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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;
}
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