add config

deploy/cpp_infer/CMakeLists.txt

@@ -57,7 +57,8 @@ link_directories("${PADDLE_LIB}/third_party/install/xxhash/lib")
 link_directories("${PADDLE_LIB}/paddle/lib")
 
 
-add_executable(${DEMO_NAME} src/main.cpp src/ocr_det.cpp src/ocr_rec.cpp src/preprocess_op.cpp src/clipper.cpp src/postprocess_op.cpp )
+AUX_SOURCE_DIRECTORY(./src SRCS)
+add_executable(${DEMO_NAME} ${SRCS})
 
 if(WITH_MKL)
   include_directories("${PADDLE_LIB}/third_party/install/mklml/include")
@@ -81,9 +82,6 @@ else()
       ${PADDLE_LIB}/paddle/lib/libpaddle_fluid${CMAKE_SHARED_LIBRARY_SUFFIX})
 endif()
 
-# user ze
-# set(EXTERNAL_LIB "-lrt -ldl -lpthread -lm -lopencv_world")
-# gry
 set(EXTERNAL_LIB "-lrt -ldl -lpthread -lm")
 
 set(DEPS ${DEPS}

deploy/cpp_infer/include/config.h

+// 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.
+
+#pragma once
+
+#include <iomanip>
+#include <iostream>
+#include <map>
+#include <ostream>
+#include <string>
+#include <vector>
+
+#include "include/utility.h"
+
+namespace PaddleOCR {
+
+class Config {
+public:
+  explicit Config(const std::string &config_file) {
+    config_map_ = LoadConfig(config_file);
+
+    this->use_gpu = bool(stoi(config_map_["use_gpu"]));
+
+    this->gpu_id = stoi(config_map_["gpu_id"]);
+
+    this->gpu_mem = stoi(config_map_["gpu_mem"]);
+
+    this->cpu_math_library_num_threads =
+        stoi(config_map_["cpu_math_library_num_threads"]);
+
+    this->max_side_len = stoi(config_map_["max_side_len"]);
+
+    this->det_db_thresh = stod(config_map_["det_db_thresh"]);
+
+    this->det_db_box_thresh = stod(config_map_["det_db_box_thresh"]);
+
+    this->det_db_box_thresh = stod(config_map_["det_db_box_thresh"]);
+
+    this->det_model_dir.assign(config_map_["det_model_dir"]);
+
+    this->rec_model_dir.assign(config_map_["rec_model_dir"]);
+
+    this->char_list_file.assign(config_map_["char_list_file"]);
+  }
+
+  bool use_gpu = false;
+
+  int gpu_id = 0;
+
+  int gpu_mem = 4000;
+
+  int cpu_math_library_num_threads = 1;
+
+  int max_side_len = 960;
+
+  double det_db_thresh = 0.3;
+
+  double det_db_box_thresh = 0.5;
+
+  double det_db_unclip_ratio = 2.0;
+
+  std::string det_model_dir;
+
+  std::string rec_model_dir;
+
+  std::string char_list_file;
+
+  void PrintConfigInfo();
+
+private:
+  // Load configuration
+  std::map<std::string, std::string> LoadConfig(const std::string &config_file);
+
+  std::vector<std::string> split(const std::string &str,
+                                 const std::string &delim);
+
+  std::map<std::string, std::string> config_map_;
+};
+
+} // namespace PaddleOCR

deploy/cpp_infer/include/ocr_det.h

@@ -36,16 +36,29 @@ namespace PaddleOCR {
 
 class DBDetector {
 public:
-  explicit DBDetector(const std::string &model_dir, bool use_gpu = false,
-                      const int gpu_id = 0, const int max_side_len = 960) {
-    LoadModel(model_dir, use_gpu);
+  explicit DBDetector(const std::string &model_dir, const bool &use_gpu = false,
+                      const int &gpu_id = 0, const int &gpu_mem = 4000,
+                      const int &cpu_math_library_num_threads = 4,
+                      const int &max_side_len = 960,
+                      const double &det_db_thresh = 0.3,
+                      const double &det_db_box_thresh = 0.5,
+                      const double &det_db_unclip_ratio = 2.0) {
+    LoadModel(model_dir);
+
+    this->use_gpu_ = use_gpu;
+    this->gpu_id_ = gpu_id;
+    this->gpu_mem_ = gpu_mem;
+    this->cpu_math_library_num_threads_ = cpu_math_library_num_threads;
+
     this->max_side_len_ = max_side_len;
+
+    this->det_db_thresh_ = det_db_thresh;
+    this->det_db_box_thresh_ = det_db_box_thresh;
+    this->det_db_unclip_ratio_ = det_db_unclip_ratio;
   }
 
   // Load Paddle inference model
-  void LoadModel(const std::string &model_dir, bool use_gpu,
-                 const int min_subgraph_size = 3, const int batch_size = 1,
-                 const int gpu_id = 0);
+  void LoadModel(const std::string &model_dir);
 
   // Run predictor
   void Run(cv::Mat &img, std::vector<std::vector<std::vector<int>>> &boxes);
@@ -53,8 +66,17 @@ public:
 private:
   std::shared_ptr<PaddlePredictor> predictor_;
 
+  bool use_gpu_ = false;
+  int gpu_id_ = 0;
+  int gpu_mem_ = 4000;
+  int cpu_math_library_num_threads_ = 4;
+
   int max_side_len_ = 960;
 
+  double det_db_thresh_ = 0.3;
+  double det_db_box_thresh_ = 0.5;
+  double det_db_unclip_ratio_ = 2.0;
+
   std::vector<float> mean_ = {0.485f, 0.456f, 0.406f};
   std::vector<float> scale_ = {1 / 0.229f, 1 / 0.224f, 1 / 0.225f};
   bool is_scale_ = true;

deploy/cpp_infer/include/ocr_rec.h

@@ -29,29 +29,40 @@
 
 #include <include/postprocess_op.h>
 #include <include/preprocess_op.h>
+#include <include/utility.h>
 
 namespace PaddleOCR {
 
 class CRNNRecognizer {
 public:
-  explicit CRNNRecognizer(const std::string &model_dir,
-                          const string label_path = "./tools/ppocr_keys_v1.txt",
-                          bool use_gpu = false, const int gpu_id = 0) {
-    LoadModel(model_dir, use_gpu);
-
-    this->label_list_ = ReadDict(label_path);
+  explicit CRNNRecognizer(
+      const std::string &model_dir, const bool &use_gpu = false,
+      const int &gpu_id = 0, const int &gpu_mem = 4000,
+      const int &cpu_math_library_num_threads = 4,
+      const string &label_path = "./tools/ppocr_keys_v1.txt") {
+    LoadModel(model_dir);
+
+    this->use_gpu_ = use_gpu;
+    this->gpu_id_ = gpu_id;
+    this->gpu_mem_ = gpu_mem;
+    this->cpu_math_library_num_threads_ = cpu_math_library_num_threads;
+
+    this->label_list_ = Utility::ReadDict(label_path);
   }
 
   // Load Paddle inference model
-  void LoadModel(const std::string &model_dir, bool use_gpu,
-                 const int gpu_id = 0, const int min_subgraph_size = 3,
-                 const int batch_size = 1);
+  void LoadModel(const std::string &model_dir);
 
   void Run(std::vector<std::vector<std::vector<int>>> boxes, cv::Mat &img);
 
 private:
   std::shared_ptr<PaddlePredictor> predictor_;
 
+  bool use_gpu_ = false;
+  int gpu_id_ = 0;
+  int gpu_mem_ = 4000;
+  int cpu_math_library_num_threads_ = 4;
+
   std::vector<std::string> label_list_;
 
   std::vector<float> mean_ = {0.5f, 0.5f, 0.5f};
@@ -66,15 +77,8 @@ private:
   // post-process
   PostProcessor post_processor_;
 
-  cv::Mat get_rotate_crop_image(const cv::Mat &srcimage,
-                                std::vector<std::vector<int>> box);
-
-  std::vector<std::string> ReadDict(const std::string &path);
-
-  template <class ForwardIterator>
-  inline size_t argmax(ForwardIterator first, ForwardIterator last) {
-    return std::distance(first, std::max_element(first, last));
-  }
+  cv::Mat GetRotateCropImage(const cv::Mat &srcimage,
+                             std::vector<std::vector<int>> box);
 
 }; // class CrnnRecognizer
 

deploy/cpp_infer/include/postprocess_op.h

@@ -28,36 +28,17 @@
 #include <numeric>
 
 #include "include/clipper.h"
+#include "include/utility.h"
 
 using namespace std;
 
 namespace PaddleOCR {
 
-inline std::vector<std::string> ReadDict(std::string path) {
-  std::ifstream in(path);
-  std::string filename;
-  std::string line;
-  std::vector<std::string> m_vec;
-  if (in) {
-    while (getline(in, line)) {
-      m_vec.push_back(line);
-    }
-  } else {
-    std::cout << "no such file" << std::endl;
-  }
-  return m_vec;
-}
-
-template <class ForwardIterator>
-inline size_t Argmax(ForwardIterator first, ForwardIterator last) {
-  return std::distance(first, std::max_element(first, last));
-}
-
 class PostProcessor {
 public:
   void GetContourArea(float **box, float unclip_ratio, float &distance);
 
-  cv::RotatedRect unclip(float **box);
+  cv::RotatedRect UnClip(float **box, const float &unclip_ratio);
 
   float **Mat2Vec(cv::Mat mat);
 
@@ -67,23 +48,17 @@ public:
   std::vector<std::vector<int>>
   order_points_clockwise(std::vector<std::vector<int>> pts);
 
-  float **get_mini_boxes(cv::RotatedRect box, float &ssid);
+  float **GetMiniBoxes(cv::RotatedRect box, float &ssid);
 
-  float box_score_fast(float **box_array, cv::Mat pred);
+  float BoxScoreFast(float **box_array, cv::Mat pred);
 
   std::vector<std::vector<std::vector<int>>>
-  boxes_from_bitmap(const cv::Mat pred, const cv::Mat bitmap);
+  BoxesFromBitmap(const cv::Mat pred, const cv::Mat bitmap,
+                  const float &box_thresh, const float &det_db_unclip_ratio);
 
   std::vector<std::vector<std::vector<int>>>
-  filter_tag_det_res(std::vector<std::vector<std::vector<int>>> boxes,
-                     float ratio_h, float ratio_w, cv::Mat srcimg);
-
-  template <class ForwardIterator>
-  inline size_t argmax(ForwardIterator first, ForwardIterator last) {
-    return std::distance(first, std::max_element(first, last));
-  }
-
-  // CRNN
+  FilterTagDetRes(std::vector<std::vector<std::vector<int>>> boxes,
+                  float ratio_h, float ratio_w, cv::Mat srcimg);
 
 private:
   void quickSort(float **s, int l, int r);
@@ -99,6 +74,7 @@ private:
       return min;
     return x;
   }
+
   inline float clampf(float x, float min, float max) {
     if (x > max)
       return max;
@@ -108,4 +84,4 @@ private:
   }
 };
 
-} // namespace PaddleOCR
+} // namespace PaddleOCR
\ No newline at end of file

deploy/cpp_infer/include/preprocess_op.h

@@ -44,7 +44,6 @@ public:
   virtual void Run(const cv::Mat *im, float *data);
 };
 
-// RGB -> CHW
 class ResizeImgType0 {
 public:
   virtual void Run(const cv::Mat &img, cv::Mat &resize_img, int max_size_len,
@@ -54,7 +53,7 @@ public:
 class CrnnResizeImg {
 public:
   virtual void Run(const cv::Mat &img, cv::Mat &resize_img, float wh_ratio,
-                   const std::vector<int> rec_image_shape = {3, 32, 320});
+                   const std::vector<int> &rec_image_shape = {3, 32, 320});
 };
 
 } // namespace PaddleOCR
\ No newline at end of file

deploy/cpp_infer/include/utility.h

+// 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.
+
+#pragma once
+
+#include <chrono>
+#include <iomanip>
+#include <iostream>
+#include <ostream>
+#include <stdlib.h>
+#include <vector>
+
+#include <algorithm>
+#include <cstring>
+#include <fstream>
+#include <numeric>
+
+namespace PaddleOCR {
+
+class Utility {
+public:
+  static std::vector<std::string> ReadDict(const std::string &path);
+
+  template <class ForwardIterator>
+  inline static size_t argmax(ForwardIterator first, ForwardIterator last) {
+    return std::distance(first, std::max_element(first, last));
+  }
+};
+
+} // namespace PaddleOCR
\ No newline at end of file

deploy/cpp_infer/src/config.cpp

+// 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/config.h>
+
+namespace PaddleOCR {
+
+std::vector<std::string> Config::split(const std::string &str,
+                                       const std::string &delim) {
+  std::vector<std::string> res;
+  if ("" == str)
+    return res;
+  char *strs = new char[str.length() + 1];
+  std::strcpy(strs, str.c_str());
+
+  char *d = new char[delim.length() + 1];
+  std::strcpy(d, delim.c_str());
+
+  char *p = std::strtok(strs, d);
+  while (p) {
+    std::string s = p;
+    res.push_back(s);
+    p = std::strtok(NULL, d);
+  }
+
+  return res;
+}
+
+std::map<std::string, std::string>
+Config::LoadConfig(const std::string &config_path) {
+  auto config = Utility::ReadDict(config_path);
+
+  std::map<std::string, std::string> dict;
+  for (int i = 0; i < config.size(); i++) {
+    // pass for empty line or comment
+    if (config[i].size() <= 1 or config[i][0] == '#') {
+      continue;
+    }
+    std::vector<std::string> res = split(config[i], " ");
+    dict[res[0]] = res[1];
+  }
+  return dict;
+}
+
+void Config::PrintConfigInfo() {
+  std::cout << "=======Paddle OCR inference config======" << std::endl;
+  for (auto iter = config_map_.begin(); iter != config_map_.end(); iter++) {
+    std::cout << iter->first << " : " << iter->second << std::endl;
+  }
+  std::cout << "=======End of Paddle OCR inference config======" << std::endl;
+}
+
+} // namespace PaddleOCR
\ No newline at end of file

deploy/cpp_infer/src/main.cpp

@@ -25,6 +25,7 @@
 #include <fstream>
 #include <numeric>
 
+#include <include/config.h>
 #include <include/ocr_det.h>
 #include <include/ocr_rec.h>
 
@@ -33,21 +34,29 @@ using namespace cv;
 using namespace PaddleOCR;
 
 int main(int argc, char **argv) {
-  if (argc < 4) {
+  if (argc < 3) {
     std::cerr << "[ERROR] usage: " << argv[0]
-              << " det_model_file rec_model_file image_path\n";
+              << " configure_filepath image_path\n";
     exit(1);
   }
-  std::string det_model_file = argv[1];
-  std::string rec_model_file = argv[2];
-  std::string img_path = argv[3];
+
+  Config config(argv[1]);
+
+  config.PrintConfigInfo();
+
+  std::string img_path(argv[2]);
 
   auto start = std::chrono::system_clock::now();
 
   cv::Mat srcimg = cv::imread(img_path, cv::IMREAD_COLOR);
 
-  DBDetector det(det_model_file);
-  CRNNRecognizer rec(rec_model_file);
+  DBDetector det(config.det_model_dir, config.use_gpu, config.gpu_id,
+                 config.gpu_mem, config.cpu_math_library_num_threads,
+                 config.max_side_len, config.det_db_thresh,
+                 config.det_db_box_thresh, config.det_db_unclip_ratio);
+  CRNNRecognizer rec(config.rec_model_dir, config.use_gpu, config.gpu_id,
+                     config.gpu_mem, config.cpu_math_library_num_threads,
+                     config.char_list_file);
 
   std::vector<std::vector<std::vector<int>>> boxes;
   det.Run(srcimg, boxes);

deploy/cpp_infer/src/ocr_det.cpp

@@ -31,29 +31,28 @@
 
 namespace PaddleOCR {
 
-void DBDetector::LoadModel(const std::string &model_dir, bool use_gpu,
-                           const int gpu_id, const int min_subgraph_size,
-                           const int batch_size) {
+void DBDetector::LoadModel(const std::string &model_dir) {
   AnalysisConfig config;
   config.SetModel(model_dir + "/model", model_dir + "/params");
 
-  // for cpu
-  config.DisableGpu();
-  config.EnableMKLDNN(); // 开启MKLDNN加速
-  config.SetCpuMathLibraryNumThreads(10);
+  if (this->use_gpu_) {
+    config.EnableUseGpu(this->gpu_mem_, this->gpu_id_);
+  } else {
+    config.DisableGpu();
+    config.EnableMKLDNN(); // 开启MKLDNN加速
+    config.SetCpuMathLibraryNumThreads(this->cpu_math_library_num_threads_);
+  }
 
-  // 使用ZeroCopyTensor，此处必须设置为false
+  // false for zero copy tensor
   config.SwitchUseFeedFetchOps(false);
-  // 若输入为多个，此处必须设置为true
+  // true for multiple input
   config.SwitchSpecifyInputNames(true);
-  // config.SwitchIrDebug(true); //
-  // 可视化调试选项，若开启，则会在每个图优化过程后生成dot文件
-  // config.SwitchIrOptim(false);// 默认为true。如果设置为false，关闭所有优化
-  config.EnableMemoryOptim(); // 开启内存/显存复用
+
+  config.SwitchIrOptim(true);
+
+  config.EnableMemoryOptim();
 
   this->predictor_ = CreatePaddlePredictor(config);
-  //   predictor_ = std::move(CreatePaddlePredictor(config)); // PaddleDetection
-  //   usage
 }
 
 void DBDetector::Run(cv::Mat &img,
@@ -69,13 +68,13 @@ void DBDetector::Run(cv::Mat &img,
   this->normalize_op_.Run(&resize_img, this->mean_, this->scale_,
                           this->is_scale_);
 
-  float *input = new float[1 * 3 * resize_img.rows * resize_img.cols];
-  this->permute_op_.Run(&resize_img, input);
+  std::vector<float> input(1 * 3 * resize_img.rows * resize_img.cols, 0.0f);
+  this->permute_op_.Run(&resize_img, input.data());
 
   auto input_names = this->predictor_->GetInputNames();
   auto input_t = this->predictor_->GetInputTensor(input_names[0]);
   input_t->Reshape({1, 3, resize_img.rows, resize_img.cols});
-  input_t->copy_from_cpu(input);
+  input_t->copy_from_cpu(input.data());
 
   this->predictor_->ZeroCopyRun();
 
@@ -93,25 +92,26 @@ void DBDetector::Run(cv::Mat &img,
   int n3 = output_shape[3];
   int n = n2 * n3;
 
-  float *pred = new float[n];
-  unsigned char *cbuf = new unsigned char[n];
+  std::vector<float> pred(n, 0.0);
+  std::vector<unsigned char> 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);
-  cv::Mat pred_map(n2, n3, CV_32F, (float *)pred);
+  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 = 0.3 * 255;
+  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);
 
-  boxes = post_processor_.boxes_from_bitmap(pred_map, bit_map);
+  boxes = post_processor_.BoxesFromBitmap(
+      pred_map, bit_map, this->det_db_box_thresh_, this->det_db_unclip_ratio_);
 
-  boxes = post_processor_.filter_tag_det_res(boxes, ratio_h, ratio_w, srcimg);
+  boxes = post_processor_.FilterTagDetRes(boxes, ratio_h, ratio_w, srcimg);
 
   //// visualization
   cv::Point rook_points[boxes.size()][4];
@@ -133,10 +133,6 @@ void DBDetector::Run(cv::Mat &img,
 
   std::cout << "The detection visualized image saved in ./det_res.png"
             << std::endl;
-
-  delete[] input;
-  delete[] pred;
-  delete[] cbuf;
 }
 
 } // namespace PaddleOCR
\ No newline at end of file

deploy/cpp_infer/src/ocr_rec.cpp

@@ -41,7 +41,7 @@ void CRNNRecognizer::Run(std::vector<std::vector<std::vector<int>>> boxes,
   std::cout << "The predicted text is :" << std::endl;
   int index = 0;
   for (int i = boxes.size() - 1; i >= 0; i--) {
-    crop_img = get_rotate_crop_image(srcimg, boxes[i]);
+    crop_img = GetRotateCropImage(srcimg, boxes[i]);
 
     float wh_ratio = float(crop_img.cols) / float(crop_img.rows);
 
@@ -50,14 +50,14 @@ void CRNNRecognizer::Run(std::vector<std::vector<std::vector<int>>> boxes,
     this->normalize_op_.Run(&resize_img, this->mean_, this->scale_,
                             this->is_scale_);
 
-    float *input = new float[1 * 3 * resize_img.rows * resize_img.cols];
+    std::vector<float> input(1 * 3 * resize_img.rows * resize_img.cols, 0.0f);
 
-    this->permute_op_.Run(&resize_img, input);
+    this->permute_op_.Run(&resize_img, input.data());
 
     auto input_names = this->predictor_->GetInputNames();
     auto input_t = this->predictor_->GetInputTensor(input_names[0]);
     input_t->Reshape({1, 3, resize_img.rows, resize_img.cols});
-    input_t->copy_from_cpu(input);
+    input_t->copy_from_cpu(input.data());
 
     this->predictor_->ZeroCopyRun();
 
@@ -104,7 +104,8 @@ void CRNNRecognizer::Run(std::vector<std::vector<std::vector<int>>> boxes,
     float max_value = 0.0f;
 
     for (int n = predict_lod[0][0]; n < predict_lod[0][1] - 1; n++) {
-      argmax_idx = int(argmax(&predict_batch[n * predict_shape[1]],
+      argmax_idx =
+          int(Utility::argmax(&predict_batch[n * predict_shape[1]],
                               &predict_batch[(n + 1) * predict_shape[1]]));
       max_value =
           float(*std::max_element(&predict_batch[n * predict_shape[1]],
@@ -116,37 +117,35 @@ void CRNNRecognizer::Run(std::vector<std::vector<std::vector<int>>> boxes,
     }
     score /= count;
     std::cout << "\tscore: " << score << std::endl;
-
-    delete[] input;
   }
 }
 
-void CRNNRecognizer::LoadModel(const std::string &model_dir, bool use_gpu,
-                               const int gpu_id, const int min_subgraph_size,
-                               const int batch_size) {
+void CRNNRecognizer::LoadModel(const std::string &model_dir) {
   AnalysisConfig config;
   config.SetModel(model_dir + "/model", model_dir + "/params");
 
-  // for cpu
-  config.DisableGpu();
-  config.EnableMKLDNN(); // 开启MKLDNN加速
-  config.SetCpuMathLibraryNumThreads(10);
+  if (this->use_gpu_) {
+    config.EnableUseGpu(this->gpu_mem_, this->gpu_id_);
+  } else {
+    config.DisableGpu();
+    config.EnableMKLDNN(); // 开启MKLDNN加速
+    config.SetCpuMathLibraryNumThreads(this->cpu_math_library_num_threads_);
+  }
 
-  // 使用ZeroCopyTensor，此处必须设置为false
+  // false for zero copy tensor
   config.SwitchUseFeedFetchOps(false);
-  // 若输入为多个，此处必须设置为true
+  // true for multiple input
   config.SwitchSpecifyInputNames(true);
-  // config.SwitchIrDebug(true); //
-  // 可视化调试选项，若开启，则会在每个图优化过程后生成dot文件
-  // config.SwitchIrOptim(false);// 默认为true。如果设置为false，关闭所有优化
-  config.EnableMemoryOptim(); // 开启内存/显存复用
+
+  config.SwitchIrOptim(true);
+
+  config.EnableMemoryOptim();
 
   this->predictor_ = CreatePaddlePredictor(config);
 }
 
-cv::Mat
-CRNNRecognizer::get_rotate_crop_image(const cv::Mat &srcimage,
-                                      std::vector<std::vector<int>> box) {
+cv::Mat CRNNRecognizer::GetRotateCropImage(const cv::Mat &srcimage,
+                                           std::vector<std::vector<int>> box) {
   cv::Mat image;
   srcimage.copyTo(image);
   std::vector<std::vector<int>> points = box;
@@ -200,19 +199,4 @@ CRNNRecognizer::get_rotate_crop_image(const cv::Mat &srcimage,
   }
 }
 
-std::vector<std::string> CRNNRecognizer::ReadDict(const std::string &path) {
-  std::ifstream in(path);
-  std::string filename;
-  std::string line;
-  std::vector<std::string> m_vec;
-  if (in) {
-    while (getline(in, line)) {
-      m_vec.push_back(line);
-    }
-  } else {
-    std::cout << "no such file" << std::endl;
-  }
-  return m_vec;
-}
-
 } // namespace PaddleOCR
\ No newline at end of file

deploy/cpp_infer/src/postprocess_op.cpp

@@ -34,8 +34,7 @@ void PostProcessor::GetContourArea(float **box, float unclip_ratio,
   distance = area * unclip_ratio / dist;
 }
 
-cv::RotatedRect PostProcessor::unclip(float **box) {
-  float unclip_ratio = 2.0;
+cv::RotatedRect PostProcessor::UnClip(float **box, const float &unclip_ratio) {
   float distance = 1.0;
 
   GetContourArea(box, unclip_ratio, distance);
@@ -136,7 +135,7 @@ PostProcessor::order_points_clockwise(std::vector<std::vector<int>> pts) {
   return rect;
 }
 
-float **PostProcessor::get_mini_boxes(cv::RotatedRect box, float &ssid) {
+float **PostProcessor::GetMiniBoxes(cv::RotatedRect box, float &ssid) {
   ssid = box.size.width >= box.size.height ? box.size.height : box.size.width;
 
   cv::Mat points;
@@ -169,7 +168,7 @@ float **PostProcessor::get_mini_boxes(cv::RotatedRect box, float &ssid) {
   return array;
 }
 
-float PostProcessor::box_score_fast(float **box_array, cv::Mat pred) {
+float PostProcessor::BoxScoreFast(float **box_array, cv::Mat pred) {
   auto array = box_array;
   int width = pred.cols;
   int height = pred.rows;
@@ -207,10 +206,11 @@ float PostProcessor::box_score_fast(float **box_array, cv::Mat pred) {
 }
 
 std::vector<std::vector<std::vector<int>>>
-PostProcessor::boxes_from_bitmap(const cv::Mat pred, const cv::Mat bitmap) {
+PostProcessor::BoxesFromBitmap(const cv::Mat pred, const cv::Mat bitmap,
+                               const float &box_thresh,
+                               const float &det_db_unclip_ratio) {
   const int min_size = 3;
   const int max_candidates = 1000;
-  const float box_thresh = 0.5;
 
   int width = bitmap.cols;
   int height = bitmap.rows;
@@ -229,7 +229,7 @@ PostProcessor::boxes_from_bitmap(const cv::Mat pred, const cv::Mat bitmap) {
   for (int _i = 0; _i < num_contours; _i++) {
     float ssid;
     cv::RotatedRect box = cv::minAreaRect(contours[_i]);
-    auto array = get_mini_boxes(box, ssid);
+    auto array = GetMiniBoxes(box, ssid);
 
     auto box_for_unclip = array;
     // end get_mini_box
@@ -239,17 +239,16 @@ PostProcessor::boxes_from_bitmap(const cv::Mat pred, const cv::Mat bitmap) {
     }
 
     float score;
-    score = box_score_fast(array, pred);
-    // end box_score_fast
+    score = BoxScoreFast(array, pred);
     if (score < box_thresh)
       continue;
 
     // start for unclip
-    cv::RotatedRect points = unclip(box_for_unclip);
+    cv::RotatedRect points = UnClip(box_for_unclip, det_db_unclip_ratio);
     // end for unclip
 
     cv::RotatedRect clipbox = points;
-    auto cliparray = get_mini_boxes(clipbox, ssid);
+    auto cliparray = GetMiniBoxes(clipbox, ssid);
 
     if (ssid < min_size + 2)
       continue;
@@ -273,9 +272,9 @@ PostProcessor::boxes_from_bitmap(const cv::Mat pred, const cv::Mat bitmap) {
   return boxes;
 }
 
-std::vector<std::vector<std::vector<int>>> PostProcessor::filter_tag_det_res(
-    std::vector<std::vector<std::vector<int>>> boxes, float ratio_h,
-    float ratio_w, cv::Mat srcimg) {
+std::vector<std::vector<std::vector<int>>>
+PostProcessor::FilterTagDetRes(std::vector<std::vector<std::vector<int>>> boxes,
+                               float ratio_h, float ratio_w, cv::Mat srcimg) {
   int oriimg_h = srcimg.rows;
   int oriimg_w = srcimg.cols;
 

deploy/cpp_infer/src/preprocess_op.cpp

@@ -97,7 +97,7 @@ void ResizeImgType0::Run(const cv::Mat &img, cv::Mat &resize_img,
 }
 
 void CrnnResizeImg::Run(const cv::Mat &img, cv::Mat &resize_img, float wh_ratio,
-                        const std::vector<int> rec_image_shape) {
+                        const std::vector<int> &rec_image_shape) {
   int imgC, imgH, imgW;
   imgC = rec_image_shape[0];
   imgH = rec_image_shape[1];

deploy/cpp_infer/src/utility.cpp

+// 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 <iostream>
+#include <ostream>
+#include <vector>
+
+#include <include/utility.h>
+
+namespace PaddleOCR {
+
+std::vector<std::string> Utility::ReadDict(const std::string &path) {
+  std::ifstream in(path);
+  std::string line;
+  std::vector<std::string> m_vec;
+  if (in) {
+    while (getline(in, line)) {
+      m_vec.push_back(line);
+    }
+  } else {
+    std::cout << "no such label file: " << path << ", exit the program..."
+              << std::endl;
+    exit(1);
+  }
+  return m_vec;
+}
+
+} // namespace PaddleOCR
\ No newline at end of file

deploy/cpp_infer/tools/config.txt

+# model load config
+use_gpu  0
+gpu_id  0
+gpu_mem  4000
+cpu_math_library_num_threads  1
+
+# det config
+max_side_len  960
+det_db_thresh  0.3
+det_db_box_thresh  0.5
+det_db_unclip_ratio  2.0
+det_model_dir  ./inference/det_db
+
+# rec config
+rec_model_dir  ./inference/rec_crnn
+char_list_file ./tools/ppocr_keys_v1.txt
+img_path  ../../doc/imgs/11.jpg

deploy/cpp_infer/tools/run.sh

 
-./build/ocr_system ./inference/det_db/ ./inference/rec_crnn/ ../../doc/imgs/12.jpg
+./build/ocr_system ./tools/config.txt ../../doc/imgs/6.jpg