I mainly use the opencv C# library of Emgucv, but because the NMS in Emgucv can only calculate Rect but not RotateRect, it is OK to recognize horizontal text, but it will not work if it is slanted. The code is as follows: (If you write irregularly, do not spray... .. If you have any questions, please tell me and improve each other)
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.IO;
using System.Drawing;
using Emgu;
using Emgu.CV;
using Emgu.Util;
using Emgu.CV.Structure;
using Emgu.CV.Dnn;
using Emgu.CV.Util;
namespace emgucv_east
{
class Program
{
static void Main(string[] args)
{
Double confThreshold = 0.5;
Double nmsThreshold = 0.4;
int inpWidth = 320;
int inpHeight = 320;
String model = "frozen_east_text_detection.pb";
Net net = DnnInvoke.ReadNet(model);
CvInvoke.NamedWindow("EAST: An Efficient and Accurate Scene Text Detector",Emgu.CV.CvEnum.NamedWindowType.AutoSize);
VectorOfMat outs = new VectorOfMat();
string[] outNames = new string[2];
outNames[0] = "feature_fusion/Conv_7/Sigmoid";
outNames[1] = "feature_fusion/concat_3";
Mat frame, blob;
frame = CvInvoke.Imread("timg (2).jpg");
CvInvoke.Imshow("frame", frame);
if (frame.IsEmpty)
{
Console.WriteLine("no image");
}
else
{
blob = DnnInvoke.BlobFromImage(frame, 1, new System.Drawing.Size(inpWidth, inpHeight),new MCvScalar(123.68, 116.78, 103.94),true,false);
net.SetInput(blob);
net.Forward(outs, outNames);
Mat scores = outs[0];
Mat geometry = outs[1];
//List<RotatedRect> detections = new List<RotatedRect>();
VectorOfRect boxes = new VectorOfRect();
VectorOfFloat confidences= new VectorOfFloat();
Decode dct = new Decode();
dct.Decode_box(scores, geometry, confThreshold, boxes, confidences);
VectorOfInt indices = new VectorOfInt();
DnnInvoke.NMSBoxes(boxes,confidences,(float)confThreshold,(float)nmsThreshold,indices);
PointF ratio = new PointF((float)((float)frame.Cols/(float)inpWidth), (float)((float)frame.Rows/ (float)inpHeight));
for (int i = 0; i < indices.Size; i++)
{
Rectangle box = boxes[indices[i]];
var vertices_x = box.X * ratio.X;
var vertices_y = box.Y * ratio.Y;
var vertices_width = box.Width * ratio.X;
var vertices_height = box.Height * ratio.Y;
var p_x = vertices_x - 0.5 * vertices_width;
var p_y = vertices_y - 0.5 * vertices_height;
Rectangle box_in = new Rectangle(new Point((int)(p_x), (int)(p_y)),new Size((int)vertices_width,(int)vertices_height));
CvInvoke.Rectangle(frame, box_in, new MCvScalar(255,255,0),4);
}
CvInvoke.Imshow("result", frame);
}
CvInvoke.WaitKey();
}
//decode
}
public class Decode
{
public void Decode_box(Mat scores, Mat geometry, double scoreThresh, VectorOfRect detections, VectorOfFloat confidences)
{
if (detections.Size>0)
{
detections.Clear();
}
//CV_Assert(scores.dims == 4); CV_Assert(geometry.dims == 4); CV_Assert(scores.size[0] == 1);
//CV_Assert(geometry.size[0] == 1); CV_Assert(scores.size[1] == 1); CV_Assert(geometry.size[1] == 5);
//CV_Assert(scores.size[2] == geometry.size[2]); CV_Assert(scores.size[3] == geometry.size[3]);
CvException.Equals(scores.Dims, 4);
CvException.Equals(geometry.Dims, 4);
var s =scores.SizeOfDimension;
var sdata = scores.GetData();
//var x = sdata.GetValue(0,0,0,0);
var gdata = geometry.GetData();
//var y = sdata.GetValue(0, 0, 0, 0);
List<RotatedRect> t_detections = new List<RotatedRect>();
List<float> t_confidences = new List<float>();
List<Rectangle> r_detections = new List<Rectangle>();
for (int y = 0; y < s[2]; ++y)
{
for (int x = 0; x < s[3]; x++)
{
float score = (float)sdata.GetValue(0, 0, y, x);
if (score<scoreThresh)
{
continue;
}
float offsetX = x * 4.0f, offsetY = y * 4.0f;
float angle = (float)gdata.GetValue(0, 4, y, x);
float cosA = (float)Math.Cos(angle);
float sinA = (float)Math.Sin(angle);
float h = (float)gdata.GetValue(0, 0, y, x)+ (float)gdata.GetValue(0, 2, y, x);
float w = (float)gdata.GetValue(0, 1, y, x) + (float)gdata.GetValue(0, 3, y, x);
PointF offset = new PointF(offsetX + cosA * (float)gdata.GetValue(0, 1, y, x) + sinA * (float)gdata.GetValue(0, 2, y, x),
offsetY - sinA * (float)gdata.GetValue(0, 1, y, x) + cosA * (float)gdata.GetValue(0, 2, y, x));
PointF p1 = new PointF();
p1.X = -sinA * h + offset.X;
p1.Y = -cosA * h + offset.Y;
PointF p3 = new PointF();
p3.X = -cosA * w + offset.X;
p3.Y = sinA * w + offset.Y;
PointF center = new PointF();
center.X = (float)0.5*(p1.X+p3.X);
center.Y = (float)0.5 * (p1.Y + p3.Y);
SizeF size = new SizeF(w,h);
float box_angle = -angle * 180.0f / (float)Math.PI;
RotatedRect r = new RotatedRect(center,size,box_angle);
Point i_center = new Point((int)(center.X),(int)(center.Y));
Size i_size = new Size((int)w,(int)h);
Rectangle r_d = new Rectangle(i_center, i_size);
r_detections.Add(r_d);
t_detections.Add(r);
t_confidences.Add(score);
}
}
Rectangle[] k_detections = r_detections.ToArray();
detections.Push(k_detections);
float[] k_confidences = t_confidences.ToArray();
confidences.Push(k_confidences);
}
}
}
The idea is the same as the C++ version, but some data types are different. It is a little troublesome, and finally the recognition effect
NMS questions can only be written by yourself. . . .