diff --git a/deploy/cpp_infer/include/ocr_det.h b/deploy/cpp_infer/include/ocr_det.h index 657ab25d8854ec54c27d71485fe9eeddc65013c3..6e4086fbaa6945b9f685e6844b7e701283de2dae 100644 --- a/deploy/cpp_infer/include/ocr_det.h +++ b/deploy/cpp_infer/include/ocr_det.h @@ -46,8 +46,7 @@ public: const double &det_db_box_thresh, const double &det_db_unclip_ratio, const bool &use_polygon_score, const bool &use_dilation, - const bool &visualize, const bool &use_tensorrt, - const std::string &precision) { + const bool &use_tensorrt, const std::string &precision) { this->use_gpu_ = use_gpu; this->gpu_id_ = gpu_id; this->gpu_mem_ = gpu_mem; @@ -62,7 +61,6 @@ public: this->use_polygon_score_ = use_polygon_score; this->use_dilation_ = use_dilation; - this->visualize_ = visualize; this->use_tensorrt_ = use_tensorrt; this->precision_ = precision; diff --git a/deploy/cpp_infer/include/ocr_rec.h b/deploy/cpp_infer/include/ocr_rec.h index ff80ba5299014885fc4c900fb87b5dcc6042744a..4052553d967fb365c3fb895c9d5b8145935fd45d 100644 --- a/deploy/cpp_infer/include/ocr_rec.h +++ b/deploy/cpp_infer/include/ocr_rec.h @@ -44,7 +44,8 @@ public: const int &gpu_id, const int &gpu_mem, const int &cpu_math_library_num_threads, const bool &use_mkldnn, const string &label_path, - const bool &use_tensorrt, const std::string &precision, + const bool &use_tensorrt, + const std::string &precision, const int &rec_batch_num) { this->use_gpu_ = use_gpu; this->gpu_id_ = gpu_id; @@ -66,7 +67,8 @@ public: // Load Paddle inference model void LoadModel(const std::string &model_dir); - void Run(std::vector img_list, std::vector *times); + void Run(std::vector img_list, std::vector &rec_texts, + std::vector &rec_text_scores, std::vector *times); private: std::shared_ptr predictor_; @@ -85,7 +87,7 @@ private: bool use_tensorrt_ = false; std::string precision_ = "fp32"; int rec_batch_num_ = 6; - + // pre-process CrnnResizeImg resize_op_; Normalize normalize_op_; diff --git a/deploy/cpp_infer/include/utility.h b/deploy/cpp_infer/include/utility.h index 5797559f7550da6bb38b014c46c1492124a9e065..f0dddacdac31e979a96648433662c76ccf972ad2 100644 --- a/deploy/cpp_infer/include/utility.h +++ b/deploy/cpp_infer/include/utility.h @@ -38,7 +38,8 @@ public: static void VisualizeBboxes(const cv::Mat &srcimg, - const std::vector>> &boxes); + const std::vector>> &boxes, + const std::string &save_path); template inline static size_t argmax(ForwardIterator first, ForwardIterator last) { @@ -47,12 +48,13 @@ public: static void GetAllFiles(const char *dir_name, std::vector &all_inputs); - + static cv::Mat GetRotateCropImage(const cv::Mat &srcimage, - std::vector> box); - - static std::vector argsort(const std::vector& array); + std::vector> box); + + static std::vector argsort(const std::vector &array); + static std::string basename(const std::string &filename); }; } // namespace PaddleOCR \ No newline at end of file diff --git a/deploy/cpp_infer/readme.md b/deploy/cpp_infer/readme.md index 8ca0e4a8c6c0eb7d09312645b70291d7e8c8016e..e7104881027b111de6821af8244ea2a6092fc14b 100644 --- a/deploy/cpp_infer/readme.md +++ b/deploy/cpp_infer/readme.md @@ -30,7 +30,7 @@ PaddleOCR模型部署。 ### 1.0 运行准备 - Linux环境，推荐使用docker。 -- Windows环境，目前支持基于`Visual Studio 2019 Community`进行编译。 +- Windows环境。 * 该文档主要介绍基于Linux环境的PaddleOCR C++预测流程，如果需要在Windows下基于预测库进行C++预测，具体编译方法请参考[Windows下编译教程](./docs/windows_vs2019_build.md) @@ -256,6 +256,7 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir |gpu_mem|int|4000|申请的GPU内存| |cpu_math_library_num_threads|int|10|CPU预测时的线程数，在机器核数充足的情况下，该值越大，预测速度越快| |enable_mkldnn|bool|true|是否使用mkldnn库| +|output|str|./output|可视化结果保存的路径| - 检测模型相关 @@ -267,7 +268,7 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir |det_db_box_thresh|float|0.5|DB后处理过滤box的阈值，如果检测存在漏框情况，可酌情减小| |det_db_unclip_ratio|float|1.6|表示文本框的紧致程度，越小则文本框更靠近文本| |use_polygon_score|bool|false|是否使用多边形框计算bbox score，false表示使用矩形框计算。矩形框计算速度更快，多边形框对弯曲文本区域计算更准确。| -|visualize|bool|true|是否对结果进行可视化，为1时，会在当前文件夹下保存文件名为`ocr_vis.png`的预测结果。| +|visualize|bool|true|是否对结果进行可视化，为1时，预测结果会保存在`output`字段指定的文件夹下和输入图像同名的图像上。| - 方向分类器相关 diff --git a/deploy/cpp_infer/readme_en.md b/deploy/cpp_infer/readme_en.md index 55160ede6bdd2f387124021f9ff25cdfb6b5a23a..61d65095394a9f5b7323bf8eb7324cd1e91b1346 100644 --- a/deploy/cpp_infer/readme_en.md +++ b/deploy/cpp_infer/readme_en.md @@ -26,6 +26,7 @@ This section will introduce how to configure the C++ environment and deploy Padd ### Environment - Linux, docker is recommended. +- Windows. ### 1.1 Compile OpenCV @@ -248,6 +249,7 @@ More parameters are as follows, |gpu_mem|int|4000|GPU memory requested| |cpu_math_library_num_threads|int|10|Number of threads when using CPU inference. When machine cores is enough, the large the value, the faster the inference speed| |enable_mkldnn|bool|true|Whether to use mkdlnn library| +|output|str|./output|Path where visualization results are saved| - Detection related parameters @@ -259,7 +261,7 @@ More parameters are as follows, |det_db_box_thresh|float|0.5|DB post-processing filter box threshold, if there is a missing box detected, it can be reduced as appropriate| |det_db_unclip_ratio|float|1.6|Indicates the compactness of the text box, the smaller the value, the closer the text box to the text| |use_polygon_score|bool|false|Whether to use polygon box to calculate bbox score, false means to use rectangle box to calculate. Use rectangular box to calculate faster, and polygonal box more accurate for curved text area.| -|visualize|bool|true|Whether to visualize the results，when it is set as true, The prediction result will be save in the image file `./ocr_vis.png`.| +|visualize|bool|true|Whether to visualize the results，when it is set as true, the prediction results will be saved in the folder specified by the `output` field on an image with the same name as the input image.| - Classifier related parameters diff --git a/deploy/cpp_infer/src/main.cpp b/deploy/cpp_infer/src/main.cpp index 31d0685f543a1441eab8b9d2595d008ff65763f8..b7b0b2486b394f4b61ef617984f2ca797b2033b3 100644 --- a/deploy/cpp_infer/src/main.cpp +++ b/deploy/cpp_infer/src/main.cpp @@ -12,7 +12,6 @@ // See the License for the specific language governing permissions and // limitations under the License. -#include "glog/logging.h" #include "omp.h" #include "opencv2/core.hpp" #include "opencv2/imgcodecs.hpp" @@ -21,13 +20,13 @@ #include #include #include +#include #include #include #include #include -#include #include #include #include @@ -45,7 +44,7 @@ DEFINE_bool(enable_mkldnn, false, "Whether use mkldnn with CPU."); DEFINE_bool(use_tensorrt, false, "Whether use tensorrt."); DEFINE_string(precision, "fp32", "Precision be one of fp32/fp16/int8"); DEFINE_bool(benchmark, false, "Whether use benchmark."); -DEFINE_string(save_log_path, "./log_output/", "Save benchmark log path."); +DEFINE_string(output, "./output/", "Save benchmark log path."); // detection related DEFINE_string(image_dir, "", "Dir of input image."); DEFINE_string(det_model_dir, "", "Path of det inference model."); @@ -86,11 +85,17 @@ int main_det(std::vector cv_all_img_names) { FLAGS_gpu_mem, FLAGS_cpu_threads, FLAGS_enable_mkldnn, FLAGS_max_side_len, FLAGS_det_db_thresh, FLAGS_det_db_box_thresh, FLAGS_det_db_unclip_ratio, - FLAGS_use_polygon_score, FLAGS_use_dilation, FLAGS_visualize, + FLAGS_use_polygon_score, FLAGS_use_dilation, FLAGS_use_tensorrt, FLAGS_precision); + if (!PathExists(FLAGS_output)) { + mkdir(FLAGS_output.c_str(), 0777); + } + for (int i = 0; i < cv_all_img_names.size(); ++i) { - // LOG(INFO) << "The predict img: " << cv_all_img_names[i]; + if (!FLAGS_benchmark) { + cout << "The predict img: " << cv_all_img_names[i] << endl; + } cv::Mat srcimg = cv::imread(cv_all_img_names[i], cv::IMREAD_COLOR); if (!srcimg.data) { @@ -102,7 +107,11 @@ int main_det(std::vector cv_all_img_names) { std::vector det_times; det.Run(srcimg, boxes, &det_times); - + //// visualization + if (FLAGS_visualize) { + std::string file_name = Utility::basename(cv_all_img_names[i]); + Utility::VisualizeBboxes(srcimg, boxes, FLAGS_output + "/" + file_name); + } time_info[0] += det_times[0]; time_info[1] += det_times[1]; time_info[2] += det_times[2]; @@ -142,8 +151,6 @@ int main_rec(std::vector cv_all_img_names) { std::vector img_list; for (int i = 0; i < cv_all_img_names.size(); ++i) { - LOG(INFO) << "The predict img: " << cv_all_img_names[i]; - cv::Mat srcimg = cv::imread(cv_all_img_names[i], cv::IMREAD_COLOR); if (!srcimg.data) { std::cerr << "[ERROR] image read failed! image path: " @@ -152,8 +159,15 @@ int main_rec(std::vector cv_all_img_names) { } img_list.push_back(srcimg); } + std::vector rec_texts(img_list.size(), ""); + std::vector rec_text_scores(img_list.size(), 0); std::vector rec_times; - rec.Run(img_list, &rec_times); + rec.Run(img_list, rec_texts, rec_text_scores, &rec_times); + // output rec results + for (int i = 0; i < rec_texts.size(); i++) { + cout << "The predict img: " << cv_all_img_names[i] << "\t" << rec_texts[i] + << "\t" << rec_text_scores[i] << endl; + } time_info[0] += rec_times[0]; time_info[1] += rec_times[1]; time_info[2] += rec_times[2]; @@ -172,11 +186,15 @@ int main_system(std::vector cv_all_img_names) { std::vector time_info_det = {0, 0, 0}; std::vector time_info_rec = {0, 0, 0}; + if (!PathExists(FLAGS_output)) { + mkdir(FLAGS_output.c_str(), 0777); + } + DBDetector det(FLAGS_det_model_dir, FLAGS_use_gpu, FLAGS_gpu_id, FLAGS_gpu_mem, FLAGS_cpu_threads, FLAGS_enable_mkldnn, FLAGS_max_side_len, FLAGS_det_db_thresh, FLAGS_det_db_box_thresh, FLAGS_det_db_unclip_ratio, - FLAGS_use_polygon_score, FLAGS_use_dilation, FLAGS_visualize, + FLAGS_use_polygon_score, FLAGS_use_dilation, FLAGS_use_tensorrt, FLAGS_precision); Classifier *cls = nullptr; @@ -197,7 +215,7 @@ int main_system(std::vector cv_all_img_names) { FLAGS_rec_batch_num); for (int i = 0; i < cv_all_img_names.size(); ++i) { - LOG(INFO) << "The predict img: " << cv_all_img_names[i]; + cout << "The predict img: " << cv_all_img_names[i] << endl; cv::Mat srcimg = cv::imread(cv_all_img_names[i], cv::IMREAD_COLOR); if (!srcimg.data) { @@ -205,15 +223,21 @@ int main_system(std::vector cv_all_img_names) { << cv_all_img_names[i] << endl; exit(1); } +#det std::vector>> boxes; std::vector det_times; std::vector rec_times; det.Run(srcimg, boxes, &det_times); + if (FLAGS_visualize) { + std::string file_name = Utility::basename(cv_all_img_names[i]); + Utility::VisualizeBboxes(srcimg, boxes, FLAGS_output + "/" + file_name); + } time_info_det[0] += det_times[0]; time_info_det[1] += det_times[1]; time_info_det[2] += det_times[2]; +#rec std::vector img_list; for (int j = 0; j < boxes.size(); j++) { cv::Mat crop_img; @@ -223,8 +247,14 @@ int main_system(std::vector cv_all_img_names) { } img_list.push_back(crop_img); } - - rec.Run(img_list, &rec_times); + std::vector rec_texts(img_list.size(), ""); + std::vector rec_text_scores(img_list.size(), 0); + rec.Run(img_list, rec_texts, rec_text_scores, &rec_times); + // output rec results + for (int i = 0; i < rec_texts.size(); i++) { + std::cout << i << "\t" << rec_texts[i] << "\t" << rec_text_scores[i] + << std::endl; + } time_info_rec[0] += rec_times[0]; time_info_rec[1] += rec_times[1]; time_info_rec[2] += rec_times[2]; diff --git a/deploy/cpp_infer/src/ocr_det.cpp b/deploy/cpp_infer/src/ocr_det.cpp index ad78999449d94dcaf2e336087de5c6837f3b233c..d72dc40cddb0845c370f5ad4bb9b6e2f6fe0bf2f 100644 --- a/deploy/cpp_infer/src/ocr_det.cpp +++ b/deploy/cpp_infer/src/ocr_det.cpp @@ -175,11 +175,6 @@ void DBDetector::Run(cv::Mat &img, std::chrono::duration postprocess_diff = postprocess_end - postprocess_start; times->push_back(double(postprocess_diff.count() * 1000)); - - //// visualization - if (this->visualize_) { - Utility::VisualizeBboxes(srcimg, boxes); - } } } // namespace PaddleOCR diff --git a/deploy/cpp_infer/src/ocr_rec.cpp b/deploy/cpp_infer/src/ocr_rec.cpp index 25224f88acecd33f5efaa34a9dfc71639663d53f..4c94e8f3fc966d2a4de8c7aad0e5ef4d4b69c804 100644 --- a/deploy/cpp_infer/src/ocr_rec.cpp +++ b/deploy/cpp_infer/src/ocr_rec.cpp @@ -17,6 +17,8 @@ namespace PaddleOCR { void CRNNRecognizer::Run(std::vector img_list, + std::vector &rec_texts, + std::vector &rec_text_scores, std::vector *times) { std::chrono::duration preprocess_diff = std::chrono::steady_clock::now() - std::chrono::steady_clock::now(); @@ -86,7 +88,7 @@ void CRNNRecognizer::Run(std::vector img_list, // ctc decode auto postprocess_start = std::chrono::steady_clock::now(); for (int m = 0; m < predict_shape[0]; m++) { - std::vector str_res; + std::string str_res; int argmax_idx; int last_index = 0; float score = 0.f; @@ -104,17 +106,16 @@ void CRNNRecognizer::Run(std::vector img_list, if (argmax_idx > 0 && (!(n > 0 && argmax_idx == last_index))) { score += max_value; count += 1; - str_res.push_back(label_list_[argmax_idx]); + str_res += label_list_[argmax_idx]; } last_index = argmax_idx; } score /= count; - if (isnan(score)) + if (isnan(score)) { continue; - for (int i = 0; i < str_res.size(); i++) { - std::cout << str_res[i]; } - std::cout << "\tscore: " << score << std::endl; + rec_texts[indices[beg_img_no + m]] = str_res; + rec_text_scores[indices[beg_img_no + m]] = score; } auto postprocess_end = std::chrono::steady_clock::now(); postprocess_diff += postprocess_end - postprocess_start; diff --git a/deploy/cpp_infer/src/utility.cpp b/deploy/cpp_infer/src/utility.cpp index 6952be54eed14d06ddcf3572d9bd2f4153894534..034df07804745178368a621936cd1ddabfd3a050 100644 --- a/deploy/cpp_infer/src/utility.cpp +++ b/deploy/cpp_infer/src/utility.cpp @@ -40,7 +40,8 @@ std::vector Utility::ReadDict(const std::string &path) { void Utility::VisualizeBboxes( const cv::Mat &srcimg, - const std::vector>> &boxes) { + const std::vector>> &boxes, + const std::string &save_path) { cv::Mat img_vis; srcimg.copyTo(img_vis); for (int n = 0; n < boxes.size(); n++) { @@ -54,8 +55,8 @@ void Utility::VisualizeBboxes( cv::polylines(img_vis, ppt, npt, 1, 1, CV_RGB(0, 255, 0), 2, 8, 0); } - cv::imwrite("./ocr_vis.png", img_vis); - std::cout << "The detection visualized image saved in ./ocr_vis.png" + cv::imwrite(save_path, img_vis); + std::cout << "The detection visualized image saved in " + save_path << std::endl; } @@ -93,7 +94,7 @@ void Utility::GetAllFiles(const char *dir_name, } cv::Mat Utility::GetRotateCropImage(const cv::Mat &srcimage, - std::vector> box) { + std::vector> box) { cv::Mat image; srcimage.copyTo(image); std::vector> points = box; @@ -147,17 +148,52 @@ cv::Mat Utility::GetRotateCropImage(const cv::Mat &srcimage, } } -std::vector Utility::argsort(const std::vector& array) -{ - const int array_len(array.size()); - std::vector array_index(array_len, 0); - for (int i = 0; i < array_len; ++i) - array_index[i] = i; +std::vector Utility::argsort(const std::vector &array) { + const int array_len(array.size()); + std::vector array_index(array_len, 0); + for (int i = 0; i < array_len; ++i) + array_index[i] = i; - std::sort(array_index.begin(), array_index.end(), - [&array](int pos1, int pos2) {return (array[pos1] < array[pos2]); }); + std::sort( + array_index.begin(), array_index.end(), + [&array](int pos1, int pos2) { return (array[pos1] < array[pos2]); }); - return array_index; + return array_index; +} + +std::string Utility::basename(const std::string &filename) { + if (filename.empty()) { + return ""; + } + + auto len = filename.length(); + auto index = filename.find_last_of("/\\"); + + if (index == std::string::npos) { + return filename; + } + + if (index + 1 >= len) { + + len--; + index = filename.substr(0, len).find_last_of("/\\"); + + if (len == 0) { + return filename; + } + + if (index == 0) { + return filename.substr(1, len - 1); + } + + if (index == std::string::npos) { + return filename.substr(0, len); + } + + return filename.substr(index + 1, len - index - 1); + } + + return filename.substr(index + 1, len - index); } } // namespace PaddleOCR \ No newline at end of file