add opencv code

DB_IC15.cpp

@@ -0,0 +1,45 @@
+
+# OpenCV >= 4.5
+
+#include <iostream>
+#include <fstream>
+
+#include <opencv2/imgproc.hpp>
+#include <opencv2/highgui.hpp>
+#include <opencv2/dnn.hpp>
+
+using namespace cv;
+using namespace cv::dnn;
+
+// Load model weights
+TextDetectionModel_DB model("./DB_IC15_resnet50.onnx");
+ 
+// Post-processing parameters
+float binThresh = 0.3;
+float polyThresh = 0.5;
+uint maxCandidates = 200;
+double unclipRatio = 2.0;
+model.setBinaryThreshold(binThresh)
+     .setPolygonThreshold(polyThresh)
+     .setMaxCandidates(maxCandidates)
+     .setUnclipRatio(unclipRatio)
+;
+ 
+// Normalization parameters
+double scale = 1.0 / 255.0;
+Scalar mean = Scalar(122.67891434, 116.66876762, 104.00698793);
+ 
+// The input shape
+Size inputSize = Size(736, 736);
+ 
+model.setInputParams(scale, inputSize, mean);
+
+
+std::vector<std::vector<Point>> detResults;
+model.detect(detResults);
+ 
+// Visualization
+polylines(frame, results, true, Scalar(0, 255, 0), 2);
+imshow("Text Detection", image);
+waitKey();
+

readme.txt

@@ -2,3 +2,19 @@
 see doc\lang\programming\pytorch\文本检测\DBNET   论文代码都有
 
 see 深入理解神经网络：从逻辑回归到CNN.md -> DBNet 可微分二值化
+
+see https://docs.opencv.org/4.x/d4/d43/tutorial_dnn_text_spotting.html
+
+    - DB_IC15_resnet50.onnx:
+    url: https://drive.google.com/uc?export=dowload&id=17_ABp79PlFt9yPCxSaarVc_DKTmrSGGf
+    sha: bef233c28947ef6ec8c663d20a2b326302421fa3
+    recommended parameter setting: -inputHeight=736, -inputWidth=1280;
+    description: This model is trained on ICDAR2015, so it can only detect English text instances.
+    
+    - DB_IC15_resnet18.onnx:
+    url: https://drive.google.com/uc?export=dowload&id=1vY_KsDZZZb_svd5RT6pjyI8BS1nPbBSX
+    sha: 19543ce09b2efd35f49705c235cc46d0e22df30b
+    recommended parameter setting: -inputHeight=736, -inputWidth=1280;
+    description: This model is trained on ICDAR2015, so it can only detect English text instances.
+
+