime;sb.Clear();foreach (DetectionResult r in results){Cv2.PutText(image, $"{r.Confidence:P2}", r.Rect.TopLeft, HersheyFonts.HersheyPlain, 2, Scalar.Red, 2);sb.AppendLine($"{r.Confidence:P2}");Cv2.Rectangle(image, r.Rect, Scalar.Red, 3);}sb.AppendLine($"Preprocess: {preprocessTime:F2}ms");sb.AppendLine($"Infer: {inferTime:F2}ms");sb.AppendLine($"Postprocess: {postprocessTime:F2}ms");sb.AppendLine($"Total: {totalTime:F2}ms");//Cv2.PutText(image, $"Preprocess: {preprocessTime:F2}ms", new OpenCvSharp.Point(10, 20), HersheyFonts.HersheyPlain, 1, Scalar.Red);//Cv2.PutText(image, $"Infer: {inferTime:F2}ms", new OpenCvSharp.Point(10, 40), HersheyFonts.HersheyPlain, 1, Scalar.Red);//Cv2.PutText(image, $"Postprocess: {postprocessTime:F2}ms", new OpenCvSharp.Point(10, 60), HersheyFonts.HersheyPlain, 1, Scalar.Red);//Cv2.PutText(image, $"Total: {totalTime:F2}ms", new OpenCvSharp.Point(10, 80), HersheyFonts.HersheyPlain, 1, Scalar.Red);textBox1.Text = sb.ToString();pictureBox2.Image = new Bitmap(image.ToMemoryStream());}private void Form1_Load(object sender, EventArgs e){startupPath = System.Windows.Forms.Application.StartupPath;model_path = startupPath + "\\face-detection-0200.xml";}}
}

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