using System;
using System.Collections.Generic;
using System.IO;
using System.Text;
 
using OpenCvSharp;
using OpenCvSharp.Extensions;
using OpenCvSharp.Utilities;
 
namespace OpenCvTest
{
    class Program
    {
        static void Main(string[] args)
        {
            //以灰(hui)度方(fang)式讀入(ru)原文件
            string filename = "source.jpg";
            var src = IplImage.FromFile(filename, LoadMode.GrayScale);
 
            //轉換(huan)到合(he)適的大(da)小，以適應快速變(bian)換(huan)
            int width = Cv.GetOptimalDFTSize(src.Width);
            int height = Cv.GetOptimalDFTSize(src.Height);
            var padded = new IplImage(width, height, BitDepth.U8, 1);
            Cv.CopyMakeBorder(src, padded, new CvPoint(0, 0), BorderType.Constant, CvScalar.ScalarAll(0));
             
            //實(shi)部(bu)、虛部(bu)(單通道)
            var real = new IplImage(padded.Size, BitDepth.F32, 1);
            var imaginary = new IplImage(padded.Size, BitDepth.F32, 1);
            //合(he)并(雙通道(dao))
            var fourier = new IplImage(padded.Size, BitDepth.F32, 2);
             
            //圖(tu)像復(fu)制到實部(bu)，虛部(bu)清零(ling)
            Cv.ConvertScale(padded, real);
            Cv.Zero(imaginary);
             
            //合并、變(bian)換(huan)、再分(fen)解
            Cv.Merge(real, imaginary, null, null, fourier);
            Cv.DFT(fourier, fourier, DFTFlag.Forward);
            Cv.Split(fourier, real, imaginary, null, null);
             
            //計算sqrt(re^2+im^2)，再存回re
            Cv.Pow(real, real, 2.0);
            Cv.Pow(imaginary, imaginary, 2.0);
            Cv.Add(real, imaginary, real);
            Cv.Pow(real, real, 0.5);
             
            //計算log(1+re)，存回re
            Cv.AddS(real, CvScalar.ScalarAll(1), real);
            Cv.Log(real, real);
             
            //歸一化，落入0-255范圍
            Cv.Normalize(real, real, 0, 255, NormType.MinMax);
             
            //把低(di)頻移動到中心
            ShiftDFT(real);
             
            //二(er)值化(hua)，以150作(zuo)為分界點，經驗(yan)值，需要根據(ju)實際情況(kuang)調整
            Cv.Threshold(real, real, 150, 255, ThresholdType.Binary);
             
            //由于HoughLines2方法(fa)只接受8UC1格式的圖片，因此(ci)進行轉換
            var gray = new IplImage(real.Size, BitDepth.U8, 1);
            Cv.ConvertScale(real, gray);
             
            //找直(zhi)線，threshold參數取(qu)100，經驗值，需要(yao)根據實(shi)際情況(kuang)調整
            var storage = Cv.CreateMemStorage();
            var lines = Cv.HoughLines2(gray, storage, HoughLinesMethod.Standard, 1, Cv.PI / 180, 100);
             
            //找到符合條件的(de)那(nei)條斜線
            float angel = 0f;
            float piThresh = (float)Cv.PI / 90;
            float pi2 = (float)Cv.PI / 2;
            for (int i = 0; i < lines.Total; ++i)
            {
                //極坐(zuo)標下的點，X是極徑，Y是夾角，我們只關心夾角
                var p = lines.GetSeqElem<CvPoint2D32f>(i);
                float theta = p.Value.Y;
                 
                if (Math.Abs(theta) >= piThresh && Math.Abs(theta - pi2) >= piThresh)
                {
                    angel = theta;
                    break;
                }
            }
            angel = angel < pi2 ? angel : (angel - (float)Cv.PI);
            Cv.ReleaseMemStorage(storage);
             
            //轉換角度
            if (angel != pi2)
            {
                float angelT = (float)(src.Height * Math.Tan(angel) / src.Width);
                angel = (float)Math.Atan(angelT);
            }
            float angelD = angel * 180 / (float)Cv.PI;
            Console.WriteLine("angtlD = {0}", angelD);
 
            //旋轉
            var center = new CvPoint2D32f(src.Width / 2.0, src.Height / 2.0);
            var rotMat = Cv.GetRotationMatrix2D(center, angelD, 1.0);
            var dst = new IplImage(src.Size, BitDepth.U8, 1);
            Cv.WarpAffine(src, dst, rotMat, Interpolation.Cubic | Interpolation.FillOutliers, CvScalar.ScalarAll(255));
             
            //顯示
            using (var window = new CvWindow("Image"))
            {
                window.Image = src;
                using (var win2 = new CvWindow("Dest"))
                {
                    win2.Image = dst;
                    Cv.WaitKey();
                }
            }
        }
         
        /// <summary>
        /// 將低頻(pin)部分移動到圖像(xiang)中心
        /// </summary>
        /// <param name="image"></param>
        /// <remarks>
        ///  0 | 3         2 | 1
        /// -------  ===> -------
        ///  1 | 2         3 | 0
        /// </remarks>
        private static void ShiftDFT(IplImage image)
        {
            int row = image.Height;
            int col = image.Width;
            int cy = row / 2;
            int cx = col / 2;
             
            var q0 = image.Clone(new CvRect(0, 0, cx, cy));//左上
            var q1 = image.Clone(new CvRect(0, cy, cx, cy));//左下
            var q2 = image.Clone(new CvRect(cx, cy, cx, cy));//右下
            var q3 = image.Clone(new CvRect(cx, 0, cx, cy));//右上
             
            Cv.SetImageROI(image, new CvRect(0, 0, cx, cy));
            q2.Copy(image);
            Cv.ResetImageROI(image);
             
            Cv.SetImageROI(image, new CvRect(0, cy, cx, cy));
            q3.Copy(image);
            Cv.ResetImageROI(image);
             
            Cv.SetImageROI(image, new CvRect(cx, cy, cx, cy));
            q0.Copy(image);
            Cv.ResetImageROI(image);
             
            Cv.SetImageROI(image, new CvRect(cx, 0, cx, cy));
            q1.Copy(image);
            Cv.ResetImageROI(image);
        }
    }
}