using OpenCvSharp;
using PaintDotNet.Adjust;
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace Metis.AutoAnalysis
{
    /// <summary>
    /// 寻找最差视场
    /// </summary>
    class WorstfieldFinder
    {
        public static Mat Find(Mat src, OpenCvSharp.Size size)
        {
            Mat gray = new Mat();
            Cv2.CvtColor(src, gray, ColorConversionCodes.BGR2GRAY);

            Mat mask = convert2Mask(gray);


            //去掉边缘
            Mat element = Cv2.GetStructuringElement(MorphShapes.Rect, new OpenCvSharp.Size(11, 11));
            Cv2.Erode(mask, mask, element);

            //取边缘
            Mat srcTemp = src.Clone();
            Mat edge = ImageSobel(srcTemp);
            if(edge == null)
            {
                Mat result1 = new Mat(src, new OpenCvSharp.Rect(new OpenCvSharp.Point(0, 0), size));
                return result1;
            }

            //把因为拼图造成的边缘去掉
            Cv2.BitwiseAnd(edge, mask, edge);

            Mat thr = new Mat();
            Cv2.Threshold(edge, thr, 50, 255, ThresholdTypes.Binary);

            OpenCvSharp.Point[][] contours = null;
            HierarchyIndex[] hierarchy = null;
            Cv2.FindContours(thr, out contours, out hierarchy, RetrievalModes.External, ContourApproximationModes.ApproxNone);

            var obj = new Mat(gray.Size(), MatType.CV_8UC1, Scalar.All(0));
            Cv2.DrawContours(obj, contours, -1, Scalar.All(255), -1);

            //遍历整个图形
            int step = 500;
            int maxNZ = -100;//非0点个数
            var tempLoc = new OpenCvSharp.Point();
            for (int y = 0; y < src.Height - size.Height; y += step)                
            {
                for (int x = 0; x < src.Width - size.Width; x += step)
                {
                    LogHelper.log.Debug(" Find x =" + x.ToString() + " y = " + y.ToString());
                    Rect rc = new Rect(x, y, size.Width, size.Height);
                    Mat roi = new Mat(obj, rc);
                    var countNZ = Cv2.CountNonZero(roi);
                    if(maxNZ < countNZ)
                    {
                        maxNZ = countNZ;
                        tempLoc = new Point(x, y);
                    }
                }
            }

            Mat result = new Mat(src, new Rect(tempLoc, size));

            return result;
        }

        /// <summary>
        /// 生成拼图后的掩码
        /// </summary>
        /// <param name="mat"></param>
        /// <returns></returns>
        private static Mat convert2Mask(Mat gray)
        {
            LogHelper.log.Debug(" convert2Mask 111");
            Mat thr = new Mat();
            Cv2.Threshold(gray, thr, 1, 255, ThresholdTypes.Binary);

            LogHelper.log.Debug(" convert2Mask 222");

            OpenCvSharp.Point[][] contours = null;
            HierarchyIndex[] hierarchy = null;
            Cv2.FindContours(thr, out contours, out hierarchy, RetrievalModes.External, ContourApproximationModes.ApproxNone);

            LogHelper.log.Debug(" convert2Mask 333");

            //生成拼图后实际图像的掩码
            var mask = new Mat(gray.Size(), MatType.CV_8UC1, Scalar.All(0));
            Cv2.DrawContours(mask, contours, -1, Scalar.All(255), -1);

            LogHelper.log.Debug(" convert2Mask 444");
            return mask;
        }

        public static Mat ImageSobel(Mat src)
        {
            Mat gray = null, xgrad = null, ygrad = null, output = null;
            try
            {
                //转为灰度
                gray = new Mat();
                Cv2.CvtColor(src, gray, ColorConversionCodes.BGR2GRAY);
                MatType m = src.Type();

                //求 X 和 Y 方向的梯度  Sobel  and scharr
                xgrad = new Mat();
                ygrad = new Mat();
                Cv2.Sobel(gray, xgrad, MatType.CV_16S, 1, 0, 3);
                Cv2.Sobel(gray, ygrad, MatType.CV_16S, 0, 1, 3);

                Cv2.ConvertScaleAbs(xgrad, xgrad);//缩放、计算绝对值并将结果转换为8位。不做转换的化显示不了，显示图相只能是8U类型 
                Cv2.ConvertScaleAbs(ygrad, ygrad);

                //加强边缘检测
                //Cv2.Scharr(gray, xgrad, -1, 1, 0, 3);
                //Cv2.Scharr(gray, ygrad, -1, 0, 1, 3);

                output = new Mat(gray.Size(), gray.Type());
                //图像混合相加(基于权重 0.5)不精确
                Cv2.AddWeighted(xgrad, 0.5, ygrad, 0.5, 0, output);

                return output;
            }
            catch (Exception ex)
            {
                
            }
            finally
            {
                if (gray != null) gray.Dispose();
                if (xgrad != null) gray.Dispose();
                if (ygrad != null) gray.Dispose();
                if (output != null) gray.Dispose();
                GC.Collect();
            }

            return null;
        }

    }
}