using CandyboxPlugin.Detectors;
using CandyboxPlugin.Geometry;
using CandyboxPlugin.Voronoi;
using OpenCvSharp;
using System.Diagnostics;
using System.Drawing.Imaging;
using System.Text.Json;
using Lindt.Candybox.Demo;
using VisionBuilder.UI.Common.NullClasses;
using Point = System.Drawing.Point;
using Size = OpenCvSharp.Size;

namespace CandyboxPlugin.Recipe
{
    //todo: update camera settings according to learned parameters
    public class HistoRecipe
    {
        private readonly string _recipeName;

        private CandyDetector _learner;
        private BlisterDetector _blister;
        
        private DefaultRectangle2Algorithm _rectangle2;
        private LearningParameters _learnedParameters;
        private ColorHeatMap _colorHeatMap;


        private Size AnalysisSize { get; }= new Size(512, 512);
        Size ThumbnailSize { get; } = new Size(256, 200);

        public const string RECIPES_DIRECTORY = "..\\Data\\Recipes";

        public HistoRecipe(string recipeName)
        {
            _recipeName = recipeName;
            _configurationPath = Path.GetFullPath(Path.Combine(RECIPES_DIRECTORY, _recipeName + ".json"));

            _learner = new CandyDetector();
            _blister = new BlisterDetector();

            _rectangle2 = new DefaultRectangle2Algorithm();
            _learnedParameters = new LearningParameters();
            _colorHeatMap = new ColorHeatMap(255);

            Reload();
        }

        public void Reload()
        {
            lock (_lockObject)
            {
                if (File.Exists(_configurationPath))
                {
                    _learnedParameters =
                        JsonSerializer.Deserialize<LearningParameters>(File.ReadAllText(_configurationPath));
                }
            }
        }

        public void LearnContours(OpenCvSharp.Point[][] contours, Mat image, List<VectorLine> cuts, bool relearn)
        {
            lock (_lockObject)
            {
                _learnedParameters = relearn ? new LearningParameters() : _learnedParameters;
                
                // Convert cuts to be relative to blister center
                
                
                _learnedParameters.Cuts = cuts;
                
                if (_learnedParameters.CandyParameters.Count == 0)//initial learning
                {
                    _learnedParameters.BlisterAngle = _blisterAngle;
                    _learnedParameters.BlisterPosition = _blisterCenter;
                    _learnedParameters.ImageWidth = (int)(_blisterEdge / 512f * 1800f);
                    for (int i = 0; i < contours.Length; i++)
                    {
                        var hist = CalcHist(contours, i, _resizedMat, out var outerRadius, out var innerRadius);
                        var moments = Cv2.Moments(contours[i]);
                        var cX = (int)(moments.M10 / moments.M00);
                        var cY = (int)(moments.M01 / moments.M00);
                        hist.GetArray(out float[] histData);
                        var p = new CandyParameter()
                        {
                            Position = new Point(cX, cY),
                            Histogram = new Queue<float[]>(),
                            OuterRadius = (int)outerRadius,
                            InnerRadius = (int)innerRadius
                        };
                        p.Histogram.Enqueue(histData);
                        _learnedParameters.CandyParameters.Add(p);
                    }
                    
                }
                else
                {
                    foreach (CandyParameter parameter in _learnedParameters.CandyParameters)
                    {

                        parameter.ResetPoint();
                        parameter.RotatePoint(Point.Empty, _blisterAngle - _learnedParameters.BlisterAngle);

                    }

                    for (int i = 0; i < contours.Length; i++)
                    {
                        var hist = CalcHist(contours, i, _resizedMat, out var outerRadius, out var innerRadius);
                        var moments = Cv2.Moments(contours[i]);
                        var cX = (int)(moments.M10 / moments.M00);
                        var cY = (int)(moments.M01 / moments.M00);
                        hist.GetArray(out float[] histData);
                        var point = ClosestPoint(_blisterCenter, cX, cY, (int)outerRadius, (int)innerRadius);
                        point.Histogram.Enqueue(histData);
                        if (point.Histogram.Count > _learnedParameters.Configuration.MemoryBuffer)
                        {
                            point.Histogram.Dequeue();
                        }

                    }
                    foreach (CandyParameter parameter in _learnedParameters.CandyParameters)
                    {

                        parameter.ResetPoint();


                    }
                }

                File.WriteAllText(_configurationPath, JsonSerializer.Serialize(_learnedParameters, new JsonSerializerOptions() { WriteIndented = true }));
                var fullSamplePath = Path.GetFullPath(Path.Combine("..\\Data\\Samples", _recipeName + ".bmp"));
                Directory.CreateDirectory(Path.GetDirectoryName(fullSamplePath));
                image.Resize(ThumbnailSize).SaveImage(fullSamplePath);
            }
        }

        public HistoRecipe Clone()
        {
            var clone = new HistoRecipe(_recipeName);
            return clone;
        }

        public Point BlisterCenter => _blisterCenter;

        public ProcessingResult ProcessImage(Mat image)
        {
            lock (_lockObject)
            {
                var sw = Stopwatch.StartNew();

                try
                {
                    var framedImage = new Mat(new Size(1800, 1408),MatType.CV_8UC3,Scalar.FromRgb(36, 67, 182));
                    // draw the image in top left corner of framed image
                    // this does not actually create new Mat. it just creates a header for the region of interest
                    image.CopyTo(framedImage[0, image.Height, 0, image.Width]);

                    // add alpha channel
                    var rgb = framedImage;
                    framedImage = framedImage.CvtColor(ColorConversionCodes.BGR2BGRA);


                    var resized = rgb.Resize(AnalysisSize);


                    _resizedMat = resized;
                    var sw1 = Stopwatch.StartNew();


                    Mat res = _learner.Eval(resized);
                    Mat resBlister = _blister.Eval(resized);

                    
                    var element = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(50, 50));
                    Mat blisterOpened = resBlister.Threshold(128,255,ThresholdTypes.Binary).MorphologyEx(MorphTypes.Open,element);
                    

                    resBlister.Dispose();
                    resBlister = blisterOpened;
                    

                    sw1.Stop();
                    Console.WriteLine("AI Time:" + sw1.ElapsedMilliseconds);
                    Mat inverted = null;
                    Mat overlayMat = new Mat(res.Width, res.Height, MatType.CV_8UC4, new Scalar(0, 0, 0, 0));
                    bool wasError = false;
                    List<int> errorPoints = new List<int>();
                    OpenCvSharp.Point[] blisterRectangle;
                    Mat numbersOverlay = new Mat(512, 512, MatType.CV_8UC4, new Scalar(0, 0, 0, 0));
                    List<EErrorReason> errorReason = new List<EErrorReason>();
                    using (var tracker = new ResourcesTracker())
                    {

                        blisterRectangle = FindBlister(resBlister, out _blisterAngle, out _blisterCenter,
                            out _blisterEdge);




                        if (_learnedParameters.CandyParameters.Count > 0)
                        {

                            DelaunayTriangulator triangulator = new DelaunayTriangulator();
                            triangulator.GenerateBorder(512, 512);

                            var points=_learnedParameters.CandyParameters
                                .Select((x, i) =>
                                    new VoronoiPoint(
                                        x.Position.X + _blisterCenter.X - _learnedParameters.BlisterPosition.X,
                                        x.Position.Y + _blisterCenter.Y - _learnedParameters.BlisterPosition.Y
                                        ))
                                .ToList();
                            var triangles = triangulator.BowyerWatson(_learnedParameters.CandyParameters
                                .Select((x,i) =>
                                    new VoronoiPoint(
                                        x.Position.X + _blisterCenter.X - _learnedParameters.BlisterPosition.X,
                                        x.Position.Y + _blisterCenter.Y - _learnedParameters.BlisterPosition.Y
                                        ))
                                .ToList());


                            var edges = Voronoi.Voronoi.GenerateEdgesFromDelaunay(triangles);
                            foreach (Edge edge in edges)
                            {
                                Cv2.Line(
                                    res,
                                    new OpenCvSharp.Point(edge.Point1.X, edge.Point1.Y),
                                    new OpenCvSharp.Point(edge.Point2.X, edge.Point2.Y),
                                    new Scalar(0, 0, 0), // Black color in BGR
                                    3 // Thickness
                                );
                            }

                        }
                        foreach (VectorLine cut in _learnedParameters.Cuts)
                        {
                            // Convert from relative to absolute coordinates
                            var absoluteStart = new OpenCvSharp.Point(
                                cut.StartPoint.X + _blisterCenter.X, 
                                cut.StartPoint.Y + _blisterCenter.Y
                            );
                            var absoluteEnd = new OpenCvSharp.Point(
                                cut.EndPoint.X + _blisterCenter.X, 
                                cut.EndPoint.Y + _blisterCenter.Y
                            );
                            
                            Cv2.Line(res, absoluteStart, absoluteEnd, new Scalar(0, 0, 0), 3);
                        }


                        var mat = res;
                        Cv2.Threshold(mat, mat, 128, 255, ThresholdTypes.Binary);
                        
                        OpenCvSharp.Point[][] contours;
                        contours = mat.FindContoursAsArray(RetrievalModes.External,
                            ContourApproximationModes.ApproxNone);

                        contours = contours.Where(x => Cv2.ContourArea(x) > 500).ToArray();


                        
                        var sw2 = Stopwatch.StartNew();
                        LastContours = contours;
                        
                        int c = 0;
                        foreach (CandyParameter parameter in _learnedParameters.CandyParameters)
                        {

                            parameter.ResetPoint();
                            parameter.RotatePoint(Point.Empty, _blisterAngle - _learnedParameters.BlisterAngle);
                            var coordX = parameter.Position.X +
                                         (_blisterCenter.X - _learnedParameters.BlisterPosition.X);
                            var coordY = parameter.Position.Y +
                                         (_blisterCenter.Y - _learnedParameters.BlisterPosition.Y);

                            // Draw filled white circle (ellipse)
                            Cv2.Circle(numbersOverlay, new OpenCvSharp.Point(coordX, coordY), 10, new Scalar(255, 255, 255, 255), thickness: -1);

                            // Draw black ellipse outline
                            Cv2.Ellipse(numbersOverlay, new OpenCvSharp.Point(coordX, coordY), new Size(10, 10), 0, 0, 360, new Scalar(0, 0, 0, 255), thickness: 1);

                            // Draw the number as text (centered, adjust offset as needed)
                            Cv2.PutText(
                                numbersOverlay,
                                c.ToString(),
                                new OpenCvSharp.Point(coordX - 7, coordY + 7), // Y offset for baseline alignment
                                HersheyFonts.HersheySimplex,
                                0.4, // Font scale
                                new Scalar(0,0,0,255),
                                1,
                                LineTypes.AntiAlias
                            );

                            

                            bool found = false;
                            for (int i = 0; i < contours.Length; i++)
                            {
                                if (Cv2.PointPolygonTest(contours[i],
                                        new Point2f(coordX, coordY), false) > 0)
                                {
                                    var hist = CalcHist(contours, i, _resizedMat, out var outerRadius,
                                        out var innerRadius);
                                    var correl = 0;
                                    foreach (float[] h in parameter.Histogram)
                                    {
                                        Mat histC = new Mat(new Size(1, 125), MatType.CV_32FC1);
                                        histC.SetArray(h);

                                        var correl_0 = Cv2.CompareHist(histC, hist, HistCompMethods.Correl) * 100;
                                        if (correl_0 > correl)
                                        {
                                            correl = (int) correl_0;
                                        }
                                    }


                                    if (_learnedParameters.Configuration.IgnoreCorrelation.Contains(c))
                                        correl = 100;
                                    if (correl > _learnedParameters.Configuration.SimilarityTolerance)
                                    {
                                        var min = _learnedParameters.Configuration.SimilarityTolerance;
                                        var max = 100;
                                        var value = correl;
                                        value = value < min ? min : value;


                                        var value2 = (int) Map(value, min, max, 0, 255);

                                        var color = _colorHeatMap.GetColorForValue(value2, 255);
                                        Cv2.DrawContours(overlayMat, contours, i,
                                            new Scalar(color.B, color.G, color.R, color.A));
                                        found = true;
                                    }
                                    else
                                    {
                                        Cv2.DrawContours(overlayMat, contours, i, OpaqueScalar(Scalar.Red));
                                        Console.WriteLine($"{c} wrong type. similarity is {correl}%");
                                        errorReason.Add(EErrorReason.WrongType);
                                        ErrorTextHelper.DrawErrorText(overlayMat, new OpenCvSharp.Point(coordX, coordY),
                                            EErrorReason.WrongType);
                                        errorPoints.Add(c);
                                        found = true;
                                        wasError = true;
                                        break;
                                    }

                                    var outerDiff = parameter.OuterRadius - outerRadius;

                                    if (Math.Abs(outerDiff / parameter.OuterRadius) * 100 >
                                        _learnedParameters.Configuration.OuterTolerance && outerDiff < 0)
                                    {
                                        Cv2.DrawContours(overlayMat, contours, i, OpaqueScalar(Scalar.Red));
                                        errorReason.Add(EErrorReason.WrongSize);
                                        ErrorTextHelper.DrawErrorText(overlayMat, new OpenCvSharp.Point(coordX, coordY),
                                            EErrorReason.WrongSize);
                                        Console.WriteLine(
                                            $"{c} wrong outer size. expected {parameter.OuterRadius}, got {outerRadius} ({Math.Abs(outerDiff / parameter.OuterRadius) * 100f})");
                                        errorPoints.Add(c);

                                        wasError = true;
                                        break;
                                    }

                                    var innerDiff = parameter.InnerRadius - innerRadius;


                                    if (Math.Abs(innerDiff / parameter.InnerRadius) * 100 >
                                        _learnedParameters.Configuration.InnerTolerance && innerDiff < 0)
                                    {
                                        Cv2.DrawContours(overlayMat, contours, i, OpaqueScalar(Scalar.Red));
                                        Console.WriteLine(
                                            $"{c} wrong inner size. expected {parameter.InnerRadius}, got {innerRadius} ({Math.Abs(innerDiff / parameter.InnerRadius) * 100f})");
                                        errorReason.Add(EErrorReason.WrongSize);
                                        ErrorTextHelper.DrawErrorText(overlayMat, new OpenCvSharp.Point(coordX, coordY),
                                            EErrorReason.WrongSize);

                                        errorPoints.Add(c);

                                        wasError = true;
                                        break;
                                    }


                                    break;
                                }


                            }

                            if (!found)
                            {
                                wasError = true;
                                errorReason.Add(EErrorReason.Missing);

                                errorPoints.Add(c);
                                Cv2.Circle(overlayMat, coordX, coordY, 10, OpaqueScalar(Scalar.Red), Cv2.FILLED);
                                ErrorTextHelper.DrawErrorText(overlayMat, new OpenCvSharp.Point(coordX, coordY),
                                    EErrorReason.Missing);
                            }

                            c++;

                        }

                        
                        if (wasError)
                        {
                            Cv2.DrawContours(overlayMat, new[] {blisterRectangle}, 0, OpaqueScalar(Scalar.Red),
                                thickness: 5);
                        }
                        else
                        {
                            Cv2.DrawContours(overlayMat, new[] {blisterRectangle}, 0, OpaqueScalar(Scalar.Pink),
                                thickness: 1);
                        }



                        inverted = overlayMat;
                        sw2.Stop();
                        Console.WriteLine("CVTime:" + sw2.ElapsedMilliseconds);
                    }





                    sw.Stop();
                    Console.WriteLine("Time:" + sw.ElapsedMilliseconds);

                    inverted = Overlap(numbersOverlay, inverted);
                    var final = inverted.Resize(framedImage.Size());
                    final = Overlap(final,framedImage);

                    if (_learnedParameters.ImageWidth > 0)
                    {
                        float cut = _learnedParameters.ImageWidth;
                        Cv2.Line(final, new OpenCvSharp.Point(cut, 0), new OpenCvSharp.Point(cut, 1408), Scalar.Red, 1);
                    }

                    if(_learnedParameters.CandyParameters.Count==0)errorReason.Add(EErrorReason.NotLearned);

                    Thread.Sleep(50);

                    return new ProcessingResult(framedImage, final, 
                        _learnedParameters.CandyParameters.Count == 0 || wasError, (int) sw.ElapsedMilliseconds,
                        errorReason)
                    {
                        BlisterRectangle = blisterRectangle.Select(x => new Point(x.X, x.Y)).ToList(),
                        ErrorPoints = errorPoints
                    };
                }
                catch(Exception ex)
                {
                    Thread.Sleep(50);
                    return new ProcessingResult(image, image,
                        true, (int)sw.ElapsedMilliseconds,
                        new List<EErrorReason>() {EErrorReason.Unknown})
                    {
                        
                    };
                }
            }
        }

        public OpenCvSharp.Point[][] LastContours { get; set; }

        public LearningParameters LearnedParameters => _learnedParameters;

        private CandyParameter ClosestPoint(Point blisterCenter, int cX, int cY, int outerRadius,
            int innerRadius)
        {
            CandyParameter closest = null;
            double minDistance = double.MaxValue;
            foreach (CandyParameter parameter in _learnedParameters.CandyParameters)
            {
                var coordX = parameter.Position.X +
                             (blisterCenter.X - _learnedParameters.BlisterPosition.X);
                var coordY = parameter.Position.Y +
                             (blisterCenter.Y - _learnedParameters.BlisterPosition.Y);
                var distance = Distance(coordX - cX, coordY - cY);
                if ( distance< minDistance)
                {
                    minDistance = distance;
                    closest = parameter;
                }
            }

            return closest;

        }

        private static double Distance(int x, int y)
        {
            return Math.Sqrt(x * x + y * y);
        }

       

        static void ShowHistogram(Mat hist)
        {
            Mat render = new Mat(new Size(125, 125), MatType.CV_8UC3, Scalar.All(255));
            double minVal, maxVal;
            Cv2.MinMaxLoc(hist, out minVal, out maxVal);
            Scalar color = Scalar.All(100);
            // Scales and draws histogram
            hist = hist * (maxVal != 0 ? 125 / maxVal : 0.0);
            hist.GetArray(out float[] histArr);
            for (int j = 0; j < 125; ++j)
            {
                render.Rectangle(
                    new OpenCvSharp.Point(j , render.Rows - (int)histArr[j]),
                    new OpenCvSharp.Point(j + 1 , render.Rows),
                    color,
                    -1);
            }
            Cv2.ImShow("hist",render);
            Cv2.WaitKey(1);
        }
        

        public static double Map (double value, double fromSource, double toSource, double fromTarget, double toTarget)
        {
            return (value - fromSource) / (toSource - fromSource) * (toTarget - fromTarget) + fromTarget;
        }
        private static object _lockObject = new object();
        
        private float _blisterAngle;
        private Point _blisterCenter;
        private int _blisterEdge;
        private Mat _resizedMat;
        private readonly string _configurationPath;


        private static Scalar OpaqueScalar(Scalar scalar)
        {
            return new Scalar(scalar.Val0, scalar.Val1, scalar.Val2, 255);
        }
        private static Mat CalcHist(OpenCvSharp.Point[][] contours, int i, Mat resizedMat,out float outerRadius,out float innerRadius)
        {
            var c = new Mat(new Size(512, 512), MatType.CV_8UC1,Scalar.Black);

            Cv2.DrawContours(c, contours, i, Scalar.White, thickness: Cv2.FILLED);

            
            Cv2.MinEnclosingCircle(contours[i],out var center,out outerRadius);

            var distance = c.DistanceTransform(DistanceTypes.L2, DistanceTransformMasks.Mask5);
            distance.MinMaxIdx(out _,out var innerRadiusD);
            innerRadius = (float) innerRadiusD;


            var hist = new Mat();
            Cv2.CalcHist(new[] {resizedMat}, new[] {0, 1, 2}, c, hist, 3, new[] {5, 5, 5},
                new[] {new Rangef(0, 256), new Rangef(0, 256), new Rangef(0, 256)});
            Cv2.Normalize(hist, hist);
            hist = hist.Reshape(1, 125, 1);


            //if (i == 22)
            //{
            //    ShowHistogram(hist);
            //}
            

            return hist;
        }

        private OpenCvSharp.Point[] FindBlister(Mat resBlister,out float blisterAngle,out Point center, out int blisterEdge)
        {
            var blisterMat = resBlister.Threshold(128, 255, ThresholdTypes.Binary);

            var blisterContours = blisterMat.FindContoursAsArray(RetrievalModes.List, ContourApproximationModes.ApproxNone);
            var cnt = blisterContours.Length;
            int? blisterArea = null;
            blisterEdge = 0;
            for (int i = 0; i < cnt; i++)
            {
                
                var area = Cv2.ContourArea(blisterContours[i]);
                if (area>5000)
                {
                    var max= blisterContours[i].Max(x => x.X);
                    if (max>blisterEdge)
                    {
                        blisterEdge = max;
                    }
                    var rect2 = Cv2.MinAreaRect(blisterContours[i]);
                    var tmp = rect2.Angle;
                    if (tmp > 15)
                    {
                        tmp = -(90 - tmp);
                    }
                    blisterAngle = tmp/180f*3.14f;

                    center = new Point((int)rect2.Center.X, (int)rect2.Center.Y);
                    Console.WriteLine("blister angle:"+blisterAngle);
                    //var c = blisterMat.CvtColor(ColorConversionCodes.GRAY2BGR);
                    //Cv2.Rectangle(c,rect2.BoundingRect(),Scalar.Red);
                    //Cv2.ImShow("test",c);
                    //Cv2.WaitKey(0);
                    return rect2.Points().Select(x=>new OpenCvSharp.Point(x.X,x.Y)).ToArray();
                    
                }
            }

            throw new Exception("Blister not found");
        }

        public static Bitmap SetImageOpacity(Bitmap image, float opacity)
        {
            try
            {
                //create a Bitmap the size of the image provided  
                var bmp = new Bitmap(image.Width, image.Height);

                //create a graphics object from the image  
                using (var gfx = Graphics.FromImage(bmp))
                {
                    //create a color matrix object  
                    var matrix = new ColorMatrix();

                    //set the opacity  
                    matrix.Matrix33 = opacity;

                    //create image attributes  
                    var attributes = new ImageAttributes();

                    //set the color(opacity) of the image  
                    attributes.SetColorMatrix(matrix, ColorMatrixFlag.Default, ColorAdjustType.Bitmap);

                    //now draw the image  
                    gfx.DrawImage(image, new Rectangle(0, 0, bmp.Width, bmp.Height), 0, 0, image.Width, image.Height,
                        GraphicsUnit.Pixel, attributes);
                }

                return bmp;
            }
            catch (Exception ex)
            {
                //MessageBox.Show(ex.Message);
                throw ex;
                //return null;
            }
        }

        public static Mat Overlap(Mat source1, Mat source2)
        {
            var target = new Mat(source2.Size(),source2.Type());
            Cv2.Split(source1, out Mat[] src2Channels);
            var alpha = src2Channels[3];
            source2.CopyTo(target);
            source1.CopyTo(target,alpha);
            return target;
        }

        public int GetCameraWidth()
        {
            return _learnedParameters.ImageWidth;
        }
        
    }
}