using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace Check.Main.Infer
{
    public interface IDetector : IDisposable
    {
        /// <summary>
        /// 初始化检测器。
        /// </summary>
        /// <param name="modelPath">模型文件路径（对于传统算法可能是模板目录）</param>
        /// <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>
        void Initialize(string modelPath, object detectionSettings = null);

        /// <summary>
        /// 执行图像检测。
        /// </summary>
        /// <param name="image">待检测的图像。</param>
        /// <returns>包含检测结果（如OK/NG，得分，边界框等）的统一对象。</returns>
        DetectionResult Detect(Bitmap image);
    }

    /// <summary>
    /// 统一的检测结果类。
    /// </summary>
    public class DetectionResult
    {
        public bool IsOk { get; set; }
        public string Message { get; set; }
        public double Score { get; set; }
        public List<RectangleF> BoundingBoxes { get; set; } // 深度学习可能返回多个目标框

        // 如果需要，可以添加带有绘制结果的图像
        public Bitmap ResultImage { get; set; }

        public DetectionResult(bool isOk, string message = "Unknown", double score = 0.0, List<RectangleF> boundingBoxes = null, Bitmap resultImage = null)
        {
            IsOk = isOk;
            Message = message;
            Score = score;
            BoundingBoxes = boundingBoxes ?? new List<RectangleF>();
            ResultImage = resultImage;
        }
    }

    //// 辅助设置类，用于传递给 HalconTemplateDetector
    //public class HalconDetectionSettings
    //{
    //    public double ScoreThreshold { get; set; } = 0.5;
    //}

    // 辅助设置类，用于传递给 YoloDetector
    public class YoloDetectionSettings
    {
        public float ConfidenceThreshold { get; set; } = 0.25f;
        public float NmsThreshold { get; set; } = 0.45f;
    }

}