vendor: OpenCV 5.0.0 snapshot at 755e50675d97db9b7d449d8bd6b09888646f6c6e

2026-08-22 00:11:13 +08:00
commit 12022378a3
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+#include <opencv2/text.hpp>
+#include <opencv2/highgui.hpp>
+#include <opencv2/imgproc.hpp>
+#include <opencv2/dnn.hpp>
+
+#include  <iostream>
+#include  <fstream>
+
+using namespace cv;
+using namespace std;
+
+namespace
+{
+void printHelpStr(const string& progFname)
+{
+    cout << "   Demo of text recognition CNN for text detection." << endl
+         << "   Max Jaderberg et al.: Reading Text in the Wild with Convolutional Neural Networks, IJCV 2015"<<endl<<endl
+         << "   Usage: " << progFname << " <output_file> <input_image>" << endl
+         << "   Caffe Model files (textbox.prototxt, TextBoxes_icdar13.caffemodel)"<<endl
+         << "     must be in the current directory. See the documentation of text::TextDetectorCNN class to get download links." << endl
+         << "   Obtaining text recognition Caffe Model files in linux shell:" << endl
+         << "   wget http://nicolaou.homouniversalis.org/assets/vgg_text/dictnet_vgg.caffemodel" << endl
+         << "   wget http://nicolaou.homouniversalis.org/assets/vgg_text/dictnet_vgg_deploy.prototxt" << endl
+         << "   wget http://nicolaou.homouniversalis.org/assets/vgg_text/dictnet_vgg_labels.txt" <<endl << endl;
+}
+
+bool fileExists (const string& filename)
+{
+    ifstream f(filename.c_str());
+    return f.good();
+}
+
+void textbox_draw(Mat src, std::vector<Rect>& groups, std::vector<float>& probs, std::vector<int>& indexes)
+{
+    for (size_t i = 0; i < indexes.size(); i++)
+    {
+        if (src.type() == CV_8UC3)
+        {
+            Rect currrentBox = groups[indexes[i]];
+            rectangle(src, currrentBox, Scalar( 0, 255, 255 ), 2, LINE_AA);
+            String label = format("%.2f", probs[indexes[i]]);
+            std::cout << "text box: " << currrentBox << " confidence: " << probs[indexes[i]] << "\n";
+
+            int baseLine = 0;
+            Size labelSize = getTextSize(label, FONT_HERSHEY_PLAIN, 1, 1, &baseLine);
+            int yLeftBottom = std::max(currrentBox.y, labelSize.height);
+            rectangle(src, Point(currrentBox.x, yLeftBottom - labelSize.height),
+                      Point(currrentBox.x + labelSize.width, yLeftBottom + baseLine), Scalar( 255, 255, 255 ), FILLED);
+
+            putText(src, label, Point(currrentBox.x, yLeftBottom), FONT_HERSHEY_PLAIN, 1, Scalar( 0,0,0 ), 1, LINE_AA);
+        }
+        else
+            rectangle(src, groups[i], Scalar( 255 ), 3, 8 );
+    }
+}
+
+}
+
+int main(int argc, const char * argv[])
+{
+    if (argc < 2)
+    {
+        printHelpStr(argv[0]);
+        cout << "Insufiecient parameters. Aborting!" << endl;
+        exit(1);
+    }
+
+    const string modelArch = "textbox.prototxt";
+    const string moddelWeights = "TextBoxes_icdar13.caffemodel";
+
+    if (!fileExists(modelArch) || !fileExists(moddelWeights))
+    {
+        printHelpStr(argv[0]);
+        cout << "Model files not found in the current directory. Aborting!" << endl;
+        exit(1);
+    }
+
+    Mat image = imread(String(argv[1]), IMREAD_COLOR);
+
+    cout << "Starting Text Box Demo" << endl;
+    Ptr<text::TextDetectorCNN> textSpotter =
+            text::TextDetectorCNN::create(modelArch, moddelWeights);
+
+    vector<Rect> bbox;
+    vector<float> outProbabillities;
+    textSpotter->detect(image, bbox, outProbabillities);
+    std::vector<int> indexes;
+    cv::dnn::NMSBoxes(bbox, outProbabillities, 0.4f, 0.5f, indexes);
+
+    Mat image_copy = image.clone();
+    textbox_draw(image_copy, bbox, outProbabillities, indexes);
+    imshow("Text detection", image_copy);
+    image_copy = image.clone();
+
+    Ptr<text::OCRHolisticWordRecognizer> wordSpotter =
+            text::OCRHolisticWordRecognizer::create("dictnet_vgg_deploy.prototxt", "dictnet_vgg.caffemodel", "dictnet_vgg_labels.txt");
+
+    for(size_t i = 0; i < indexes.size(); i++)
+    {
+        Mat wordImg;
+        cvtColor(image(bbox[indexes[i]]), wordImg, COLOR_BGR2GRAY);
+        string word;
+        vector<float> confs;
+        wordSpotter->run(wordImg, word, NULL, NULL, &confs);
+
+        Rect currrentBox = bbox[indexes[i]];
+        rectangle(image_copy, currrentBox, Scalar( 0, 255, 255 ), 2, LINE_AA);
+
+        int baseLine = 0;
+        Size labelSize = getTextSize(word, FONT_HERSHEY_PLAIN, 1, 1, &baseLine);
+        int yLeftBottom = std::max(currrentBox.y, labelSize.height);
+        rectangle(image_copy, Point(currrentBox.x, yLeftBottom - labelSize.height),
+                  Point(currrentBox.x + labelSize.width, yLeftBottom + baseLine), Scalar( 255, 255, 255 ), FILLED);
+
+        putText(image_copy, word, Point(currrentBox.x, yLeftBottom), FONT_HERSHEY_PLAIN, 1, Scalar( 0,0,0 ), 1, LINE_AA);
+
+    }
+    imshow("Text recognition", image_copy);
+    cout << "Recognition finished. Press any key to exit.\n";
+    waitKey();
+    return 0;
+}