C# OpenCvSharp DNN 实现百度网盘AI大赛-表格检测第2名方案第三部分-表格方向识别

时间:2024-12-16 21:07:54

目录

说明

效果

模型

项目

​编辑

代码

参考

下载

其他


说明

百度网盘AI大赛-表格检测的第2名方案。

该算法包含表格边界框检测、表格分割和表格方向识别三个部分,首先,ppyoloe-plus-x 对边界框进行预测,并对置信度较高的表格边界框(box)进行裁剪。裁剪后的单个表格实例会送入到DBNet中进行语义分割,分割结果通过opencv轮廓处理获得表格关键点(point)。之后,我们根据DBNet计算的关键点在裁剪后的单个表格实例上绘制表格边界。最后,PP-LCNet结合表格边界先验和表格实例图像,对表格的方向进行预测,并根据之前定义的几何轮廓点与语义轮廓点的对应关系,将几何轮廓点映射为语义轮廓点。

本文使用C# OpenCvSharp DNN 实现百度网盘AI大赛-表格检测第2名方案第三部分-表格方向识别

效果

模型

Model Properties
-------------------------
---------------------------------------------------------------

Inputs
-------------------------
name:input
tensor:Float[-1, 3, 624, 624]
---------------------------------------------------------------

Outputs
-------------------------
name:linear_1.tmp_1
tensor:Float[-1, 4]
---------------------------------------------------------------

项目

代码

using OpenCvSharp;
using OpenCvSharp.Dnn;
using System;
using System.Drawing;
using System.Linq;
using System.Windows.Forms;

namespace OpenCvSharp_DNN_Demo
{
    public partial class frmMain : Form
    {
        public frmMain()
        {
            InitializeComponent();
        }

        string fileFilter = "*.*|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png";
        string image_path = "";
        string startupPath;
        string classer_path;

        DateTime dt1 = DateTime.Now;
        DateTime dt2 = DateTime.Now;
        string model_path;
        Mat image;

        Mat result_mat;
        Mat result_image;
        Mat result_mat_to_float;

        Net opencv_net;
        Mat BN_image;

        float[] result_array;

        int max_image_length;
        Mat max_image;
        Rect roi;

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

            pictureBox1.Image = null;
            pictureBox2.Image = null;
            textBox1.Text = "";

            image_path = ofd.FileName;
            pictureBox1.Image = new Bitmap(image_path);
            image = new Mat(image_path);
        }

        private void Form1_Load(object sender, EventArgs e)
        {
            string model_path = "model/paddle_cls.onnx";
            opencv_net = CvDnn.ReadNetFromOnnx(model_path);

            image_path = "test_img/1.jpg";
            pictureBox1.Image = new Bitmap(image_path);

        }

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

            if (image_path == "")
            {
                return;
            }
            textBox1.Text = "检测中,请稍等……";
            pictureBox2.Image = null;
            Application.DoEvents();

            Mat image = new Mat(image_path);

            //缩放图片
            max_image_length = image.Cols > image.Rows ? image.Cols : image.Rows;
            max_image = Mat.Zeros(new OpenCvSharp.Size(max_image_length, max_image_length), MatType.CV_8UC3);
            roi = new Rect(0, 0, image.Cols, image.Rows);
            image.CopyTo(new Mat(max_image, roi));

            //数据归一化处理
            BN_image = CvDnn.BlobFromImage(max_image, 1 / 255.0, new OpenCvSharp.Size(624, 624), new Scalar(0, 0, 0), true, false);

            //配置图片输入数据
            opencv_net.SetInput(BN_image);

            dt1 = DateTime.Now;
            //模型推理,读取推理结果
            result_mat = opencv_net.Forward();
            dt2 = DateTime.Now;

            //将推理结果转为float数据类型
            result_mat_to_float = new Mat(1, 4, MatType.CV_32F, result_mat.Data);

            //将数据读取到数组中
            result_mat_to_float.GetArray<float>(out result_array);

            float max = result_array.Max(); // 
            int maxIndex = Array.IndexOf(result_array, max); // 获取最大值的索引位置
            //语义左上角位于几何左上角,定义为0;
            //语义左上角位于几何右上角,定义为1;
            //语义左上角位于几何右下角,定义了2;
            //语义左上角位于几何左下角,定义为3。
            
            textBox1.Text = "推理耗时:" + (dt2 - dt1).TotalMilliseconds + "ms\r\n";
            string msg = "";
            if (maxIndex == 0) {
                msg = "语义左上角位于几何左上角";
            }
            else if (maxIndex == 1)
            {
                msg = "语义左上角位于几何右上角";
            }
            else if (maxIndex == 2)
            {
                msg = "语义左上角位于几何右下角";
            }
            else if (maxIndex == 3)
            {
                msg = "语义左上角位于几何左下角";
            }
            textBox1.Text += "\r\n" + msg;
        }

        private void pictureBox2_DoubleClick(object sender, EventArgs e)
        {
            Common.ShowNormalImg(pictureBox2.Image);
        }
        
        private void pictureBox1_DoubleClick(object sender, EventArgs e)
        {
            Common.ShowNormalImg(pictureBox1.Image);
        }
    }
}
 

using OpenCvSharp;
using OpenCvSharp.Dnn;
using System;
using System.Drawing;
using System.Linq;
using System.Windows.Forms;

namespace OpenCvSharp_DNN_Demo
{
    public partial class frmMain : Form
    {
        public frmMain()
        {
            InitializeComponent();
        }

        string fileFilter = "*.*|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png";
        string image_path = "";
        string startupPath;
        string classer_path;

        DateTime dt1 = DateTime.Now;
        DateTime dt2 = DateTime.Now;
        string model_path;
        Mat image;

        Mat result_mat;
        Mat result_image;
        Mat result_mat_to_float;

        Net opencv_net;
        Mat BN_image;

        float[] result_array;

        int max_image_length;
        Mat max_image;
        Rect roi;

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

            pictureBox1.Image = null;
            pictureBox2.Image = null;
            textBox1.Text = "";

            image_path = ofd.FileName;
            pictureBox1.Image = new Bitmap(image_path);
            image = new Mat(image_path);
        }

        private void Form1_Load(object sender, EventArgs e)
        {
            string model_path = "model/paddle_cls.onnx";
            opencv_net = CvDnn.ReadNetFromOnnx(model_path);

            image_path = "test_img/1.jpg";
            pictureBox1.Image = new Bitmap(image_path);

        }

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

            if (image_path == "")
            {
                return;
            }
            textBox1.Text = "检测中,请稍等……";
            pictureBox2.Image = null;
            Application.DoEvents();

            Mat image = new Mat(image_path);

            //缩放图片
            max_image_length = image.Cols > image.Rows ? image.Cols : image.Rows;
            max_image = Mat.Zeros(new OpenCvSharp.Size(max_image_length, max_image_length), MatType.CV_8UC3);
            roi = new Rect(0, 0, image.Cols, image.Rows);
            image.CopyTo(new Mat(max_image, roi));

            //数据归一化处理
            BN_image = CvDnn.BlobFromImage(max_image, 1 / 255.0, new OpenCvSharp.Size(624, 624), new Scalar(0, 0, 0), true, false);

            //配置图片输入数据
            opencv_net.SetInput(BN_image);

            dt1 = DateTime.Now;
            //模型推理,读取推理结果
            result_mat = opencv_net.Forward();
            dt2 = DateTime.Now;

            //将推理结果转为float数据类型
            result_mat_to_float = new Mat(1, 4, MatType.CV_32F, result_mat.Data);

            //将数据读取到数组中
            result_mat_to_float.GetArray<float>(out result_array);

            float max = result_array.Max(); // 
            int maxIndex = Array.IndexOf(result_array, max); // 获取最大值的索引位置
            //语义左上角位于几何左上角,定义为0;
            //语义左上角位于几何右上角,定义为1;
            //语义左上角位于几何右下角,定义了2;
            //语义左上角位于几何左下角,定义为3。
            
            textBox1.Text = "推理耗时:" + (dt2 - dt1).TotalMilliseconds + "ms\r\n";
            string msg = "";
            if (maxIndex == 0) {
                msg = "语义左上角位于几何左上角";
            }
            else if (maxIndex == 1)
            {
                msg = "语义左上角位于几何右上角";
            }
            else if (maxIndex == 2)
            {
                msg = "语义左上角位于几何右下角";
            }
            else if (maxIndex == 3)
            {
                msg = "语义左上角位于几何左下角";
            }
            textBox1.Text += "\r\n" + msg;
        }

        private void pictureBox2_DoubleClick(object sender, EventArgs e)
        {
            Common.ShowNormalImg(pictureBox2.Image);
        }
        
        private void pictureBox1_DoubleClick(object sender, EventArgs e)
        {
            Common.ShowNormalImg(pictureBox1.Image);
        }
    }
}

参考

https://github.com/hpc203/TableDetection

下载

源码下载

其他

C# OpenCvSharp DNN 第一部分-表格边界框检测-****博客

C# OnnxRuntime 第二部分-表格分割-****博客