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C# PaddleInference 文字检测（只检测不识别）_c# 全文错别字 检测

作者：Gausst松鼠会 | 2024-06-09 05:31:47

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c# 全文错别字 检测

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效果

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效果

项目

代码

using OpenCvSharp.Extensions;
using OpenCvSharp;
using Sdcb.PaddleInference.Native;
using Sdcb.PaddleInference;
using System;
using System.Collections.Generic;
using System.Data;
using System.Drawing;
using System.Linq;
using System.Text;
using System.Windows.Forms;
using System.Runtime.InteropServices;
using System.Globalization;

namespace PaddleInference_文字检测
{
    public partial class Form1 : Form
    {
        public Form1()
        {
            InitializeComponent();
        }

        Bitmap bmp;
        string fileFilter = "*.*|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png";
        string img = "";

        private void button1_Click(object sender, EventArgs e)
        {
            OpenFileDialog ofd = new OpenFileDialog();
            ofd.Filter = fileFilter;
            if (ofd.ShowDialog() != DialogResult.OK) return;

            pictureBox1.Image = null;

            img = ofd.FileName;
            bmp = new Bitmap(img);
            pictureBox1.Image = new Bitmap(img);
        }


        int MaxSize = 1536;
        float? BoxThreshold = 0.3f;
        float? BoxScoreThreahold = 0.7f;
        int? DilatedSize = 2;
        int MinSize = 3;
        float UnclipRatio = 2.0f;
        PaddlePredictor predictor;
        private unsafe void Form1_Load(object sender, EventArgs e)
        {
            IntPtr _ptr = PaddleNative.PD_ConfigCreate();

            Encoding PaddleEncoding = Environment.OSVersion.Platform == PlatformID.Win32NT ? Encoding.GetEncoding(CultureInfo.CurrentCulture.TextInfo.ANSICodePage) : Encoding.UTF8;

            //设置推理模型路径
            String programPath = Application.StartupPath + "\\ch_PP-OCRv3_det\\inference.pdmodel";
            String paramsPath = Application.StartupPath + "\\ch_PP-OCRv3_det\\inference.pdiparams";

            byte[] programBytes = PaddleEncoding.GetBytes(programPath);
            byte[] paramsBytes = PaddleEncoding.GetBytes(paramsPath);
            fixed (byte* programPtr = programBytes)
            fixed (byte* paramsPtr = paramsBytes)
            {
                PaddleNative.PD_ConfigSetModel(_ptr, (IntPtr)programPtr, (IntPtr)paramsPtr);
            }

            predictor = new PaddlePredictor(PaddleNative.PD_PredictorCreate(_ptr));
        }

        private void button2_Click(object sender, EventArgs e)
        {
            if (img == "")
            {
                return;
            }

            Mat src = Cv2.ImRead(img);

            Mat resized = MatResize(src, MaxSize);
            Mat padded = MatPadding32(resized);
            Mat normalized = Normalize(padded);
            OpenCvSharp.Size resizedSize = resized.Size();
            using (PaddleTensor input = predictor.GetInputTensor(predictor.InputNames[0]))
            {
                input.Shape = new[] { 1, 3, normalized.Rows, normalized.Cols };
                float[] setData = ExtractMat(normalized);
                input.SetData(setData);
            }

            if (!predictor.Run())
            {
                throw new Exception("PaddlePredictor(Detector) run failed.");
            }

            using (PaddleTensor output = predictor.GetOutputTensor(predictor.OutputNames[0]))
            {
                float[] data = output.GetData<float>();
                int[] shape = output.Shape;

                Mat pred = new Mat(shape[2], shape[3], MatType.CV_32FC1, data);
                Mat cbuf = new Mat();

                Mat roi = pred[0, resizedSize.Height, 0, resizedSize.Width];
                roi.ConvertTo(cbuf, MatType.CV_8UC1, 255);

                Mat dilated = new Mat();
                Mat binary = BoxThreshold != null ?
                   cbuf.Threshold((int)(BoxThreshold * 255), 255, ThresholdTypes.Binary) :
                   cbuf;

                if (DilatedSize != null)
                {
                    Mat ones = Cv2.GetStructuringElement(MorphShapes.Rect, new OpenCvSharp.Size(DilatedSize.Value, DilatedSize.Value));
                    Cv2.Dilate(binary, dilated, ones);
                    ones.Dispose();
                }
                else
                {
                    Cv2.CopyTo(binary, dilated);
                }

                OpenCvSharp.Point[][] contours = dilated.FindContoursAsArray(RetrievalModes.List, ContourApproximationModes.ApproxSimple);

                OpenCvSharp.Size size = src.Size();
                double scaleRate = 1.0 * src.Width / resizedSize.Width;

                RotatedRect[] rects = contours
                    .Where(x => BoxScoreThreahold == null || GetScore(x, pred) > BoxScoreThreahold)
                    .Select(x => Cv2.MinAreaRect(x))
                    .Where(x => x.Size.Width > MinSize && x.Size.Height > MinSize)
                    .Select(rect =>
                    {
                        float minEdge = Math.Min(rect.Size.Width, rect.Size.Height);
                        Size2f newSize = new Size2f(
                            (rect.Size.Width + UnclipRatio * minEdge) * scaleRate,
                            (rect.Size.Height + UnclipRatio * minEdge) * scaleRate);
                        RotatedRect largerRect = new RotatedRect(rect.Center * scaleRate, newSize, rect.Angle);
                        return largerRect;
                    })
                    .OrderBy(v => v.Center.Y)
                    .ThenBy(v => v.Center.X)
                    .ToArray();

                src.Dispose();
                binary.Dispose();
                roi.Dispose();
                cbuf.Dispose();
                pred.Dispose();
                dilated.Dispose();

                //绘图
                Mat src2 = Cv2.ImRead(img);
                for (int i = 0; i < rects.Length; i++)
                {
                    Scalar scalar = Scalar.RandomColor();
                    List<OpenCvSharp.Point> temp = new List<OpenCvSharp.Point>();
                    foreach (var item2 in rects[i].Points())
                    {
                        temp.Add(new OpenCvSharp.Point(item2.X, item2.Y));
                    }
                    List<List<OpenCvSharp.Point>> lltemp = new List<List<OpenCvSharp.Point>>();
                    lltemp.Add(temp);
                    Cv2.Polylines(src2, lltemp, true, scalar);
                }

                if (pictureBox1.Image!=null)
                {
                    pictureBox1.Image.Dispose();
                }

                pictureBox1.Image = BitmapConverter.ToBitmap(src2);
                src2.Dispose();

            }
        }

        private float GetScore(OpenCvSharp.Point[] contour, Mat pred)
        {
            int width = pred.Width;
            int height = pred.Height;
            int[] boxX = contour.Select(v => v.X).ToArray();
            int[] boxY = contour.Select(v => v.Y).ToArray();

            int xmin = Clamp(boxX.Min(), 0, width - 1);
            int xmax = Clamp(boxX.Max(), 0, width - 1);
            int ymin = Clamp(boxY.Min(), 0, height - 1);
            int ymax = Clamp(boxY.Max(), 0, height - 1);

            OpenCvSharp.Point[] rootPoints = contour
                .Select(v => new OpenCvSharp.Point(v.X - xmin, v.Y - ymin))
                .ToArray();
            Mat mask = new Mat(ymax - ymin + 1, xmax - xmin + 1, MatType.CV_8UC1, Scalar.Black);
            mask.FillPoly(new[] { rootPoints }, new Scalar(1));

            Mat croppedMat = pred[ymin, ymax + 1, xmin, xmax + 1];
            float score = (float)croppedMat.Mean(mask).Val0;
            return score;
        }

        public int Clamp(int val, int min, int max)
        {
            if (val < min)
            {
                return min;
            }
            else if (val > max)
            {
                return max;
            }
            return val;
        }

        float[] ExtractMat(Mat src)
        {
            int rows = src.Rows;
            int cols = src.Cols;
            float[] array = new float[rows * cols * 3];
            GCHandle gCHandle = default(GCHandle);
            try
            {
                gCHandle = GCHandle.Alloc(array, GCHandleType.Pinned);
                IntPtr intPtr = gCHandle.AddrOfPinnedObject();
                for (int i = 0; i < src.Channels(); i++)
                {
                    Mat dest = new Mat(rows, cols, MatType.CV_32FC1, intPtr + i * rows * cols * 4, 0L);
                    Cv2.ExtractChannel(src, dest, i);
                    dest.Dispose();
                }
                return array;
            }
            finally
            {
                gCHandle.Free();
            }
        }

        private Mat MatResize(Mat src, int? maxSize)
        {
            if (maxSize == null) return src.Clone();

            OpenCvSharp.Size size = src.Size();
            int longEdge = Math.Max(size.Width, size.Height);
            double scaleRate = 1.0 * maxSize.Value / longEdge;

            return scaleRate < 1.0 ?
                src.Resize(OpenCvSharp.Size.Zero, scaleRate, scaleRate) :
                src.Clone();
        }

        private Mat MatPadding32(Mat src)
        {
            OpenCvSharp.Size size = src.Size();
            OpenCvSharp.Size newSize = new OpenCvSharp.Size(
                32 * Math.Ceiling(1.0 * size.Width / 32),
                32 * Math.Ceiling(1.0 * size.Height / 32));

            return src.CopyMakeBorder(0, newSize.Height - size.Height, 0, newSize.Width - size.Width, BorderTypes.Constant, Scalar.Black);
        }

        private Mat Normalize(Mat src)
        {
            Mat normalized = new Mat();
            src.ConvertTo(normalized, MatType.CV_32FC3, 1.0 / 255);
            Mat[] bgr = normalized.Split();
            float[] scales = new[] { 1 / 0.229f, 1 / 0.224f, 1 / 0.225f };
            float[] means = new[] { 0.485f, 0.456f, 0.406f };
            for (int i = 0; i < bgr.Length; ++i)
            {
                bgr[i].ConvertTo(bgr[i], MatType.CV_32FC1, 1.0 * scales[i], (0.0 - means[i]) * scales[i]);
            }
            normalized.Dispose();
            Mat dest = new Mat();
            Cv2.Merge(bgr, dest);
            foreach (Mat channel in bgr)
            {
                channel.Dispose();
            }
            return dest;
        }

    }
}

  1. using OpenCvSharp.Extensions;
  2. using OpenCvSharp;
  3. using Sdcb.PaddleInference.Native;
  4. using Sdcb.PaddleInference;
  5. using System;
  6. using System.Collections.Generic;
  7. using System.Data;
  8. using System.Drawing;
  9. using System.Linq;
  10. using System.Text;
  11. using System.Windows.Forms;
  12. using System.Runtime.InteropServices;
  13. using System.Globalization;
  14.  
  15. namespace PaddleInference_文字检测
  16. {
  17.     public partial class Form1 : Form
  18.     {
  19.         public Form1()
  20.         {
  21.             InitializeComponent();
  22.         }
  23.  
  24.         Bitmap bmp;
  25.         string fileFilter = "*.*|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png";
  26.         string img = "";
  27.  
  28.         private void button1_Click(object sender, EventArgs e)
  29.         {
  30.             OpenFileDialog ofd = new OpenFileDialog();
  31.             ofd.Filter = fileFilter;
  32.             if (ofd.ShowDialog() != DialogResult.OK) return;
  33.  
  34.             pictureBox1.Image = null;
  35.  
  36.             img = ofd.FileName;
  37.             bmp = new Bitmap(img);
  38.             pictureBox1.Image = new Bitmap(img);
  39.         }
  40.  
  41.  
  42.         int MaxSize = 1536;
  43.         float? BoxThreshold = 0.3f;
  44.         float? BoxScoreThreahold = 0.7f;
  45.         int? DilatedSize = 2;
  46.         int MinSize = 3;
  47.         float UnclipRatio = 2.0f;
  48.         PaddlePredictor predictor;
  49.         private unsafe void Form1_Load(object sender, EventArgs e)
  50.         {
  51.             IntPtr _ptr = PaddleNative.PD_ConfigCreate();
  52.  
  53.             Encoding PaddleEncoding = Environment.OSVersion.Platform == PlatformID.Win32NT ? Encoding.GetEncoding(CultureInfo.CurrentCulture.TextInfo.ANSICodePage) : Encoding.UTF8;
  54.  
  55.             //设置推理模型路径
  56.             String programPath = Application.StartupPath + "\\ch_PP-OCRv3_det\\inference.pdmodel";
  57.             String paramsPath = Application.StartupPath + "\\ch_PP-OCRv3_det\\inference.pdiparams";
  58.  
  59.             byte[] programBytes = PaddleEncoding.GetBytes(programPath);
  60.             byte[] paramsBytes = PaddleEncoding.GetBytes(paramsPath);
  61.             fixed (byte* programPtr = programBytes)
  62.             fixed (byte* paramsPtr = paramsBytes)
  63.             {
  64.                 PaddleNative.PD_ConfigSetModel(_ptr, (IntPtr)programPtr, (IntPtr)paramsPtr);
  65.             }
  66.  
  67.             predictor = new PaddlePredictor(PaddleNative.PD_PredictorCreate(_ptr));
  68.         }
  69.  
  70.         private void button2_Click(object sender, EventArgs e)
  71.         {
  72.             if (img == "")
  73.             {
  74.                 return;
  75.             }
  76.  
  77.             Mat src = Cv2.ImRead(img);
  78.  
  79.             Mat resized = MatResize(src, MaxSize);
  80.             Mat padded = MatPadding32(resized);
  81.             Mat normalized = Normalize(padded);
  82.             OpenCvSharp.Size resizedSize = resized.Size();
  83.             using (PaddleTensor input = predictor.GetInputTensor(predictor.InputNames[0]))
  84.             {
  85.                 input.Shape = new[] { 1, 3, normalized.Rows, normalized.Cols };
  86.                 float[] setData = ExtractMat(normalized);
  87.                 input.SetData(setData);
  88.             }
  89.  
  90.             if (!predictor.Run())
  91.             {
  92.                 throw new Exception("PaddlePredictor(Detector) run failed.");
  93.             }
  94.  
  95.             using (PaddleTensor output = predictor.GetOutputTensor(predictor.OutputNames[0]))
  96.             {
  97.                 float[] data = output.GetData<float>();
  98.                 int[] shape = output.Shape;
  99.  
  100.                 Mat pred = new Mat(shape[2], shape[3], MatType.CV_32FC1, data);
  101.                 Mat cbuf = new Mat();
  102.  
  103.                 Mat roi = pred[0, resizedSize.Height, 0, resizedSize.Width];
  104.                 roi.ConvertTo(cbuf, MatType.CV_8UC1, 255);
  105.  
  106.                 Mat dilated = new Mat();
  107.                 Mat binary = BoxThreshold != null ?
  108.                    cbuf.Threshold((int)(BoxThreshold * 255), 255, ThresholdTypes.Binary) :
  109.                    cbuf;
  110.  
  111.                 if (DilatedSize != null)
  112.                 {
  113.                     Mat ones = Cv2.GetStructuringElement(MorphShapes.Rect, new OpenCvSharp.Size(DilatedSize.Value, DilatedSize.Value));
  114.                     Cv2.Dilate(binary, dilated, ones);
  115.                     ones.Dispose();
  116.                 }
  117.                 else
  118.                 {
  119.                     Cv2.CopyTo(binary, dilated);
  120.                 }
  121.  
  122.                 OpenCvSharp.Point[][] contours = dilated.FindContoursAsArray(RetrievalModes.List, ContourApproximationModes.ApproxSimple);
  123.  
  124.                 OpenCvSharp.Size size = src.Size();
  125.                 double scaleRate = 1.0 * src.Width / resizedSize.Width;
  126.  
  127.                 RotatedRect[] rects = contours
  128.                     .Where(x => BoxScoreThreahold == null || GetScore(x, pred) > BoxScoreThreahold)
  129.                     .Select(x => Cv2.MinAreaRect(x))
  130.                     .Where(x => x.Size.Width > MinSize && x.Size.Height > MinSize)
  131.                     .Select(rect =>
  132.                     {
  133.                         float minEdge = Math.Min(rect.Size.Width, rect.Size.Height);
  134.                         Size2f newSize = new Size2f(
  135.                             (rect.Size.Width + UnclipRatio * minEdge) * scaleRate,
  136.                             (rect.Size.Height + UnclipRatio * minEdge) * scaleRate);
  137.                         RotatedRect largerRect = new RotatedRect(rect.Center * scaleRate, newSize, rect.Angle);
  138.                         return largerRect;
  139.                     })
  140.                     .OrderBy(v => v.Center.Y)
  141.                     .ThenBy(v => v.Center.X)
  142.                     .ToArray();
  143.  
  144.                 src.Dispose();
  145.                 binary.Dispose();
  146.                 roi.Dispose();
  147.                 cbuf.Dispose();
  148.                 pred.Dispose();
  149.                 dilated.Dispose();
  150.  
  151.                 //绘图
  152.                 Mat src2 = Cv2.ImRead(img);
  153.                 for (int i = 0; i < rects.Length; i++)
  154.                 {
  155.                     Scalar scalar = Scalar.RandomColor();
  156.                     List<OpenCvSharp.Point> temp = new List<OpenCvSharp.Point>();
  157.                     foreach (var item2 in rects[i].Points())
  158.                     {
  159.                         temp.Add(new OpenCvSharp.Point(item2.X, item2.Y));
  160.                     }
  161.                     List<List<OpenCvSharp.Point>> lltemp = new List<List<OpenCvSharp.Point>>();
  162.                     lltemp.Add(temp);
  163.                     Cv2.Polylines(src2, lltemp, true, scalar);
  164.                 }
  165.  
  166.                 if (pictureBox1.Image!=null)
  167.                 {
  168.                     pictureBox1.Image.Dispose();
  169.                 }
  170.  
  171.                 pictureBox1.Image = BitmapConverter.ToBitmap(src2);
  172.                 src2.Dispose();
  173.  
  174.             }
  175.         }
  176.  
  177.         private float GetScore(OpenCvSharp.Point[] contour, Mat pred)
  178.         {
  179.             int width = pred.Width;
  180.             int height = pred.Height;
  181.             int[] boxX = contour.Select(v => v.X).ToArray();
  182.             int[] boxY = contour.Select(v => v.Y).ToArray();
  183.  
  184.             int xmin = Clamp(boxX.Min(), 0, width - 1);
  185.             int xmax = Clamp(boxX.Max(), 0, width - 1);
  186.             int ymin = Clamp(boxY.Min(), 0, height - 1);
  187.             int ymax = Clamp(boxY.Max(), 0, height - 1);
  188.  
  189.             OpenCvSharp.Point[] rootPoints = contour
  190.                 .Select(v => new OpenCvSharp.Point(v.X - xmin, v.Y - ymin))
  191.                 .ToArray();
  192.             Mat mask = new Mat(ymax - ymin + 1, xmax - xmin + 1, MatType.CV_8UC1, Scalar.Black);
  193.             mask.FillPoly(new[] { rootPoints }, new Scalar(1));
  194.  
  195.             Mat croppedMat = pred[ymin, ymax + 1, xmin, xmax + 1];
  196.             float score = (float)croppedMat.Mean(mask).Val0;
  197.             return score;
  198.         }
  199.  
  200.         public int Clamp(int val, int min, int max)
  201.         {
  202.             if (val < min)
  203.             {
  204.                 return min;
  205.             }
  206.             else if (val > max)
  207.             {
  208.                 return max;
  209.             }
  210.             return val;
  211.         }
  212.  
  213.         float[] ExtractMat(Mat src)
  214.         {
  215.             int rows = src.Rows;
  216.             int cols = src.Cols;
  217.             float[] array = new float[rows * cols * 3];
  218.             GCHandle gCHandle = default(GCHandle);
  219.             try
  220.             {
  221.                 gCHandle = GCHandle.Alloc(array, GCHandleType.Pinned);
  222.                 IntPtr intPtr = gCHandle.AddrOfPinnedObject();
  223.                 for (int i = 0; i < src.Channels(); i++)
  224.                 {
  225.                     Mat dest = new Mat(rows, cols, MatType.CV_32FC1, intPtr + i * rows * cols * 4, 0L);
  226.                     Cv2.ExtractChannel(src, dest, i);
  227.                     dest.Dispose();
  228.                 }
  229.                 return array;
  230.             }
  231.             finally
  232.             {
  233.                 gCHandle.Free();
  234.             }
  235.         }
  236.  
  237.         private Mat MatResize(Mat src, int? maxSize)
  238.         {
  239.             if (maxSize == null) return src.Clone();
  240.  
  241.             OpenCvSharp.Size size = src.Size();
  242.             int longEdge = Math.Max(size.Width, size.Height);
  243.             double scaleRate = 1.0 * maxSize.Value / longEdge;
  244.  
  245.             return scaleRate < 1.0 ?
  246.                 src.Resize(OpenCvSharp.Size.Zero, scaleRate, scaleRate) :
  247.                 src.Clone();
  248.         }
  249.  
  250.         private Mat MatPadding32(Mat src)
  251.         {
  252.             OpenCvSharp.Size size = src.Size();
  253.             OpenCvSharp.Size newSize = new OpenCvSharp.Size(
  254.                 32 * Math.Ceiling(1.0 * size.Width / 32),
  255.                 32 * Math.Ceiling(1.0 * size.Height / 32));
  256.  
  257.             return src.CopyMakeBorder(0, newSize.Height - size.Height, 0, newSize.Width - size.Width, BorderTypes.Constant, Scalar.Black);
  258.         }
  259.  
  260.         private Mat Normalize(Mat src)
  261.         {
  262.             Mat normalized = new Mat();
  263.             src.ConvertTo(normalized, MatType.CV_32FC3, 1.0 / 255);
  264.             Mat[] bgr = normalized.Split();
  265.             float[] scales = new[] { 1 / 0.229f, 1 / 0.224f, 1 / 0.225f };
  266.             float[] means = new[] { 0.485f, 0.456f, 0.406f };
  267.             for (int i = 0; i < bgr.Length; ++i)
  268.             {
  269.                 bgr[i].ConvertTo(bgr[i], MatType.CV_32FC1, 1.0 * scales[i], (0.0 - means[i]) * scales[i]);
  270.             }
  271.             normalized.Dispose();
  272.             Mat dest = new Mat();
  273.             Cv2.Merge(bgr, dest);
  274.             foreach (Mat channel in bgr)
  275.             {
  276.                 channel.Dispose();
  277.             }
  278.             return dest;
  279.         }
  280.  
  281.     }
  282. }

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