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feat: add cpp demo for wechatqrcode
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‎models/qrcode_wechatqrcode/CMakeLists.txt

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cmake_minimum_required(VERSION 3.24.0)
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project(opencv_zoo_qrcode_wechatqrcode)
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set(OPENCV_VERSION "4.10.0")
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set(OPENCV_INSTALLATION_PATH "" CACHE PATH "Where to look for OpenCV installation")
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# Find OpenCV
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find_package(OpenCV ${OPENCV_VERSION} REQUIRED HINTS ${OPENCV_INSTALLATION_PATH})
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add_executable(demo demo.cpp)
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target_link_libraries(demo ${OpenCV_LIBS})

‎models/qrcode_wechatqrcode/README.md

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## Demo
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### Python
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Run the following command to try the demo:
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```shell
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python demo.py --help
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```
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### C++
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Install latest OpenCV and CMake >= 3.24.0 to get started with:
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```shell
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# A typical and default installation path of OpenCV is /usr/local
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cmake -B build -D OPENCV_INSTALLATION_PATH=/path/to/opencv/installation .
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cmake --build build
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# detect on camera input
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./build/demo
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# detect on an image
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./build/demo -i=/path/to/image -v
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# get help messages
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./build/demo -h
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```
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### Example outputs
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![webcam demo](./example_outputs/wechat_qrcode_demo.gif)

‎models/qrcode_wechatqrcode/demo.cpp

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#include <iostream>
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#include <opencv2/opencv.hpp>
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#include <opencv2/wechat_qrcode.hpp>
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#include <string>
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#include <vector>
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// function to visualize QR code detection results
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cv::Mat visualize(cv::Mat image, const std::vector<std::string>& results,
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const std::vector<cv::Mat>& points,
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cv::Scalar points_color = cv::Scalar(0, 255, 0),
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cv::Scalar text_color = cv::Scalar(0, 255, 0),
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double fps = -1) {
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cv::Mat output = image.clone();
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if (fps >= 0) {
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cv::putText(output, "FPS: " + std::to_string(fps), cv::Point(0, 15),
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cv::FONT_HERSHEY_SIMPLEX, 0.5, text_color);
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}
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double fontScale = 0.5;
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int fontSize = 1;
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for (size_t i = 0; i < results.size(); ++i) {
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const auto& p = points[i];
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// iterate through the mat to access points
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for (int r = 0; r < p.rows; ++r) {
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cv::Point point(p.at<float>(r, 0), p.at<float>(r, 1));
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cv::circle(output, point, 10, points_color, -1);
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}
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// calculate QR code center
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int qrcode_center_x = (p.at<float>(0, 0) + p.at<float>(2, 0)) / 2;
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int qrcode_center_y = (p.at<float>(0, 1) + p.at<float>(2, 1)) / 2;
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// get text size
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int baseline = 0;
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cv::Size text_size =
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cv::getTextSize(results[i], cv::FONT_HERSHEY_DUPLEX, fontScale,
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fontSize, &baseline);
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// position text at the center of QR code
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cv::Point text_pos(qrcode_center_x - text_size.width / 2,
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qrcode_center_y + text_size.height / 2);
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// draw text
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cv::putText(output, results[i], text_pos, cv::FONT_HERSHEY_DUPLEX,
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fontScale, text_color, fontSize);
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}
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return output;
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}
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int main(int argc, char** argv) {
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// argument parsing
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cv::CommandLineParser parser(
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argc, argv,
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"{help h | | Show this help message.}"
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"{input i | | Set path to the input image. Omit for using default camera.}"
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"{detect_prototxt_path | detect_2021nov.prototxt | Set path to detect.prototxt.}"
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"{detect_model_path | detect_2021nov.caffemodel | Set path to detect.caffemodel.}"
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"{sr_model_path | sr_2021nov.caffemodel | Set path to sr.caffemodel.}"
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"{backend_target bt | 0 | Choose one of the backend-target pairs to run this demo.}"
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"{save s | false | Specify to save file with results (i.e. bounding box, confidence level). Invalid in case of camera input.}"
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"{vis v | false | Specify to open a new window to show results. Invalid in case of camera input.}");
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if (parser.has("help")) {
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parser.printMessage();
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return 0;
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}
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// backend-target pairs
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const std::vector<std::pair<int, int>> backend_target_pairs = {
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{cv::dnn::DNN_BACKEND_OPENCV, cv::dnn::DNN_TARGET_CPU},
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{cv::dnn::DNN_BACKEND_CUDA, cv::dnn::DNN_TARGET_CUDA},
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{cv::dnn::DNN_BACKEND_CUDA, cv::dnn::DNN_TARGET_CUDA_FP16},
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{cv::dnn::DNN_BACKEND_TIMVX, cv::dnn::DNN_TARGET_NPU},
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{cv::dnn::DNN_BACKEND_CANN, cv::dnn::DNN_TARGET_NPU}};
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// get backend-target from arguments
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int backend_target_index = parser.get<int>("backend_target");
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if (backend_target_index < 0 ||
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backend_target_index >= backend_target_pairs.size()) {
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std::cerr << "Invalid backend-target index" << std::endl;
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return -1;
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}
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// get paths
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std::string detect_prototxt = parser.get<std::string>("detect_prototxt_path");
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std::string detect_model = parser.get<std::string>("detect_model_path");
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std::string sr_prototxt = parser.get<std::string>("sr_prototxt_path");
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std::string sr_model = parser.get<std::string>("sr_model_path");
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// initialize wechatqrcode detector
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cv::Ptr<cv::wechat_qrcode::WeChatQRCode> detector =
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cv::makePtr<cv::wechat_qrcode::WeChatQRCode>(
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detect_prototxt, detect_model, sr_prototxt, sr_model);
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// check if input is specified
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std::string input_path = parser.get<std::string>("input");
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bool save_result = parser.get<bool>("save");
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bool visualize_result = parser.get<bool>("vis");
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if (!input_path.empty()) {
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// image processing
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cv::Mat image = cv::imread(input_path);
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if (image.empty()) {
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std::cerr << "Could not read the image" << std::endl;
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return -1;
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}
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std::vector<std::string> results;
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std::vector<cv::Mat> points;
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results = detector->detectAndDecode(image, points);
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for (const auto& result : results) {
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std::cout << result << std::endl;
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}
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// visualize results
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cv::Mat result_image = visualize(image, results, points);
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// save results if requested
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if (save_result) {
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cv::imwrite("result.jpg", result_image);
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std::cout << "Results saved to result.jpg" << std::endl;
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}
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// show visualization if requested
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if (visualize_result) {
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cv::imshow(input_path, result_image);
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cv::waitKey(0);
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}
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} else {
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// camera processing
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cv::VideoCapture cap(0);
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if (!cap.isOpened()) {
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std::cerr << "Error opening camera" << std::endl;
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return -1;
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}
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cv::Mat frame;
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cv::TickMeter tm;
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while (true) {
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cap >> frame;
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if (frame.empty()) {
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std::cout << "No frames grabbed" << std::endl;
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break;
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}
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std::vector<std::string> results;
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std::vector<cv::Mat> points;
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tm.start();
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results = detector->detectAndDecode(frame, points);
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tm.stop();
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double fps = tm.getFPS();
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// visualize results
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cv::Mat result_frame =
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visualize(frame, results, points, cv::Scalar(0, 255, 0),
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cv::Scalar(0, 255, 0), fps);
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cv::imshow("WeChatQRCode Demo", result_frame);
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tm.reset();
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if (cv::waitKey(1) >= 0) break;
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}
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}
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return 0;
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}

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