63 lines
2.1 KiB
C#
63 lines
2.1 KiB
C#
using System;
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using System.Collections.Generic;
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using System.Linq;
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using System.Text;
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using System.Threading.Tasks;
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namespace Check.Main.Infer
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{
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public interface IDetector : IDisposable
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{
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/// <summary>
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/// 初始化检测器。
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/// </summary>
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/// <param name="modelPath">模型文件路径（对于传统算法可能是模板目录）</param>
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/// <param name="detectionSettings">特定于检测器的设置对象（可选，可以用于传递阈值等）</param>
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void Initialize(string modelPath, object detectionSettings = null);
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/// <summary>
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/// 执行图像检测。
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/// </summary>
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/// <param name="image">待检测的图像。</param>
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/// <returns>包含检测结果（如OK/NG，得分，边界框等）的统一对象。</returns>
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DetectionResult Detect(Bitmap image);
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}
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/// <summary>
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/// 统一的检测结果类。
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/// </summary>
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public class DetectionResult
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{
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public bool IsOk { get; set; }
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public string Message { get; set; }
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public double Score { get; set; }
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public List<RectangleF> BoundingBoxes { get; set; } // 深度学习可能返回多个目标框
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// 如果需要，可以添加带有绘制结果的图像
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public Bitmap ResultImage { get; set; }
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public DetectionResult(bool isOk, string message = "Unknown", double score = 0.0, List<RectangleF> boundingBoxes = null, Bitmap resultImage = null)
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{
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IsOk = isOk;
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Message = message;
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Score = score;
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BoundingBoxes = boundingBoxes ?? new List<RectangleF>();
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ResultImage = resultImage;
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}
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}
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//// 辅助设置类，用于传递给 HalconTemplateDetector
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//public class HalconDetectionSettings
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//{
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// public double ScoreThreshold { get; set; } = 0.5;
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//}
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// 辅助设置类，用于传递给 YoloDetector
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public class YoloDetectionSettings
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{
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public float ConfidenceThreshold { get; set; } = 0.25f;
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public float NmsThreshold { get; set; } = 0.45f;
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}
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}
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