using System;
using System.Numerics;
using Emgu.CV;
using Emgu.CV.Structure;
using Emgu.CV.Util;

namespace ImageMinipulation {
    
    /// <summary>
    /// All programs are made using videos from (Programming with Chris) video seiress
    /// </summary>
    public class vanGoghFilters
    {
        /// <summary>
        /// Displays an image in a window and displays the same image but bluerd in a new window
        /// </summary>
        public void One() 
        {
            Mat pic = new Mat();
            Mat gaussianBlur = new Mat();

            pic = CvInvoke.Imread("./img/StarryNight.jpg");
            CvInvoke.GaussianBlur(pic, gaussianBlur, new System.Drawing.Size(15, 15), 5.0);

            CvInvoke.Imshow("starry night", pic);
            CvInvoke.Imshow("blurry night", gaussianBlur);

            CvInvoke.WaitKey();
        }

        /// <summary>
        /// Resizes and image to a predetermined amount
        /// </summary>
        public void Two()
        {
            Mat pic = CvInvoke.Imread("./img/StarryNight.jpg");
            Mat resizedPic = new Mat();

            int height = pic.Rows;
            int width = pic.Cols;

            Console.WriteLine($"Starry Night is : {width} x {height}");

            CvInvoke.Resize(pic, resizedPic, new System.Drawing.Size(400, 500));

            CvInvoke.Imshow("Starry Night", pic);
            CvInvoke.Imshow("resized Night", resizedPic);

            CvInvoke.WaitKey();
        }

        /// <summary>
        /// Rotates an image around the center 45 degrees
        /// </summary>
        public void Three()
        {
            Mat pic = CvInvoke.Imread("./img/StarryNight.jpg");
            Mat rotatedPic = new Mat();
            double angleFortyFive = 45;
            int width = pic.Cols;
            int height = pic.Rows;
            
            System.Drawing.PointF center = new System.Drawing.PointF((width - 1) / 2.0f, (height - 1) / 2.0f);
            Mat rotationMatrix = new Mat();

            CvInvoke.GetRotationMatrix2D(center, angleFortyFive, 1.0, rotationMatrix);
            CvInvoke.WarpAffine(pic, rotatedPic, rotationMatrix, new System.Drawing.Size(width, height));

            CvInvoke.Imshow("Rotated Night", rotatedPic);

            CvInvoke.WaitKey();
        }

        /// <summary>
        /// Changing the color of pixels inside a range to new colors
        /// </summary>
        public void Four()
        {
            Mat pic = CvInvoke.Imread("./img/StarryNight.jpg");
            Image<Bgr, byte> convertPic = pic.ToImage<Bgr, byte>();

            int width = pic.Cols;
            int height = pic.Rows;

            var image = convertPic.InRange(new Bgr(75, 0, 0), new Bgr(255, 125, 125));

            for (int i = 0; i < image.Rows; i++)
            {
                for (int j = 0; j < image.Cols; j++)
                {
                    var num = image[i, j];

                    if (num.Intensity > 0)
                    {
                        convertPic[i, j] = new Bgr(convertPic[i, j].MCvScalar.V0 - 50, convertPic[i, j].MCvScalar.V1 + 100, convertPic[i, j].MCvScalar.V2 - 50);                        
                    }

                }
            }
            Mat changedPic = convertPic.Mat;

            CvInvoke.Imshow("Starry Night", pic);
            CvInvoke.Imshow("Color-Shifted Night", changedPic);

            CvInvoke.WaitKey();
        }

        /// <summary>
        /// Adds a sharpen filter to a picture based on an array
        /// </summary>
        public void Five()
        {
            Mat pic = CvInvoke.Imread("./img/StarryNight.jpg");

            /// This is a 3D matrix, and we will be using a process called convoluion
            /// Convolution is the application of a kernel to each individual pixal and it's surrounding pixels
            /// then you take that value and put it back in the pixel and some effect happens depending on the valuse
            /// in the kernel
            /// A new convoluted kernal can be looked up for the effect you want (this kernal is basic sharpen)
            float[,] kernalArray = new float[3, 3]
            {
                {  0, -1,  0},
                { -1,  5, -1},
                {  0, -1,  0}
            };

            ConvolutionKernelF kernal = new ConvolutionKernelF(kernalArray);

            Mat filteredPic = new Mat();
            pic.CopyTo(filteredPic);

            CvInvoke.Filter2D(pic, filteredPic, kernal, new System.Drawing.Point(0, 0));

            CvInvoke.Imshow("Convoluted Night", filteredPic);

            CvInvoke.WaitKey();
        }

        /// <summary>
        /// Uses the sobel edge detection to output just the edges in the image
        /// </summary>
        public void Six()
        {
            Mat pic = CvInvoke.Imread("./img/iPhone.jpg");
            
            Mat guassianBlur = new Mat();
            Mat sobelX = new Mat();
            Mat sobelY = new Mat();
            Mat sobelXY = new Mat();

            pic.CopyTo(sobelX);
            pic.CopyTo(sobelY);
            pic.CopyTo(sobelXY);

            CvInvoke.GaussianBlur(pic, guassianBlur, new System.Drawing.Size(3, 3), 5.0);

            CvInvoke.Sobel(guassianBlur, sobelX, Emgu.CV.CvEnum.DepthType.Default, 1, 0, 5);
            CvInvoke.Sobel(guassianBlur, sobelY, Emgu.CV.CvEnum.DepthType.Default, 0, 1, 5);
            CvInvoke.Sobel(guassianBlur, sobelXY, Emgu.CV.CvEnum.DepthType.Default, 1, 1, 5);

            CvInvoke.Imshow("sobelX", sobelX);
            CvInvoke.Imshow("sobelY", sobelY);
            CvInvoke.Imshow("sobelXY", sobelXY);

            CvInvoke.WaitKey();
        }

        /// <summary>
        /// Uses the canny edge detection to output the edges in an image (this method can be a little sharper depending on the image)
        /// </summary>
        public void Seven()
        {
            Mat pic = CvInvoke.Imread("./img/iPhone.jpg");

            Mat guassianBlur = new Mat();
            Mat cannyPic = new Mat();

            var averge = pic.ToImage<Gray, byte>().GetAverage();

            var lowerthreshold = Math.Max(0, (1.0 - 0.33) * averge.Intensity);
            var upperthreshold = Math.Max(255, (1.0 + 0.33) * averge.Intensity);

            CvInvoke.GaussianBlur(pic, guassianBlur, new System.Drawing.Size(3, 3), 5.0);
            CvInvoke.Canny(guassianBlur, cannyPic, lowerthreshold, upperthreshold, 3);

            CvInvoke.Imshow("Canny", cannyPic);
            
            CvInvoke.WaitKey();
        }

        /// <summary>
        /// Makes a threshold image to tell us where the contours are then defines those contours with green lines and fills the contourd parts in with blue
        /// </summary>
        public void Eight()
        {
            Mat pic = CvInvoke.Imread("./img/iPhone.jpg");
            Mat thresholdPic = new Mat();
            Mat hierarchy = new Mat();

            VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint();
            
            Image<Gray, byte> grayPic = pic.ToImage<Gray, byte>();

            CvInvoke.Threshold(grayPic, thresholdPic, 210, 255, Emgu.CV.CvEnum.ThresholdType.Binary);
            CvInvoke.FindContours(thresholdPic, contours, hierarchy, Emgu.CV.CvEnum.RetrType.Tree, Emgu.CV.CvEnum.ChainApproxMethod.ChainApproxNone);
            CvInvoke.DrawContours(pic, contours, -1, new MCvScalar(0, 255, 0), 2);

            CvInvoke.FillPoly(pic, contours, new MCvScalar(255, 0, 0));

            CvInvoke.Imshow("Threshold", thresholdPic);
            CvInvoke.Imshow("pic with contours", pic);

            CvInvoke.WaitKey();
        }

        /// <summary>
        /// Template matching, it lookes at a template image then compares that to an overall image and checks if there is anything 
        /// that matches our template then outputs where it found a match
        /// </summary>
        public void Nine()
        {
            Mat answeredPic = CvInvoke.Imread("./img/GraderPage-Answered.jpg");
            Mat aWasAnswered = CvInvoke.Imread("./img/A_abcd.jpg");
            Mat templateOuput = new Mat();

            CvInvoke.Resize(answeredPic, answeredPic, new System.Drawing.Size(0, 0), 0.7d, 0.7d);
            CvInvoke.Resize(aWasAnswered, aWasAnswered, new System.Drawing.Size(0, 0), 0.7d, 0.7d);

            CvInvoke.MatchTemplate(answeredPic, aWasAnswered, templateOuput, Emgu.CV.CvEnum.TemplateMatchingType.CcoeffNormed);

            double minVal = 0.0d;
            double maxVal = 0.0d;
            System.Drawing.Point minLoc = new System.Drawing.Point();
            System.Drawing.Point maxLoc = new System.Drawing.Point();

            CvInvoke.MinMaxLoc(templateOuput, ref minVal, ref maxVal, ref minLoc, ref maxLoc);
            CvInvoke.Threshold(templateOuput, templateOuput, 0.85, 1, Emgu.CV.CvEnum.ThresholdType.ToZero);

            var matches = templateOuput.ToImage<Gray, byte>();

            for (int i = 0; i < matches.Rows; i++)
            {
                for (int j = 0; j < matches.Cols; j++)
                {
                    if (matches[i, j].Intensity > .8)
                    {
                        System.Drawing.Point loc = new System.Drawing.Point(j, i);
                        System.Drawing.Rectangle box = new System.Drawing.Rectangle(loc, aWasAnswered.Size);

                        CvInvoke.Rectangle(answeredPic, box, new MCvScalar(0, 255, 0), 2);
                    }
                }
            }

            CvInvoke.Imshow("template detected", answeredPic);

            CvInvoke.WaitKey();
        }
    }
}