diff --git a/deploy/cpp_infer/CMakeLists.txt b/deploy/cpp_infer/CMakeLists.txt index f741d5e8db65d426704fcbc6c01540275fd3e2f9..efb183c5b4ebb460832b7d353e8a019ee079d975 100644 --- a/deploy/cpp_infer/CMakeLists.txt +++ b/deploy/cpp_infer/CMakeLists.txt @@ -1,4 +1,4 @@ -project(ocr_system CXX C) +project(ppocr CXX C) option(WITH_MKL "Compile demo with MKL/OpenBlas support, default use MKL." ON) option(WITH_GPU "Compile demo with GPU/CPU, default use CPU." OFF) @@ -11,7 +11,7 @@ SET(CUDA_LIB "" CACHE PATH "Location of libraries") SET(CUDNN_LIB "" CACHE PATH "Location of libraries") SET(TENSORRT_DIR "" CACHE PATH "Compile demo with TensorRT") -set(DEMO_NAME "ocr_system") +set(DEMO_NAME "ppocr") macro(safe_set_static_flag) @@ -206,7 +206,7 @@ endif() set(DEPS ${DEPS} ${OpenCV_LIBS}) -AUX_SOURCE_DIRECTORY(./src_system SRCS) +AUX_SOURCE_DIRECTORY(./src SRCS) add_executable(${DEMO_NAME} ${SRCS}) target_link_libraries(${DEMO_NAME} ${DEPS}) diff --git a/deploy/cpp_infer/include/clipper.h b/deploy/cpp_infer/include/clipper.h index 384a6cf44c191a369906373d40fb81ffb02bb7fa..522f81c8c48fe77c50e87c8b753568432c056e38 100644 --- a/deploy/cpp_infer/include/clipper.h +++ b/deploy/cpp_infer/include/clipper.h @@ -31,6 +31,8 @@ * * *******************************************************************************/ +#pragma once + #ifndef clipper_hpp #define clipper_hpp diff --git a/deploy/cpp_infer/include/ocr_cls.h b/deploy/cpp_infer/include/ocr_cls.h index 41494085a797c7a4490942741e6e888033c0be00..a43c80053498843ec0152c96d209057017fff352 100644 --- a/deploy/cpp_infer/include/ocr_cls.h +++ b/deploy/cpp_infer/include/ocr_cls.h @@ -12,6 +12,8 @@ // See the License for the specific language governing permissions and // limitations under the License. +#pragma once + #include "opencv2/core.hpp" #include "opencv2/imgcodecs.hpp" #include "opencv2/imgproc.hpp" diff --git a/deploy/cpp_infer/include/ocr_rec.h b/deploy/cpp_infer/include/ocr_rec.h index 0c42f090003ccc8fbf1d433c34297653fb8a4b66..25f55ae26a29cc4f93f152cc072bd444aedf6bf2 100644 --- a/deploy/cpp_infer/include/ocr_rec.h +++ b/deploy/cpp_infer/include/ocr_rec.h @@ -12,6 +12,8 @@ // See the License for the specific language governing permissions and // limitations under the License. +#pragma once + #include "opencv2/core.hpp" #include "opencv2/imgcodecs.hpp" #include "opencv2/imgproc.hpp" diff --git a/deploy/cpp_infer/src/main.cpp b/deploy/cpp_infer/src/main.cpp new file mode 100644 index 0000000000000000000000000000000000000000..830f032d4649c44ed33527c383dd332b494c47c3 --- /dev/null +++ b/deploy/cpp_infer/src/main.cpp @@ -0,0 +1,336 @@ +// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// 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" +#include "opencv2/imgproc.hpp" +#include +#include +#include +#include +#include + +#include +#include +#include + +#include +#include +#include +#include +#include + +#include + +DEFINE_bool(use_gpu, false, "Infering with GPU or CPU."); +DEFINE_int32(gpu_id, 0, "Device id of GPU to execute."); +DEFINE_int32(gpu_mem, 4000, "GPU id when infering with GPU."); +DEFINE_int32(cpu_math_library_num_threads, 10, "Num of threads with CPU."); +DEFINE_bool(use_mkldnn, false, "Whether use mkldnn with CPU."); +DEFINE_bool(use_tensorrt, false, "Whether use tensorrt."); +DEFINE_bool(use_fp16, false, "Whether use fp16 when use tensorrt."); +// detection related +DEFINE_string(image_dir, "", "Dir of input image."); +DEFINE_string(det_model_dir, "", "Path of det inference model."); +DEFINE_int32(max_side_len, 960, "max_side_len of input image."); +DEFINE_double(det_db_thresh, 0.3, "Threshold of det_db_thresh."); +DEFINE_double(det_db_box_thresh, 0.5, "Threshold of det_db_box_thresh."); +DEFINE_double(det_db_unclip_ratio, 1.6, "Threshold of det_db_unclip_ratio."); +DEFINE_bool(use_polygon_score, false, "Whether use polygon score."); +DEFINE_bool(visualize, true, "Whether show the detection results."); +// classification related +DEFINE_bool(use_angle_cls, false, "Whether use use_angle_cls."); +DEFINE_string(cls_model_dir, "", "Path of cls inference model."); +DEFINE_double(cls_thresh, 0.9, "Threshold of cls_thresh."); +// recognition related +DEFINE_string(rec_model_dir, "", "Path of rec inference model."); +DEFINE_string(char_list_file, "../../ppocr/utils/ppocr_keys_v1.txt", "Path of dictionary."); + + +using namespace std; +using namespace cv; +using namespace PaddleOCR; + + +static bool PathExists(const std::string& path){ +#ifdef _WIN32 + struct _stat buffer; + return (_stat(path.c_str(), &buffer) == 0); +#else + struct stat buffer; + return (stat(path.c_str(), &buffer) == 0); +#endif // !_WIN32 +} + + +cv::Mat GetRotateCropImage(const cv::Mat &srcimage, + std::vector> box) { + cv::Mat image; + srcimage.copyTo(image); + std::vector> points = box; + + int x_collect[4] = {box[0][0], box[1][0], box[2][0], box[3][0]}; + int y_collect[4] = {box[0][1], box[1][1], box[2][1], box[3][1]}; + int left = int(*std::min_element(x_collect, x_collect + 4)); + int right = int(*std::max_element(x_collect, x_collect + 4)); + int top = int(*std::min_element(y_collect, y_collect + 4)); + int bottom = int(*std::max_element(y_collect, y_collect + 4)); + + cv::Mat img_crop; + image(cv::Rect(left, top, right - left, bottom - top)).copyTo(img_crop); + + for (int i = 0; i < points.size(); i++) { + points[i][0] -= left; + points[i][1] -= top; + } + + int img_crop_width = int(sqrt(pow(points[0][0] - points[1][0], 2) + + pow(points[0][1] - points[1][1], 2))); + int img_crop_height = int(sqrt(pow(points[0][0] - points[3][0], 2) + + pow(points[0][1] - points[3][1], 2))); + + cv::Point2f pts_std[4]; + pts_std[0] = cv::Point2f(0., 0.); + pts_std[1] = cv::Point2f(img_crop_width, 0.); + pts_std[2] = cv::Point2f(img_crop_width, img_crop_height); + pts_std[3] = cv::Point2f(0.f, img_crop_height); + + cv::Point2f pointsf[4]; + pointsf[0] = cv::Point2f(points[0][0], points[0][1]); + pointsf[1] = cv::Point2f(points[1][0], points[1][1]); + pointsf[2] = cv::Point2f(points[2][0], points[2][1]); + pointsf[3] = cv::Point2f(points[3][0], points[3][1]); + + cv::Mat M = cv::getPerspectiveTransform(pointsf, pts_std); + + cv::Mat dst_img; + cv::warpPerspective(img_crop, dst_img, M, + cv::Size(img_crop_width, img_crop_height), + cv::BORDER_REPLICATE); + + if (float(dst_img.rows) >= float(dst_img.cols) * 1.5) { + cv::Mat srcCopy = cv::Mat(dst_img.rows, dst_img.cols, dst_img.depth()); + cv::transpose(dst_img, srcCopy); + cv::flip(srcCopy, srcCopy, 0); + return srcCopy; + } else { + return dst_img; + } +} + + +int main_det(int argc, char **argv) { + // Parsing command-line + google::ParseCommandLineFlags(&argc, &argv, true); + if (FLAGS_det_model_dir.empty() || FLAGS_image_dir.empty()) { + std::cout << "Usage[det]: ./ppocr --det_model_dir=/PATH/TO/DET_INFERENCE_MODEL/ " + << "--image_dir=/PATH/TO/INPUT/IMAGE/" << std::endl; + exit(1); + } + if (!PathExists(FLAGS_image_dir)) { + std::cerr << "[ERROR] image path not exist! image_dir: " << FLAGS_image_dir << endl; + exit(1); + } + + std::vector cv_all_img_names; + cv::glob(FLAGS_image_dir, cv_all_img_names); + std::cout << "total images num: " << cv_all_img_names.size() << endl; + + DBDetector det(FLAGS_det_model_dir, FLAGS_use_gpu, FLAGS_gpu_id, + FLAGS_gpu_mem, FLAGS_cpu_math_library_num_threads, + FLAGS_use_mkldnn, FLAGS_max_side_len, FLAGS_det_db_thresh, + FLAGS_det_db_box_thresh, FLAGS_det_db_unclip_ratio, + FLAGS_use_polygon_score, FLAGS_visualize, + FLAGS_use_tensorrt, FLAGS_use_fp16); + + auto start = std::chrono::system_clock::now(); + + 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: " << cv_all_img_names[i] << endl; + exit(1); + } + std::vector>> boxes; + + det.Run(srcimg, boxes); + + auto end = std::chrono::system_clock::now(); + auto duration = + std::chrono::duration_cast(end - start); + std::cout << "Cost " + << double(duration.count()) * + std::chrono::microseconds::period::num / + std::chrono::microseconds::period::den + << "s" << std::endl; + } + + return 0; +} + + +int main_rec(int argc, char **argv) { + // Parsing command-line + google::ParseCommandLineFlags(&argc, &argv, true); + if (FLAGS_rec_model_dir.empty() || FLAGS_image_dir.empty()) { + std::cout << "Usage[rec]: ./ppocr --rec_model_dir=/PATH/TO/REC_INFERENCE_MODEL/ " + << "--image_dir=/PATH/TO/INPUT/IMAGE/" << std::endl; + exit(1); + } + if (!PathExists(FLAGS_image_dir)) { + std::cerr << "[ERROR] image path not exist! image_dir: " << FLAGS_image_dir << endl; + exit(1); + } + + std::vector cv_all_img_names; + cv::glob(FLAGS_image_dir, cv_all_img_names); + std::cout << "total images num: " << cv_all_img_names.size() << endl; + + CRNNRecognizer rec(FLAGS_rec_model_dir, FLAGS_use_gpu, FLAGS_gpu_id, + FLAGS_gpu_mem, FLAGS_cpu_math_library_num_threads, + FLAGS_use_mkldnn, FLAGS_char_list_file, + FLAGS_use_tensorrt, FLAGS_use_fp16); + + auto start = std::chrono::system_clock::now(); + + 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: " << cv_all_img_names[i] << endl; + exit(1); + } + + rec.Run(srcimg); + + auto end = std::chrono::system_clock::now(); + auto duration = + std::chrono::duration_cast(end - start); + std::cout << "Cost " + << double(duration.count()) * + std::chrono::microseconds::period::num / + std::chrono::microseconds::period::den + << "s" << std::endl; + } + + return 0; +} + + +int main_system(int argc, char **argv) { + // Parsing command-line + google::ParseCommandLineFlags(&argc, &argv, true); + if ((FLAGS_det_model_dir.empty() || FLAGS_rec_model_dir.empty() || FLAGS_image_dir.empty()) || + (FLAGS_use_angle_cls && FLAGS_cls_model_dir.empty())) { + std::cout << "Usage[system without angle cls]: ./ppocr --det_model_dir=/PATH/TO/DET_INFERENCE_MODEL/ " + << "--rec_model_dir=/PATH/TO/REC_INFERENCE_MODEL/ " + << "--image_dir=/PATH/TO/INPUT/IMAGE/" << std::endl; + std::cout << "Usage[system with angle cls]: ./ppocr --det_model_dir=/PATH/TO/DET_INFERENCE_MODEL/ " + << "--use_angle_cls=true " + << "--cls_model_dir=/PATH/TO/CLS_INFERENCE_MODEL/ " + << "--rec_model_dir=/PATH/TO/REC_INFERENCE_MODEL/ " + << "--image_dir=/PATH/TO/INPUT/IMAGE/" << std::endl; + exit(1); + } + if (!PathExists(FLAGS_image_dir)) { + std::cerr << "[ERROR] image path not exist! image_dir: " << FLAGS_image_dir << endl; + exit(1); + } + + std::vector cv_all_img_names; + cv::glob(FLAGS_image_dir, cv_all_img_names); + std::cout << "total images num: " << cv_all_img_names.size() << endl; + + DBDetector det(FLAGS_det_model_dir, FLAGS_use_gpu, FLAGS_gpu_id, + FLAGS_gpu_mem, FLAGS_cpu_math_library_num_threads, + FLAGS_use_mkldnn, FLAGS_max_side_len, FLAGS_det_db_thresh, + FLAGS_det_db_box_thresh, FLAGS_det_db_unclip_ratio, + FLAGS_use_polygon_score, FLAGS_visualize, + FLAGS_use_tensorrt, FLAGS_use_fp16); + + Classifier *cls = nullptr; + if (FLAGS_use_angle_cls) { + cls = new Classifier(FLAGS_cls_model_dir, FLAGS_use_gpu, FLAGS_gpu_id, + FLAGS_gpu_mem, FLAGS_cpu_math_library_num_threads, + FLAGS_use_mkldnn, FLAGS_cls_thresh, + FLAGS_use_tensorrt, FLAGS_use_fp16); + } + + CRNNRecognizer rec(FLAGS_rec_model_dir, FLAGS_use_gpu, FLAGS_gpu_id, + FLAGS_gpu_mem, FLAGS_cpu_math_library_num_threads, + FLAGS_use_mkldnn, FLAGS_char_list_file, + FLAGS_use_tensorrt, FLAGS_use_fp16); + + auto start = std::chrono::system_clock::now(); + + 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(FLAGS_image_dir, cv::IMREAD_COLOR); + if (!srcimg.data) { + std::cerr << "[ERROR] image read failed! image path: " << cv_all_img_names[i] << endl; + exit(1); + } + std::vector>> boxes; + + det.Run(srcimg, boxes); + + cv::Mat crop_img; + for (int j = 0; j < boxes.size(); j++) { + crop_img = GetRotateCropImage(srcimg, boxes[j]); + + if (cls != nullptr) { + crop_img = cls->Run(crop_img); + } + rec.Run(crop_img); + } + + auto end = std::chrono::system_clock::now(); + auto duration = + std::chrono::duration_cast(end - start); + std::cout << "Cost " + << double(duration.count()) * + std::chrono::microseconds::period::num / + std::chrono::microseconds::period::den + << "s" << std::endl; + } + + return 0; +} + + +int main(int argc, char **argv) { + if (strcmp(argv[1], "det")!=0 && strcmp(argv[1], "rec")!=0 && strcmp(argv[1], "system")!=0) { + std::cout << "Please choose one mode of [det, rec, system] !" << std::endl; + return -1; + } + std::cout << "mode: " << argv[1] << endl; + + if (strcmp(argv[1], "det")==0) { + return main_det(argc, argv); + } + if (strcmp(argv[1], "rec")==0) { + return main_rec(argc, argv); + } + if (strcmp(argv[1], "system")==0) { + return main_system(argc, argv); + } + +// return 0; +} diff --git a/deploy/cpp_infer/src_system/ocr_cls.cpp b/deploy/cpp_infer/src/ocr_cls.cpp similarity index 100% rename from deploy/cpp_infer/src_system/ocr_cls.cpp rename to deploy/cpp_infer/src/ocr_cls.cpp diff --git a/deploy/cpp_infer/src_system/ocr_det.cpp b/deploy/cpp_infer/src/ocr_det.cpp similarity index 98% rename from deploy/cpp_infer/src_system/ocr_det.cpp rename to deploy/cpp_infer/src/ocr_det.cpp index 110393107092ade1a20865b52656053503358fe4..58dc4dce8117f81b17e3c88ea02404d474ea9248 100644 --- a/deploy/cpp_infer/src_system/ocr_det.cpp +++ b/deploy/cpp_infer/src/ocr_det.cpp @@ -13,8 +13,7 @@ // limitations under the License. #include -#include -#include + namespace PaddleOCR { diff --git a/deploy/cpp_infer/src_system/ocr_rec.cpp b/deploy/cpp_infer/src/ocr_rec.cpp similarity index 100% rename from deploy/cpp_infer/src_system/ocr_rec.cpp rename to deploy/cpp_infer/src/ocr_rec.cpp diff --git a/deploy/cpp_infer/include/postprocess_op.cpp b/deploy/cpp_infer/src/postprocess_op.cpp similarity index 100% rename from deploy/cpp_infer/include/postprocess_op.cpp rename to deploy/cpp_infer/src/postprocess_op.cpp diff --git a/deploy/cpp_infer/include/preprocess_op.cpp b/deploy/cpp_infer/src/preprocess_op.cpp similarity index 100% rename from deploy/cpp_infer/include/preprocess_op.cpp rename to deploy/cpp_infer/src/preprocess_op.cpp diff --git a/deploy/cpp_infer/src_det/main.cpp b/deploy/cpp_infer/src_det/main.cpp deleted file mode 100644 index b3e45cea4e0f6941596f4e2358bbb2427ca12f78..0000000000000000000000000000000000000000 --- a/deploy/cpp_infer/src_det/main.cpp +++ /dev/null @@ -1,120 +0,0 @@ -// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// 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" -#include "opencv2/imgproc.hpp" -#include -#include -#include -#include -#include - -#include -#include -#include - -#include -#include -#include - -#include - -DEFINE_bool(use_gpu, false, "Infering with GPU or CPU."); -DEFINE_int32(gpu_id, 0, "Device id of GPU to execute."); -DEFINE_int32(gpu_mem, 4000, "GPU id when infering with GPU."); -DEFINE_int32(cpu_math_library_num_threads, 10, "Num of threads with CPU."); -DEFINE_bool(use_mkldnn, false, "Whether use mkldnn with CPU."); - -DEFINE_string(image_dir, "", "Dir of input image."); -DEFINE_string(det_model_dir, "", "Path of det inference model."); -DEFINE_int32(max_side_len, 960, "max_side_len of input image."); -DEFINE_double(det_db_thresh, 0.3, "Threshold of det_db_thresh."); -DEFINE_double(det_db_box_thresh, 0.5, "Threshold of det_db_box_thresh."); -DEFINE_double(det_db_unclip_ratio, 1.6, "Threshold of det_db_unclip_ratio."); -DEFINE_bool(use_polygon_score, false, "Whether use polygon score."); -DEFINE_bool(visualize, true, "Whether show the detection results."); - -DEFINE_bool(use_tensorrt, false, "Whether use tensorrt."); -DEFINE_bool(use_fp16, false, "Whether use fp16 when use tensorrt."); - - -using namespace std; -using namespace cv; -using namespace PaddleOCR; - - -static bool PathExists(const std::string& path){ -#ifdef _WIN32 - struct _stat buffer; - return (_stat(path.c_str(), &buffer) == 0); -#else - struct stat buffer; - return (stat(path.c_str(), &buffer) == 0); -#endif // !_WIN32 -} - - -int main(int argc, char **argv) { - // Parsing command-line - google::ParseCommandLineFlags(&argc, &argv, true); - if (FLAGS_det_model_dir.empty() || FLAGS_image_dir.empty()) { - std::cout << "Usage: ./ocr_det --det_model_dir=/PATH/TO/INFERENCE_MODEL/ " - << "--image_dir=/PATH/TO/INPUT/IMAGE/" << std::endl; - return -1; - } - - if (!PathExists(FLAGS_image_dir)) { - std::cerr << "[ERROR] image path not exist! image_dir: " << FLAGS_image_dir << endl; - exit(1); - } - std::vector cv_all_img_names; - cv::glob(FLAGS_image_dir, cv_all_img_names); - std::cout << "total images num: " << cv_all_img_names.size() << endl; - - DBDetector det(FLAGS_det_model_dir, FLAGS_use_gpu, FLAGS_gpu_id, - FLAGS_gpu_mem, FLAGS_cpu_math_library_num_threads, - FLAGS_use_mkldnn, FLAGS_max_side_len, FLAGS_det_db_thresh, - FLAGS_det_db_box_thresh, FLAGS_det_db_unclip_ratio, - FLAGS_use_polygon_score, FLAGS_visualize, - FLAGS_use_tensorrt, FLAGS_use_fp16); - - auto start = std::chrono::system_clock::now(); - - 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: " << cv_all_img_names[i] << endl; - exit(1); - } - std::vector>> boxes; - - det.Run(srcimg, boxes); - - auto end = std::chrono::system_clock::now(); - auto duration = - std::chrono::duration_cast(end - start); - std::cout << "Cost " - << double(duration.count()) * - std::chrono::microseconds::period::num / - std::chrono::microseconds::period::den - << "s" << std::endl; - } - - return 0; -} diff --git a/deploy/cpp_infer/src_det/ocr_det.cpp b/deploy/cpp_infer/src_det/ocr_det.cpp deleted file mode 100644 index 110393107092ade1a20865b52656053503358fe4..0000000000000000000000000000000000000000 --- a/deploy/cpp_infer/src_det/ocr_det.cpp +++ /dev/null @@ -1,163 +0,0 @@ -// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// See the License for the specific language governing permissions and -// limitations under the License. - -#include -#include -#include - -namespace PaddleOCR { - -void DBDetector::LoadModel(const std::string &model_dir) { - // AnalysisConfig config; - paddle_infer::Config config; - config.SetModel(model_dir + "/inference.pdmodel", - model_dir + "/inference.pdiparams"); - - if (this->use_gpu_) { - config.EnableUseGpu(this->gpu_mem_, this->gpu_id_); - if (this->use_tensorrt_) { - config.EnableTensorRtEngine( - 1 << 20, 10, 3, - this->use_fp16_ ? paddle_infer::Config::Precision::kHalf - : paddle_infer::Config::Precision::kFloat32, - false, false); - std::map> min_input_shape = { - {"x", {1, 3, 50, 50}}, - {"conv2d_92.tmp_0", {1, 96, 20, 20}}, - {"conv2d_91.tmp_0", {1, 96, 10, 10}}, - {"nearest_interp_v2_1.tmp_0", {1, 96, 10, 10}}, - {"nearest_interp_v2_2.tmp_0", {1, 96, 20, 20}}, - {"nearest_interp_v2_3.tmp_0", {1, 24, 20, 20}}, - {"nearest_interp_v2_4.tmp_0", {1, 24, 20, 20}}, - {"nearest_interp_v2_5.tmp_0", {1, 24, 20, 20}}, - {"elementwise_add_7", {1, 56, 2, 2}}, - {"nearest_interp_v2_0.tmp_0", {1, 96, 2, 2}}}; - std::map> max_input_shape = { - {"x", {1, 3, this->max_side_len_, this->max_side_len_}}, - {"conv2d_92.tmp_0", {1, 96, 400, 400}}, - {"conv2d_91.tmp_0", {1, 96, 200, 200}}, - {"nearest_interp_v2_1.tmp_0", {1, 96, 200, 200}}, - {"nearest_interp_v2_2.tmp_0", {1, 96, 400, 400}}, - {"nearest_interp_v2_3.tmp_0", {1, 24, 400, 400}}, - {"nearest_interp_v2_4.tmp_0", {1, 24, 400, 400}}, - {"nearest_interp_v2_5.tmp_0", {1, 24, 400, 400}}, - {"elementwise_add_7", {1, 56, 400, 400}}, - {"nearest_interp_v2_0.tmp_0", {1, 96, 400, 400}}}; - std::map> opt_input_shape = { - {"x", {1, 3, 640, 640}}, - {"conv2d_92.tmp_0", {1, 96, 160, 160}}, - {"conv2d_91.tmp_0", {1, 96, 80, 80}}, - {"nearest_interp_v2_1.tmp_0", {1, 96, 80, 80}}, - {"nearest_interp_v2_2.tmp_0", {1, 96, 160, 160}}, - {"nearest_interp_v2_3.tmp_0", {1, 24, 160, 160}}, - {"nearest_interp_v2_4.tmp_0", {1, 24, 160, 160}}, - {"nearest_interp_v2_5.tmp_0", {1, 24, 160, 160}}, - {"elementwise_add_7", {1, 56, 40, 40}}, - {"nearest_interp_v2_0.tmp_0", {1, 96, 40, 40}}}; - - config.SetTRTDynamicShapeInfo(min_input_shape, max_input_shape, - opt_input_shape); - } - } else { - config.DisableGpu(); - if (this->use_mkldnn_) { - config.EnableMKLDNN(); - // cache 10 different shapes for mkldnn to avoid memory leak - config.SetMkldnnCacheCapacity(10); - } - config.SetCpuMathLibraryNumThreads(this->cpu_math_library_num_threads_); - } - // use zero_copy_run as default - config.SwitchUseFeedFetchOps(false); - // true for multiple input - config.SwitchSpecifyInputNames(true); - - config.SwitchIrOptim(true); - - config.EnableMemoryOptim(); - // config.DisableGlogInfo(); - - this->predictor_ = CreatePredictor(config); -} - -void DBDetector::Run(cv::Mat &img, - std::vector>> &boxes) { - float ratio_h{}; - float ratio_w{}; - - cv::Mat srcimg; - cv::Mat resize_img; - img.copyTo(srcimg); - this->resize_op_.Run(img, resize_img, this->max_side_len_, ratio_h, ratio_w, - this->use_tensorrt_); - - this->normalize_op_.Run(&resize_img, this->mean_, this->scale_, - this->is_scale_); - - std::vector input(1 * 3 * resize_img.rows * resize_img.cols, 0.0f); - this->permute_op_.Run(&resize_img, input.data()); - - // Inference. - auto input_names = this->predictor_->GetInputNames(); - auto input_t = this->predictor_->GetInputHandle(input_names[0]); - input_t->Reshape({1, 3, resize_img.rows, resize_img.cols}); - input_t->CopyFromCpu(input.data()); - this->predictor_->Run(); - - std::vector out_data; - auto output_names = this->predictor_->GetOutputNames(); - auto output_t = this->predictor_->GetOutputHandle(output_names[0]); - std::vector output_shape = output_t->shape(); - int out_num = std::accumulate(output_shape.begin(), output_shape.end(), 1, - std::multiplies()); - - out_data.resize(out_num); - output_t->CopyToCpu(out_data.data()); - - int n2 = output_shape[2]; - int n3 = output_shape[3]; - int n = n2 * n3; - - std::vector pred(n, 0.0); - std::vector cbuf(n, ' '); - - for (int i = 0; i < n; i++) { - pred[i] = float(out_data[i]); - cbuf[i] = (unsigned char)((out_data[i]) * 255); - } - - cv::Mat cbuf_map(n2, n3, CV_8UC1, (unsigned char *)cbuf.data()); - cv::Mat pred_map(n2, n3, CV_32F, (float *)pred.data()); - - const double threshold = this->det_db_thresh_ * 255; - const double maxvalue = 255; - cv::Mat bit_map; - cv::threshold(cbuf_map, bit_map, threshold, maxvalue, cv::THRESH_BINARY); - cv::Mat dilation_map; - cv::Mat dila_ele = cv::getStructuringElement(cv::MORPH_RECT, cv::Size(2, 2)); - cv::dilate(bit_map, dilation_map, dila_ele); - boxes = post_processor_.BoxesFromBitmap( - pred_map, dilation_map, this->det_db_box_thresh_, - this->det_db_unclip_ratio_, this->use_polygon_score_); - - boxes = post_processor_.FilterTagDetRes(boxes, ratio_h, ratio_w, srcimg); - std::cout << "Detected boxes num: " << boxes.size() << endl; - - //// visualization - if (this->visualize_) { - Utility::VisualizeBboxes(srcimg, boxes); - } -} - -} // namespace PaddleOCR diff --git a/deploy/cpp_infer/src_rec/main.cpp b/deploy/cpp_infer/src_rec/main.cpp deleted file mode 100644 index a9355be90b009223fd67c28491353086858a43b6..0000000000000000000000000000000000000000 --- a/deploy/cpp_infer/src_rec/main.cpp +++ /dev/null @@ -1,112 +0,0 @@ -// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// 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" -#include "opencv2/imgproc.hpp" -#include -#include -#include -#include -#include - -#include -#include -#include - -#include -#include -#include - -#include - -DEFINE_bool(use_gpu, false, "Infering with GPU or CPU."); -DEFINE_int32(gpu_id, 0, "Device id of GPU to execute."); -DEFINE_int32(gpu_mem, 4000, "GPU id when infering with GPU."); -DEFINE_int32(cpu_math_library_num_threads, 10, "Num of threads with CPU."); -DEFINE_bool(use_mkldnn, false, "Whether use mkldnn with CPU."); - -DEFINE_string(image_dir, "", "Dir of input image."); -DEFINE_string(rec_model_dir, "", "Path of rec inference model."); -DEFINE_string(char_list_file, "../../ppocr/utils/ppocr_keys_v1.txt", "Path of dictionary."); - -DEFINE_bool(use_tensorrt, false, "Whether use tensorrt."); -DEFINE_bool(use_fp16, false, "Whether use fp16 when use tensorrt."); - - -using namespace std; -using namespace cv; -using namespace PaddleOCR; - - -static bool PathExists(const std::string& path){ -#ifdef _WIN32 - struct _stat buffer; - return (_stat(path.c_str(), &buffer) == 0); -#else - struct stat buffer; - return (stat(path.c_str(), &buffer) == 0); -#endif // !_WIN32 -} - - -int main(int argc, char **argv) { - // Parsing command-line - google::ParseCommandLineFlags(&argc, &argv, true); - if (FLAGS_rec_model_dir.empty() || FLAGS_image_dir.empty()) { - std::cout << "Usage: ./ocr_rec --rec_model_dir=/PATH/TO/INFERENCE_MODEL/ " - << "--image_dir=/PATH/TO/INPUT/IMAGE/" << std::endl; - return -1; - } - - if (!PathExists(FLAGS_image_dir)) { - std::cerr << "[ERROR] image path not exist! image_dir: " << FLAGS_image_dir << endl; - exit(1); - } - std::vector cv_all_img_names; - cv::glob(FLAGS_image_dir, cv_all_img_names); - std::cout << "total images num: " << cv_all_img_names.size() << endl; - - CRNNRecognizer rec(FLAGS_rec_model_dir, FLAGS_use_gpu, FLAGS_gpu_id, - FLAGS_gpu_mem, FLAGS_cpu_math_library_num_threads, - FLAGS_use_mkldnn, FLAGS_char_list_file, - FLAGS_use_tensorrt, FLAGS_use_fp16); - - auto start = std::chrono::system_clock::now(); - - 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: " << cv_all_img_names[i] << endl; - exit(1); - } - - rec.Run(srcimg); - - auto end = std::chrono::system_clock::now(); - auto duration = - std::chrono::duration_cast(end - start); - std::cout << "Cost " - << double(duration.count()) * - std::chrono::microseconds::period::num / - std::chrono::microseconds::period::den - << "s" << std::endl; - } - - return 0; -} diff --git a/deploy/cpp_infer/src_rec/ocr_rec.cpp b/deploy/cpp_infer/src_rec/ocr_rec.cpp deleted file mode 100644 index 5aa20770bae8470342cd0e3d3c87b6f4a5358f69..0000000000000000000000000000000000000000 --- a/deploy/cpp_infer/src_rec/ocr_rec.cpp +++ /dev/null @@ -1,185 +0,0 @@ -// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// See the License for the specific language governing permissions and -// limitations under the License. - -#include -#include - -namespace PaddleOCR { - -void CRNNRecognizer::Run(cv::Mat &img) { - cv::Mat srcimg; - img.copyTo(srcimg); - cv::Mat resize_img; - - float wh_ratio = float(srcimg.cols) / float(srcimg.rows); - - this->resize_op_.Run(srcimg, resize_img, wh_ratio, this->use_tensorrt_); - - this->normalize_op_.Run(&resize_img, this->mean_, this->scale_, - this->is_scale_); - - std::vector input(1 * 3 * resize_img.rows * resize_img.cols, 0.0f); - - this->permute_op_.Run(&resize_img, input.data()); - - // Inference. - auto input_names = this->predictor_->GetInputNames(); - auto input_t = this->predictor_->GetInputHandle(input_names[0]); - input_t->Reshape({1, 3, resize_img.rows, resize_img.cols}); - input_t->CopyFromCpu(input.data()); - this->predictor_->Run(); - - std::vector predict_batch; - auto output_names = this->predictor_->GetOutputNames(); - auto output_t = this->predictor_->GetOutputHandle(output_names[0]); - auto predict_shape = output_t->shape(); - - int out_num = std::accumulate(predict_shape.begin(), predict_shape.end(), 1, - std::multiplies()); - predict_batch.resize(out_num); - - output_t->CopyToCpu(predict_batch.data()); - - // ctc decode - std::vector str_res; - int argmax_idx; - int last_index = 0; - float score = 0.f; - int count = 0; - float max_value = 0.0f; - - for (int n = 0; n < predict_shape[1]; n++) { - argmax_idx = - int(Utility::argmax(&predict_batch[n * predict_shape[2]], - &predict_batch[(n + 1) * predict_shape[2]])); - max_value = - float(*std::max_element(&predict_batch[n * predict_shape[2]], - &predict_batch[(n + 1) * predict_shape[2]])); - - if (argmax_idx > 0 && (!(n > 0 && argmax_idx == last_index))) { - score += max_value; - count += 1; - str_res.push_back(label_list_[argmax_idx]); - } - last_index = argmax_idx; - } - score /= count; - for (int i = 0; i < str_res.size(); i++) { - std::cout << str_res[i]; - } - std::cout << "\tscore: " << score << std::endl; -} - -void CRNNRecognizer::LoadModel(const std::string &model_dir) { - // AnalysisConfig config; - paddle_infer::Config config; - config.SetModel(model_dir + "/inference.pdmodel", - model_dir + "/inference.pdiparams"); - - if (this->use_gpu_) { - config.EnableUseGpu(this->gpu_mem_, this->gpu_id_); - if (this->use_tensorrt_) { - config.EnableTensorRtEngine( - 1 << 20, 10, 3, - this->use_fp16_ ? paddle_infer::Config::Precision::kHalf - : paddle_infer::Config::Precision::kFloat32, - false, false); - std::map> min_input_shape = { - {"x", {1, 3, 32, 10}}}; - std::map> max_input_shape = { - {"x", {1, 3, 32, 2000}}}; - std::map> opt_input_shape = { - {"x", {1, 3, 32, 320}}}; - - config.SetTRTDynamicShapeInfo(min_input_shape, max_input_shape, - opt_input_shape); - } - } else { - config.DisableGpu(); - if (this->use_mkldnn_) { - config.EnableMKLDNN(); - // cache 10 different shapes for mkldnn to avoid memory leak - config.SetMkldnnCacheCapacity(10); - } - config.SetCpuMathLibraryNumThreads(this->cpu_math_library_num_threads_); - } - - config.SwitchUseFeedFetchOps(false); - // true for multiple input - config.SwitchSpecifyInputNames(true); - - config.SwitchIrOptim(true); - - config.EnableMemoryOptim(); - config.DisableGlogInfo(); - - this->predictor_ = CreatePredictor(config); -} - -cv::Mat CRNNRecognizer::GetRotateCropImage(const cv::Mat &srcimage, - std::vector> box) { - cv::Mat image; - srcimage.copyTo(image); - std::vector> points = box; - - int x_collect[4] = {box[0][0], box[1][0], box[2][0], box[3][0]}; - int y_collect[4] = {box[0][1], box[1][1], box[2][1], box[3][1]}; - int left = int(*std::min_element(x_collect, x_collect + 4)); - int right = int(*std::max_element(x_collect, x_collect + 4)); - int top = int(*std::min_element(y_collect, y_collect + 4)); - int bottom = int(*std::max_element(y_collect, y_collect + 4)); - - cv::Mat img_crop; - image(cv::Rect(left, top, right - left, bottom - top)).copyTo(img_crop); - - for (int i = 0; i < points.size(); i++) { - points[i][0] -= left; - points[i][1] -= top; - } - - int img_crop_width = int(sqrt(pow(points[0][0] - points[1][0], 2) + - pow(points[0][1] - points[1][1], 2))); - int img_crop_height = int(sqrt(pow(points[0][0] - points[3][0], 2) + - pow(points[0][1] - points[3][1], 2))); - - cv::Point2f pts_std[4]; - pts_std[0] = cv::Point2f(0., 0.); - pts_std[1] = cv::Point2f(img_crop_width, 0.); - pts_std[2] = cv::Point2f(img_crop_width, img_crop_height); - pts_std[3] = cv::Point2f(0.f, img_crop_height); - - cv::Point2f pointsf[4]; - pointsf[0] = cv::Point2f(points[0][0], points[0][1]); - pointsf[1] = cv::Point2f(points[1][0], points[1][1]); - pointsf[2] = cv::Point2f(points[2][0], points[2][1]); - pointsf[3] = cv::Point2f(points[3][0], points[3][1]); - - cv::Mat M = cv::getPerspectiveTransform(pointsf, pts_std); - - cv::Mat dst_img; - cv::warpPerspective(img_crop, dst_img, M, - cv::Size(img_crop_width, img_crop_height), - cv::BORDER_REPLICATE); - - if (float(dst_img.rows) >= float(dst_img.cols) * 1.5) { - cv::Mat srcCopy = cv::Mat(dst_img.rows, dst_img.cols, dst_img.depth()); - cv::transpose(dst_img, srcCopy); - cv::flip(srcCopy, srcCopy, 0); - return srcCopy; - } else { - return dst_img; - } -} - -} // namespace PaddleOCR diff --git a/deploy/cpp_infer/src_system/main.cpp b/deploy/cpp_infer/src_system/main.cpp deleted file mode 100644 index 8409e3296dd8cca6210d6705de9a2c4b7bf1d8b0..0000000000000000000000000000000000000000 --- a/deploy/cpp_infer/src_system/main.cpp +++ /dev/null @@ -1,213 +0,0 @@ -// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// 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" -#include "opencv2/imgproc.hpp" -#include -#include -#include -#include -#include - -#include -#include -#include - -#include -#include -#include -#include - -#include - -DEFINE_bool(use_gpu, false, "Infering with GPU or CPU."); -DEFINE_int32(gpu_id, 0, "Device id of GPU to execute."); -DEFINE_int32(gpu_mem, 4000, "GPU id when infering with GPU."); -DEFINE_int32(cpu_math_library_num_threads, 10, "Num of threads with CPU."); -DEFINE_bool(use_mkldnn, false, "Whether use mkldnn with CPU."); - -DEFINE_string(image_dir, "", "Dir of input image."); -DEFINE_string(det_model_dir, "", "Path of det inference model."); -DEFINE_int32(max_side_len, 960, "max_side_len of input image."); -DEFINE_double(det_db_thresh, 0.3, "Threshold of det_db_thresh."); -DEFINE_double(det_db_box_thresh, 0.5, "Threshold of det_db_box_thresh."); -DEFINE_double(det_db_unclip_ratio, 1.6, "Threshold of det_db_unclip_ratio."); -DEFINE_bool(use_polygon_score, false, "Whether use polygon score."); -DEFINE_bool(visualize, true, "Whether show the detection results."); - -DEFINE_bool(use_angle_cls, false, "Whether use use_angle_cls."); -DEFINE_string(cls_model_dir, "", "Path of cls inference model."); -DEFINE_double(cls_thresh, 0.9, "Threshold of cls_thresh."); - -DEFINE_string(rec_model_dir, "", "Path of rec inference model."); -DEFINE_string(char_list_file, "../../ppocr/utils/ppocr_keys_v1.txt", "Path of dictionary."); - -DEFINE_bool(use_tensorrt, false, "Whether use tensorrt."); -DEFINE_bool(use_fp16, false, "Whether use fp16 when use tensorrt."); - -using namespace std; -using namespace cv; -using namespace PaddleOCR; - - -static bool PathExists(const std::string& path){ -#ifdef _WIN32 - struct _stat buffer; - return (_stat(path.c_str(), &buffer) == 0); -#else - struct stat buffer; - return (stat(path.c_str(), &buffer) == 0); -#endif // !_WIN32 -} - - -cv::Mat GetRotateCropImage(const cv::Mat &srcimage, - std::vector> box) { - cv::Mat image; - srcimage.copyTo(image); - std::vector> points = box; - - int x_collect[4] = {box[0][0], box[1][0], box[2][0], box[3][0]}; - int y_collect[4] = {box[0][1], box[1][1], box[2][1], box[3][1]}; - int left = int(*std::min_element(x_collect, x_collect + 4)); - int right = int(*std::max_element(x_collect, x_collect + 4)); - int top = int(*std::min_element(y_collect, y_collect + 4)); - int bottom = int(*std::max_element(y_collect, y_collect + 4)); - - cv::Mat img_crop; - image(cv::Rect(left, top, right - left, bottom - top)).copyTo(img_crop); - - for (int i = 0; i < points.size(); i++) { - points[i][0] -= left; - points[i][1] -= top; - } - - int img_crop_width = int(sqrt(pow(points[0][0] - points[1][0], 2) + - pow(points[0][1] - points[1][1], 2))); - int img_crop_height = int(sqrt(pow(points[0][0] - points[3][0], 2) + - pow(points[0][1] - points[3][1], 2))); - - cv::Point2f pts_std[4]; - pts_std[0] = cv::Point2f(0., 0.); - pts_std[1] = cv::Point2f(img_crop_width, 0.); - pts_std[2] = cv::Point2f(img_crop_width, img_crop_height); - pts_std[3] = cv::Point2f(0.f, img_crop_height); - - cv::Point2f pointsf[4]; - pointsf[0] = cv::Point2f(points[0][0], points[0][1]); - pointsf[1] = cv::Point2f(points[1][0], points[1][1]); - pointsf[2] = cv::Point2f(points[2][0], points[2][1]); - pointsf[3] = cv::Point2f(points[3][0], points[3][1]); - - cv::Mat M = cv::getPerspectiveTransform(pointsf, pts_std); - - cv::Mat dst_img; - cv::warpPerspective(img_crop, dst_img, M, - cv::Size(img_crop_width, img_crop_height), - cv::BORDER_REPLICATE); - - if (float(dst_img.rows) >= float(dst_img.cols) * 1.5) { - cv::Mat srcCopy = cv::Mat(dst_img.rows, dst_img.cols, dst_img.depth()); - cv::transpose(dst_img, srcCopy); - cv::flip(srcCopy, srcCopy, 0); - return srcCopy; - } else { - return dst_img; - } -} - - -int main(int argc, char **argv) { - // Parsing command-line - google::ParseCommandLineFlags(&argc, &argv, true); - if ((FLAGS_det_model_dir.empty() || FLAGS_rec_model_dir.empty() || FLAGS_image_dir.empty()) || - (FLAGS_use_angle_cls && FLAGS_cls_model_dir.empty())) { - std::cout << "Usage[default]: ./ocr_system --det_model_dir=/PATH/TO/DET_INFERENCE_MODEL/ " - << "--rec_model_dir=/PATH/TO/REC_INFERENCE_MODEL/ " - << "--image_dir=/PATH/TO/INPUT/IMAGE/" << std::endl; - std::cout << "Usage[use angle cls]: ./ocr_system --det_model_dir=/PATH/TO/DET_INFERENCE_MODEL/ " - << "--use_angle_cls=true " - << "--cls_model_dir=/PATH/TO/CLS_INFERENCE_MODEL/ " - << "--rec_model_dir=/PATH/TO/REC_INFERENCE_MODEL/ " - << "--image_dir=/PATH/TO/INPUT/IMAGE/" << std::endl; - return -1; - } - - if (!PathExists(FLAGS_image_dir)) { - std::cerr << "[ERROR] image path not exist! image_dir: " << FLAGS_image_dir << endl; - exit(1); - } - std::vector cv_all_img_names; - cv::glob(FLAGS_image_dir, cv_all_img_names); - std::cout << "total images num: " << cv_all_img_names.size() << endl; - - DBDetector det(FLAGS_det_model_dir, FLAGS_use_gpu, FLAGS_gpu_id, - FLAGS_gpu_mem, FLAGS_cpu_math_library_num_threads, - FLAGS_use_mkldnn, FLAGS_max_side_len, FLAGS_det_db_thresh, - FLAGS_det_db_box_thresh, FLAGS_det_db_unclip_ratio, - FLAGS_use_polygon_score, FLAGS_visualize, - FLAGS_use_tensorrt, FLAGS_use_fp16); - - Classifier *cls = nullptr; - if (FLAGS_use_angle_cls) { - cls = new Classifier(FLAGS_cls_model_dir, FLAGS_use_gpu, FLAGS_gpu_id, - FLAGS_gpu_mem, FLAGS_cpu_math_library_num_threads, - FLAGS_use_mkldnn, FLAGS_cls_thresh, - FLAGS_use_tensorrt, FLAGS_use_fp16); - } - - CRNNRecognizer rec(FLAGS_rec_model_dir, FLAGS_use_gpu, FLAGS_gpu_id, - FLAGS_gpu_mem, FLAGS_cpu_math_library_num_threads, - FLAGS_use_mkldnn, FLAGS_char_list_file, - FLAGS_use_tensorrt, FLAGS_use_fp16); - - auto start = std::chrono::system_clock::now(); - - 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(FLAGS_image_dir, cv::IMREAD_COLOR); - if (!srcimg.data) { - std::cerr << "[ERROR] image read failed! image path: " << cv_all_img_names[i] << endl; - exit(1); - } - std::vector>> boxes; - - det.Run(srcimg, boxes); - - cv::Mat crop_img; - for (int j = 0; j < boxes.size(); j++) { - crop_img = GetRotateCropImage(srcimg, boxes[j]); - - if (cls != nullptr) { - crop_img = cls->Run(crop_img); - } - rec.Run(crop_img); - } - - auto end = std::chrono::system_clock::now(); - auto duration = - std::chrono::duration_cast(end - start); - std::cout << "Cost " - << double(duration.count()) * - std::chrono::microseconds::period::num / - std::chrono::microseconds::period::den - << "s" << std::endl; - } - - return 0; -} diff --git a/deploy/cpp_infer/tools/build.sh b/deploy/cpp_infer/tools/build.sh index 6ae5833f58546765f047ba64ed8ed55afd0c1654..66586a9a02383665546317ef198376b14c5fbcea 100755 --- a/deploy/cpp_infer/tools/build.sh +++ b/deploy/cpp_infer/tools/build.sh @@ -1,16 +1,3 @@ -set -o errexit - -if [ $# != 1 ] ; then -echo "USAGE: $0 MODE (one of ['det', 'rec', 'system'])" -echo " e.g.: $0 system" -exit 1; -fi - -# MODE be one of ['det', 'rec', 'system'] -MODE=$1 -cp CMakeLists_$MODE.txt CMakeLists.txt - - OPENCV_DIR=/paddle/git/new/PaddleOCR/deploy/cpp_infer/opencv-3.4.7/opencv3/ LIB_DIR=/paddle/git/new/PaddleOCR/deploy/cpp_infer/paddle_inference/ CUDA_LIB_DIR=/usr/local/cuda/lib64/ diff --git a/deploy/cpp_infer/tools/config.txt b/deploy/cpp_infer/tools/config.txt deleted file mode 100644 index d4d66d65225bc9d1d4d62f45550db71fb5d8414e..0000000000000000000000000000000000000000 --- a/deploy/cpp_infer/tools/config.txt +++ /dev/null @@ -1,31 +0,0 @@ -# model load config -use_gpu 0 -gpu_id 0 -gpu_mem 4000 -cpu_math_library_num_threads 10 -use_mkldnn 0 - -# det config -max_side_len 960 -det_db_thresh 0.3 -det_db_box_thresh 0.5 -det_db_unclip_ratio 1.6 -use_polygon_score 1 -det_model_dir ./inference/ch_ppocr_mobile_v2.0_det_infer/ - -# cls config -use_angle_cls 0 -cls_model_dir ./inference/ch_ppocr_mobile_v2.0_cls_infer/ -cls_thresh 0.9 - -# rec config -rec_model_dir ./inference/ch_ppocr_mobile_v2.0_rec_infer/ -char_list_file ../../ppocr/utils/ppocr_keys_v1.txt - -# show the detection results -visualize 0 - -# use_tensorrt -use_tensorrt 0 -use_fp16 0 - diff --git a/deploy/cpp_infer/tools/run.sh b/deploy/cpp_infer/tools/run.sh deleted file mode 100755 index fa61da75e3a71262f539ee348c69fb82ed2574fb..0000000000000000000000000000000000000000 --- a/deploy/cpp_infer/tools/run.sh +++ /dev/null @@ -1,2 +0,0 @@ - -./build/ocr_system ./tools/config.txt ../../doc/imgs/12.jpg