fix bug

deploy/cpp_infer/include/ocr_cls.h

@@ -14,26 +14,12 @@
 
 #pragma once
 
-#include "opencv2/core.hpp"
-#include "opencv2/imgcodecs.hpp"
-#include "opencv2/imgproc.hpp"
 #include "paddle_api.h"
 #include "paddle_inference_api.h"
-#include <chrono>
-#include <iomanip>
-#include <iostream>
-#include <ostream>
-#include <vector>
-
-#include <cstring>
-#include <fstream>
-#include <numeric>
 
 #include <include/preprocess_op.h>
 #include <include/utility.h>
 
-using namespace paddle_infer;
-
 namespace PaddleOCR {
 
 class Classifier {
@@ -66,7 +52,7 @@ public:
            std::vector<float> &cls_scores, std::vector<double> &times);
 
 private:
-  std::shared_ptr<Predictor> predictor_;
+  std::shared_ptr<paddle_infer::Predictor> predictor_;
 
   bool use_gpu_ = false;
   int gpu_id_ = 0;

deploy/cpp_infer/include/ocr_det.h

@@ -14,26 +14,12 @@
 
 #pragma once
 
-#include "opencv2/core.hpp"
-#include "opencv2/imgcodecs.hpp"
-#include "opencv2/imgproc.hpp"
 #include "paddle_api.h"
 #include "paddle_inference_api.h"
-#include <chrono>
-#include <iomanip>
-#include <iostream>
-#include <ostream>
-#include <vector>
-
-#include <cstring>
-#include <fstream>
-#include <numeric>
 
 #include <include/postprocess_op.h>
 #include <include/preprocess_op.h>
 
-using namespace paddle_infer;
-
 namespace PaddleOCR {
 
 class DBDetector {
@@ -41,7 +27,7 @@ public:
   explicit DBDetector(const std::string &model_dir, const bool &use_gpu,
                       const int &gpu_id, const int &gpu_mem,
                       const int &cpu_math_library_num_threads,
-                      const bool &use_mkldnn, const string &limit_type,
+                      const bool &use_mkldnn, const std::string &limit_type,
                       const int &limit_side_len, const double &det_db_thresh,
                       const double &det_db_box_thresh,
                       const double &det_db_unclip_ratio,
@@ -77,7 +63,7 @@ public:
            std::vector<double> &times);
 
 private:
-  std::shared_ptr<Predictor> predictor_;
+  std::shared_ptr<paddle_infer::Predictor> predictor_;
 
   bool use_gpu_ = false;
   int gpu_id_ = 0;
@@ -85,7 +71,7 @@ private:
   int cpu_math_library_num_threads_ = 4;
   bool use_mkldnn_ = false;
 
-  string limit_type_ = "max";
+  std::string limit_type_ = "max";
   int limit_side_len_ = 960;
 
   double det_db_thresh_ = 0.3;

deploy/cpp_infer/include/ocr_rec.h

@@ -14,27 +14,12 @@
 
 #pragma once
 
-#include "opencv2/core.hpp"
-#include "opencv2/imgcodecs.hpp"
-#include "opencv2/imgproc.hpp"
 #include "paddle_api.h"
 #include "paddle_inference_api.h"
-#include <chrono>
-#include <iomanip>
-#include <iostream>
-#include <ostream>
-#include <vector>
-
-#include <cstring>
-#include <fstream>
-#include <numeric>
 
 #include <include/ocr_cls.h>
-#include <include/preprocess_op.h>
 #include <include/utility.h>
 
-using namespace paddle_infer;
-
 namespace PaddleOCR {
 
 class CRNNRecognizer {
@@ -42,7 +27,7 @@ public:
   explicit CRNNRecognizer(const std::string &model_dir, const bool &use_gpu,
                           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_mkldnn, const std::string &label_path,
                           const bool &use_tensorrt,
                           const std::string &precision,
                           const int &rec_batch_num, const int &rec_img_h,
@@ -75,7 +60,7 @@ public:
            std::vector<float> &rec_text_scores, std::vector<double> &times);
 
 private:
-  std::shared_ptr<Predictor> predictor_;
+  std::shared_ptr<paddle_infer::Predictor> predictor_;
 
   bool use_gpu_ = false;
   int gpu_id_ = 0;

deploy/cpp_infer/include/paddleocr.h

@@ -14,28 +14,9 @@
 
 #pragma once
 
-#include "opencv2/core.hpp"
-#include "opencv2/imgcodecs.hpp"
-#include "opencv2/imgproc.hpp"
-#include "paddle_api.h"
-#include "paddle_inference_api.h"
-#include <chrono>
-#include <iomanip>
-#include <iostream>
-#include <ostream>
-#include <vector>
-
-#include <cstring>
-#include <fstream>
-#include <numeric>
-
 #include <include/ocr_cls.h>
 #include <include/ocr_det.h>
 #include <include/ocr_rec.h>
-#include <include/preprocess_op.h>
-#include <include/utility.h>
-
-using namespace paddle_infer;
 
 namespace PaddleOCR {
 

deploy/cpp_infer/include/paddlestructure.h

@@ -14,28 +14,9 @@
 
 #pragma once
 
-#include "opencv2/core.hpp"
-#include "opencv2/imgcodecs.hpp"
-#include "opencv2/imgproc.hpp"
-#include "paddle_api.h"
-#include "paddle_inference_api.h"
-#include <chrono>
-#include <iomanip>
-#include <iostream>
-#include <ostream>
-#include <vector>
-
-#include <cstring>
-#include <fstream>
-#include <numeric>
-
 #include <include/paddleocr.h>
-#include <include/preprocess_op.h>
 #include <include/structure_layout.h>
 #include <include/structure_table.h>
-#include <include/utility.h>
-
-using namespace paddle_infer;
 
 namespace PaddleOCR {
 

deploy/cpp_infer/include/postprocess_op.h

@@ -14,24 +14,9 @@
 
 #pragma once
 
-#include "opencv2/core.hpp"
-#include "opencv2/imgcodecs.hpp"
-#include "opencv2/imgproc.hpp"
-#include <chrono>
-#include <iomanip>
-#include <iostream>
-#include <ostream>
-#include <vector>
-
-#include <cstring>
-#include <fstream>
-#include <numeric>
-
 #include "include/clipper.h"
 #include "include/utility.h"
 
-using namespace std;
-
 namespace PaddleOCR {
 
 class DBPostProcessor {
@@ -92,23 +77,7 @@ private:
 
 class TablePostProcessor {
 public:
-  void init(std::string label_path, bool merge_no_span_structure = true) {
-    this->label_list_ = Utility::ReadDict(label_path);
-    if (merge_no_span_structure) {
-      this->label_list_.push_back("<td></td>");
-      std::vector<std::string>::iterator it;
-      for (it = this->label_list_.begin(); it != this->label_list_.end();) {
-        if (*it == "<td>") {
-          it = this->label_list_.erase(it);
-        } else {
-          ++it;
-        }
-      }
-    }
-    // add_special_char
-    this->label_list_.insert(this->label_list_.begin(), this->beg);
-    this->label_list_.push_back(this->end);
-  }
+  void init(std::string label_path, bool merge_no_span_structure = true);
   void Run(std::vector<float> &loc_preds, std::vector<float> &structure_probs,
            std::vector<float> &rec_scores, std::vector<int> &loc_preds_shape,
            std::vector<int> &structure_probs_shape,
@@ -126,13 +95,7 @@ class PicodetPostProcessor {
 public:
   void init(std::string label_path, const double score_threshold = 0.4,
             const double nms_threshold = 0.5,
-            const std::vector<int> &fpn_stride = {8, 16, 32, 64}) {
-    this->label_list_ = Utility::ReadDict(label_path);
-    this->score_threshold_ = score_threshold;
-    this->nms_threshold_ = nms_threshold;
-    this->num_class_ = label_list_.size();
-    this->fpn_stride_ = fpn_stride;
-  }
+            const std::vector<int> &fpn_stride = {8, 16, 32, 64});
   void Run(std::vector<StructurePredictResult> &results,
            std::vector<std::vector<float>> outs, std::vector<int> ori_shape,
            std::vector<int> resize_shape, int eg_max);

deploy/cpp_infer/include/preprocess_op.h

@@ -14,21 +14,12 @@
 
 #pragma once
 
-#include "opencv2/core.hpp"
-#include "opencv2/imgcodecs.hpp"
-#include "opencv2/imgproc.hpp"
-#include <chrono>
-#include <iomanip>
 #include <iostream>
-#include <ostream>
 #include <vector>
 
-#include <cstring>
-#include <fstream>
-#include <numeric>
-
-using namespace std;
-using namespace paddle;
+#include "opencv2/core.hpp"
+#include "opencv2/imgcodecs.hpp"
+#include "opencv2/imgproc.hpp"
 
 namespace PaddleOCR {
 
@@ -51,9 +42,9 @@ public:
 
 class ResizeImgType0 {
 public:
-  virtual void Run(const cv::Mat &img, cv::Mat &resize_img, string limit_type,
-                   int limit_side_len, float &ratio_h, float &ratio_w,
-                   bool use_tensorrt);
+  virtual void Run(const cv::Mat &img, cv::Mat &resize_img,
+                   std::string limit_type, int limit_side_len, float &ratio_h,
+                   float &ratio_w, bool use_tensorrt);
 };
 
 class CrnnResizeImg {

deploy/cpp_infer/include/structure_layout.h

@@ -14,26 +14,11 @@
 
 #pragma once
 
-#include "opencv2/core.hpp"
-#include "opencv2/imgcodecs.hpp"
-#include "opencv2/imgproc.hpp"
 #include "paddle_api.h"
 #include "paddle_inference_api.h"
-#include <chrono>
-#include <iomanip>
-#include <iostream>
-#include <ostream>
-#include <vector>
-
-#include <cstring>
-#include <fstream>
-#include <numeric>
 
 #include <include/postprocess_op.h>
 #include <include/preprocess_op.h>
-#include <include/utility.h>
-
-using namespace paddle_infer;
 
 namespace PaddleOCR {
 
@@ -42,7 +27,7 @@ public:
   explicit StructureLayoutRecognizer(
       const std::string &model_dir, const bool &use_gpu, 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_mkldnn, const std::string &label_path,
       const bool &use_tensorrt, const std::string &precision,
       const double &layout_score_threshold,
       const double &layout_nms_threshold) {
@@ -66,7 +51,7 @@ public:
            std::vector<double> &times);
 
 private:
-  std::shared_ptr<Predictor> predictor_;
+  std::shared_ptr<paddle_infer::Predictor> predictor_;
 
   bool use_gpu_ = false;
   int gpu_id_ = 0;

deploy/cpp_infer/include/structure_table.h

@@ -14,26 +14,11 @@
 
 #pragma once
 
-#include "opencv2/core.hpp"
-#include "opencv2/imgcodecs.hpp"
-#include "opencv2/imgproc.hpp"
 #include "paddle_api.h"
 #include "paddle_inference_api.h"
-#include <chrono>
-#include <iomanip>
-#include <iostream>
-#include <ostream>
-#include <vector>
-
-#include <cstring>
-#include <fstream>
-#include <numeric>
 
 #include <include/postprocess_op.h>
 #include <include/preprocess_op.h>
-#include <include/utility.h>
-
-using namespace paddle_infer;
 
 namespace PaddleOCR {
 
@@ -42,7 +27,7 @@ public:
   explicit StructureTableRecognizer(
       const std::string &model_dir, const bool &use_gpu, 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_mkldnn, const std::string &label_path,
       const bool &use_tensorrt, const std::string &precision,
       const int &table_batch_num, const int &table_max_len,
       const bool &merge_no_span_structure) {
@@ -70,7 +55,7 @@ public:
            std::vector<double> &times);
 
 private:
-  std::shared_ptr<Predictor> predictor_;
+  std::shared_ptr<paddle_infer::Predictor> predictor_;
 
   bool use_gpu_ = false;
   int gpu_id_ = 0;

deploy/cpp_infer/include/utility.h

@@ -41,8 +41,7 @@ struct OCRPredictResult {
 };
 
 struct StructurePredictResult {
-  std::vector<int> box;
-  std::vector<float> box_float;
+  std::vector<float> box;
   std::vector<std::vector<int>> cell_box;
   std::string type;
   std::vector<OCRPredictResult> text_res;
@@ -60,7 +59,7 @@ public:
                               const std::string &save_path);
 
   static void VisualizeBboxes(const cv::Mat &srcimg,
-                              StructurePredictResult &structure_result,
+                              const StructurePredictResult &structure_result,
                               const std::string &save_path);
 
   template <class ForwardIterator>
@@ -84,7 +83,8 @@ public:
 
   static void print_result(const std::vector<OCRPredictResult> &ocr_result);
 
-  static cv::Mat crop_image(cv::Mat &img, std::vector<int> &area);
+  static cv::Mat crop_image(cv::Mat &img, const std::vector<int> &area);
+  static cv::Mat crop_image(cv::Mat &img, const std::vector<float> &area);
 
   static void sorted_boxes(std::vector<OCRPredictResult> &ocr_result);
 

deploy/cpp_infer/src/main.cpp

@@ -75,7 +75,8 @@ void check_params() {
   }
   if (FLAGS_precision != "fp32" && FLAGS_precision != "fp16" &&
       FLAGS_precision != "int8") {
-    cout << "precison should be 'fp32'(default), 'fp16' or 'int8'. " << endl;
+    std::cout << "precison should be 'fp32'(default), 'fp16' or 'int8'. "
+              << std::endl;
     exit(1);
   }
 }
@@ -93,7 +94,7 @@ void ocr(std::vector<cv::String> &cv_all_img_names) {
     cv::Mat img = cv::imread(cv_all_img_names[i], cv::IMREAD_COLOR);
     if (!img.data) {
       std::cerr << "[ERROR] image read failed! image path: "
-                << cv_all_img_names[i] << endl;
+                << cv_all_img_names[i] << std::endl;
       continue;
     }
     img_list.push_back(img);
@@ -104,7 +105,7 @@ void ocr(std::vector<cv::String> &cv_all_img_names) {
       ocr.ocr(img_list, FLAGS_det, FLAGS_rec, FLAGS_cls);
 
   for (int i = 0; i < img_names.size(); ++i) {
-    cout << "predict img: " << cv_all_img_names[i] << endl;
+    std::cout << "predict img: " << cv_all_img_names[i] << std::endl;
     Utility::print_result(ocr_results[i]);
     if (FLAGS_visualize && FLAGS_det) {
       std::string file_name = Utility::basename(img_names[i]);
@@ -126,11 +127,11 @@ void structure(std::vector<cv::String> &cv_all_img_names) {
   }
 
   for (int i = 0; i < cv_all_img_names.size(); i++) {
-    cout << "predict img: " << cv_all_img_names[i] << endl;
+    std::cout << "predict img: " << cv_all_img_names[i] << std::endl;
     cv::Mat img = cv::imread(cv_all_img_names[i], cv::IMREAD_COLOR);
     if (!img.data) {
       std::cerr << "[ERROR] image read failed! image path: "
-                << cv_all_img_names[i] << endl;
+                << cv_all_img_names[i] << std::endl;
       continue;
     }
 
@@ -156,14 +157,14 @@ void structure(std::vector<cv::String> &cv_all_img_names) {
                                        "_" + file_name);
         }
       } else {
-        cout << "count of ocr result is : "
-             << structure_results[j].text_res.size() << endl;
+        std::cout << "count of ocr result is : "
+                  << structure_results[j].text_res.size() << std::endl;
         if (structure_results[j].text_res.size() > 0) {
-          cout << "********** print ocr result "
-               << "**********" << endl;
+          std::cout << "********** print ocr result "
+                    << "**********" << std::endl;
           Utility::print_result(structure_results[j].text_res);
-          cout << "********** end print ocr result "
-               << "**********" << endl;
+          std::cout << "********** end print ocr result "
+                    << "**********" << std::endl;
         }
       }
     }
@@ -180,13 +181,13 @@ int main(int argc, char **argv) {
 
   if (!Utility::PathExists(FLAGS_image_dir)) {
     std::cerr << "[ERROR] image path not exist! image_dir: " << FLAGS_image_dir
-              << endl;
+              << std::endl;
     exit(1);
   }
 
   std::vector<cv::String> cv_all_img_names;
   cv::glob(FLAGS_image_dir, cv_all_img_names);
-  std::cout << "total images num: " << cv_all_img_names.size() << endl;
+  std::cout << "total images num: " << cv_all_img_names.size() << std::endl;
 
   if (!Utility::PathExists(FLAGS_output)) {
     Utility::CreateDir(FLAGS_output);
@@ -196,6 +197,6 @@ int main(int argc, char **argv) {
   } else if (FLAGS_type == "structure") {
     structure(cv_all_img_names);
   } else {
-    std::cout << "only value in ['ocr','structure'] is supported" << endl;
+    std::cout << "only value in ['ocr','structure'] is supported" << std::endl;
   }
 }

deploy/cpp_infer/src/ocr_cls.cpp

@@ -32,7 +32,7 @@ void Classifier::Run(std::vector<cv::Mat> img_list,
   for (int beg_img_no = 0; beg_img_no < img_num;
        beg_img_no += this->cls_batch_num_) {
     auto preprocess_start = std::chrono::steady_clock::now();
-    int end_img_no = min(img_num, beg_img_no + this->cls_batch_num_);
+    int end_img_no = std::min(img_num, beg_img_no + this->cls_batch_num_);
     int batch_num = end_img_no - beg_img_no;
     // preprocess
     std::vector<cv::Mat> norm_img_batch;
@@ -97,7 +97,7 @@ void Classifier::Run(std::vector<cv::Mat> img_list,
 }
 
 void Classifier::LoadModel(const std::string &model_dir) {
-  AnalysisConfig config;
+  paddle_infer::Config config;
   config.SetModel(model_dir + "/inference.pdmodel",
                   model_dir + "/inference.pdiparams");
 
@@ -112,9 +112,9 @@ void Classifier::LoadModel(const std::string &model_dir) {
         precision = paddle_infer::Config::Precision::kInt8;
       }
       config.EnableTensorRtEngine(1 << 20, 10, 3, precision, false, false);
-      if (!Utility::PathExists("./trt_cls_shape.txt")){
+      if (!Utility::PathExists("./trt_cls_shape.txt")) {
         config.CollectShapeRangeInfo("./trt_cls_shape.txt");
-      } else { 
+      } else {
         config.EnableTunedTensorRtDynamicShape("./trt_cls_shape.txt", true);
       }
     }
@@ -136,6 +136,6 @@ void Classifier::LoadModel(const std::string &model_dir) {
   config.EnableMemoryOptim();
   config.DisableGlogInfo();
 
-  this->predictor_ = CreatePredictor(config);
+  this->predictor_ = paddle_infer::CreatePredictor(config);
 }
 } // namespace PaddleOCR

deploy/cpp_infer/src/ocr_det.cpp

@@ -33,12 +33,11 @@ void DBDetector::LoadModel(const std::string &model_dir) {
         precision = paddle_infer::Config::Precision::kInt8;
       }
       config.EnableTensorRtEngine(1 << 30, 1, 20, precision, false, false);
-      if (!Utility::PathExists("./trt_det_shape.txt")){
+      if (!Utility::PathExists("./trt_det_shape.txt")) {
         config.CollectShapeRangeInfo("./trt_det_shape.txt");
-      } else { 
+      } else {
         config.EnableTunedTensorRtDynamicShape("./trt_det_shape.txt", true);
       }
-      
     }
   } else {
     config.DisableGpu();
@@ -59,7 +58,7 @@ void DBDetector::LoadModel(const std::string &model_dir) {
   config.EnableMemoryOptim();
   // config.DisableGlogInfo();
 
-  this->predictor_ = CreatePredictor(config);
+  this->predictor_ = paddle_infer::CreatePredictor(config);
 }
 
 void DBDetector::Run(cv::Mat &img,

deploy/cpp_infer/src/ocr_rec.cpp

@@ -37,7 +37,7 @@ void CRNNRecognizer::Run(std::vector<cv::Mat> img_list,
   for (int beg_img_no = 0; beg_img_no < img_num;
        beg_img_no += this->rec_batch_num_) {
     auto preprocess_start = std::chrono::steady_clock::now();
-    int end_img_no = min(img_num, beg_img_no + this->rec_batch_num_);
+    int end_img_no = std::min(img_num, beg_img_no + this->rec_batch_num_);
     int batch_num = end_img_no - beg_img_no;
     int imgH = this->rec_image_shape_[1];
     int imgW = this->rec_image_shape_[2];
@@ -46,7 +46,7 @@ void CRNNRecognizer::Run(std::vector<cv::Mat> img_list,
       int h = img_list[indices[ino]].rows;
       int w = img_list[indices[ino]].cols;
       float wh_ratio = w * 1.0 / h;
-      max_wh_ratio = max(max_wh_ratio, wh_ratio);
+      max_wh_ratio = std::max(max_wh_ratio, wh_ratio);
     }
 
     int batch_width = imgW;
@@ -60,7 +60,7 @@ void CRNNRecognizer::Run(std::vector<cv::Mat> img_list,
       this->normalize_op_.Run(&resize_img, this->mean_, this->scale_,
                               this->is_scale_);
       norm_img_batch.push_back(resize_img);
-      batch_width = max(resize_img.cols, batch_width);
+      batch_width = std::max(resize_img.cols, batch_width);
     }
 
     std::vector<float> input(batch_num * 3 * imgH * batch_width, 0.0f);
@@ -115,7 +115,7 @@ void CRNNRecognizer::Run(std::vector<cv::Mat> img_list,
         last_index = argmax_idx;
       }
       score /= count;
-      if (isnan(score)) {
+      if (std::isnan(score)) {
         continue;
       }
       rec_texts[indices[beg_img_no + m]] = str_res;
@@ -130,7 +130,6 @@ void CRNNRecognizer::Run(std::vector<cv::Mat> img_list,
 }
 
 void CRNNRecognizer::LoadModel(const std::string &model_dir) {
-  //   AnalysisConfig config;
   paddle_infer::Config config;
   config.SetModel(model_dir + "/inference.pdmodel",
                   model_dir + "/inference.pdiparams");
@@ -147,12 +146,11 @@ void CRNNRecognizer::LoadModel(const std::string &model_dir) {
       if (this->precision_ == "int8") {
         precision = paddle_infer::Config::Precision::kInt8;
       }
-      if (!Utility::PathExists("./trt_rec_shape.txt")){
+      if (!Utility::PathExists("./trt_rec_shape.txt")) {
         config.CollectShapeRangeInfo("./trt_rec_shape.txt");
-      } else { 
+      } else {
         config.EnableTunedTensorRtDynamicShape("./trt_rec_shape.txt", true);
       }
-      
     }
   } else {
     config.DisableGpu();
@@ -177,7 +175,7 @@ void CRNNRecognizer::LoadModel(const std::string &model_dir) {
   config.EnableMemoryOptim();
   //   config.DisableGlogInfo();
 
-  this->predictor_ = CreatePredictor(config);
+  this->predictor_ = paddle_infer::CreatePredictor(config);
 }
 
 } // namespace PaddleOCR

deploy/cpp_infer/src/paddleocr.cpp

@@ -16,7 +16,7 @@
 #include <include/paddleocr.h>
 
 #include "auto_log/autolog.h"
-#include <numeric>
+
 namespace PaddleOCR {
 
 PPOCR::PPOCR() {

deploy/cpp_infer/src/paddlestructure.cpp

@@ -16,8 +16,6 @@
 #include <include/paddlestructure.h>
 
 #include "auto_log/autolog.h"
-#include <numeric>
-#include <sys/stat.h>
 
 namespace PaddleOCR {
 
@@ -50,7 +48,7 @@ PaddleStructure::structure(cv::Mat srcimg, bool layout, bool table, bool ocr) {
   } else {
     StructurePredictResult res;
     res.type = "table";
-    res.box = std::vector<int>(4, 0);
+    res.box = std::vector<float>(4, 0.0);
     res.box[2] = img.cols;
     res.box[3] = img.rows;
     structure_results.push_back(res);
@@ -108,10 +106,10 @@ void PaddleStructure::table(cv::Mat img,
     std::vector<int> ocr_box;
     for (int j = 0; j < ocr_result.size(); j++) {
       ocr_box = Utility::xyxyxyxy2xyxy(ocr_result[j].box);
-      ocr_box[0] = max(0, ocr_box[0] - expand_pixel);
-      ocr_box[1] = max(0, ocr_box[1] - expand_pixel),
-      ocr_box[2] = min(img_list[i].cols, ocr_box[2] + expand_pixel);
-      ocr_box[3] = min(img_list[i].rows, ocr_box[3] + expand_pixel);
+      ocr_box[0] = std::max(0, ocr_box[0] - expand_pixel);
+      ocr_box[1] = std::max(0, ocr_box[1] - expand_pixel),
+      ocr_box[2] = std::min(img_list[i].cols, ocr_box[2] + expand_pixel);
+      ocr_box[3] = std::min(img_list[i].rows, ocr_box[3] + expand_pixel);
 
       cv::Mat crop_img = Utility::crop_image(img_list[i], ocr_box);
       rec_img_list.push_back(crop_img);
@@ -132,8 +130,8 @@ PaddleStructure::rebuild_table(std::vector<std::string> structure_html_tags,
                                std::vector<std::vector<int>> structure_boxes,
                                std::vector<OCRPredictResult> &ocr_result) {
   // match text in same cell
-  std::vector<std::vector<string>> matched(structure_boxes.size(),
-                                           std::vector<std::string>());
+  std::vector<std::vector<std::string>> matched(structure_boxes.size(),
+                                                std::vector<std::string>());
 
   std::vector<int> ocr_box;
   std::vector<int> structure_box;
@@ -233,7 +231,7 @@ float PaddleStructure::dis(std::vector<int> &box1, std::vector<int> &box2) {
       abs(x1_2 - x1_1) + abs(y1_2 - y1_1) + abs(x2_2 - x2_1) + abs(y2_2 - y2_1);
   float dis_2 = abs(x1_2 - x1_1) + abs(y1_2 - y1_1);
   float dis_3 = abs(x2_2 - x2_1) + abs(y2_2 - y2_1);
-  return dis + min(dis_2, dis_3);
+  return dis + std::min(dis_2, dis_3);
 }
 
 void PaddleStructure::reset_timer() {

deploy/cpp_infer/src/postprocess_op.cpp

@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include <include/clipper.h>
 #include <include/postprocess_op.h>
 
 namespace PaddleOCR {
@@ -352,6 +351,25 @@ std::vector<std::vector<std::vector<int>>> DBPostProcessor::FilterTagDetRes(
   return root_points;
 }
 
+void TablePostProcessor::init(std::string label_path,
+                              bool merge_no_span_structure) {
+  this->label_list_ = Utility::ReadDict(label_path);
+  if (merge_no_span_structure) {
+    this->label_list_.push_back("<td></td>");
+    std::vector<std::string>::iterator it;
+    for (it = this->label_list_.begin(); it != this->label_list_.end();) {
+      if (*it == "<td>") {
+        it = this->label_list_.erase(it);
+      } else {
+        ++it;
+      }
+    }
+  }
+  // add_special_char
+  this->label_list_.insert(this->label_list_.begin(), this->beg);
+  this->label_list_.push_back(this->end);
+}
+
 void TablePostProcessor::Run(
     std::vector<float> &loc_preds, std::vector<float> &structure_probs,
     std::vector<float> &rec_scores, std::vector<int> &loc_preds_shape,
@@ -412,7 +430,7 @@ void TablePostProcessor::Run(
       }
     }
     score /= count;
-    if (isnan(score) || rec_boxes.size() == 0) {
+    if (std::isnan(score) || rec_boxes.size() == 0) {
       score = -1;
     }
     rec_scores.push_back(score);
@@ -421,6 +439,17 @@ void TablePostProcessor::Run(
   }
 }
 
+void PicodetPostProcessor::init(std::string label_path,
+                                const double score_threshold,
+                                const double nms_threshold,
+                                const std::vector<int> &fpn_stride) {
+  this->label_list_ = Utility::ReadDict(label_path);
+  this->score_threshold_ = score_threshold;
+  this->nms_threshold_ = nms_threshold;
+  this->num_class_ = label_list_.size();
+  this->fpn_stride_ = fpn_stride;
+}
+
 void PicodetPostProcessor::Run(std::vector<StructurePredictResult> &results,
                                std::vector<std::vector<float>> outs,
                                std::vector<int> ori_shape,
@@ -469,12 +498,10 @@ void PicodetPostProcessor::Run(std::vector<StructurePredictResult> &results,
     }
     this->nms(bbox_results[i], this->nms_threshold_);
     for (auto box : bbox_results[i]) {
-      box.box_float[0] = box.box_float[0] / scale_factor_w;
-      box.box_float[2] = box.box_float[2] / scale_factor_w;
-      box.box_float[1] = box.box_float[1] / scale_factor_h;
-      box.box_float[3] = box.box_float[3] / scale_factor_h;
-      box.box = {(int)box.box_float[0], (int)box.box_float[1],
-                 (int)box.box_float[2], (int)box.box_float[3]};
+      box.box[0] = box.box[0] / scale_factor_w;
+      box.box[2] = box.box[2] / scale_factor_w;
+      box.box[1] = box.box[1] / scale_factor_h;
+      box.box[3] = box.box[3] / scale_factor_h;
       results.push_back(box);
     }
   }
@@ -501,13 +528,13 @@ PicodetPostProcessor::disPred2Bbox(std::vector<float> bbox_pred, int label,
     dis_pred[i] = dis;
   }
 
-  float xmin_float = (std::max)(ct_x - dis_pred[0], .0f);
-  float ymin_float = (std::max)(ct_y - dis_pred[1], .0f);
-  float xmax_float = (std::min)(ct_x + dis_pred[2], (float)im_shape[1]);
-  float ymax_float = (std::min)(ct_y + dis_pred[3], (float)im_shape[0]);
+  float xmin = (std::max)(ct_x - dis_pred[0], .0f);
+  float ymin = (std::max)(ct_y - dis_pred[1], .0f);
+  float xmax = (std::min)(ct_x + dis_pred[2], (float)im_shape[1]);
+  float ymax = (std::min)(ct_y + dis_pred[3], (float)im_shape[0]);
 
   StructurePredictResult result_item;
-  result_item.box_float = {xmin_float, ymin_float, xmax_float, ymax_float};
+  result_item.box = {xmin, ymin, xmax, ymax};
   result_item.type = this->label_list_[label];
   result_item.confidence = score;
 
@@ -530,8 +557,7 @@ void PicodetPostProcessor::nms(std::vector<StructurePredictResult> &input_boxes,
       if (picked[j] == 0) {
         continue;
       }
-      float iou =
-          Utility::iou(input_boxes[i].box_float, input_boxes[j].box_float);
+      float iou = Utility::iou(input_boxes[i].box, input_boxes[j].box);
       if (iou > nms_threshold) {
         picked[j] = 0;
       }

deploy/cpp_infer/src/preprocess_op.cpp

@@ -12,21 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include "opencv2/core.hpp"
-#include "opencv2/imgcodecs.hpp"
-#include "opencv2/imgproc.hpp"
-#include "paddle_api.h"
-#include "paddle_inference_api.h"
-#include <chrono>
-#include <iomanip>
-#include <iostream>
-#include <ostream>
-#include <vector>
-
-#include <cstring>
-#include <fstream>
-#include <numeric>
-
 #include <include/preprocess_op.h>
 
 namespace PaddleOCR {
@@ -69,13 +54,13 @@ void Normalize::Run(cv::Mat *im, const std::vector<float> &mean,
 }
 
 void ResizeImgType0::Run(const cv::Mat &img, cv::Mat &resize_img,
-                         string limit_type, int limit_side_len, float &ratio_h,
-                         float &ratio_w, bool use_tensorrt) {
+                         std::string limit_type, int limit_side_len,
+                         float &ratio_h, float &ratio_w, bool use_tensorrt) {
   int w = img.cols;
   int h = img.rows;
   float ratio = 1.f;
   if (limit_type == "min") {
-    int min_wh = min(h, w);
+    int min_wh = std::min(h, w);
     if (min_wh < limit_side_len) {
       if (h < w) {
         ratio = float(limit_side_len) / float(h);
@@ -84,7 +69,7 @@ void ResizeImgType0::Run(const cv::Mat &img, cv::Mat &resize_img,
       }
     }
   } else {
-    int max_wh = max(h, w);
+    int max_wh = std::max(h, w);
     if (max_wh > limit_side_len) {
       if (h > w) {
         ratio = float(limit_side_len) / float(h);
@@ -97,8 +82,8 @@ void ResizeImgType0::Run(const cv::Mat &img, cv::Mat &resize_img,
   int resize_h = int(float(h) * ratio);
   int resize_w = int(float(w) * ratio);
 
-  resize_h = max(int(round(float(resize_h) / 32) * 32), 32);
-  resize_w = max(int(round(float(resize_w) / 32) * 32), 32);
+  resize_h = std::max(int(round(float(resize_h) / 32) * 32), 32);
+  resize_w = std::max(int(round(float(resize_w) / 32) * 32), 32);
 
   cv::resize(img, resize_img, cv::Size(resize_w, resize_h));
   ratio_h = float(resize_h) / float(h);

deploy/cpp_infer/src/structure_layout.cpp

@@ -94,7 +94,7 @@ void StructureLayoutRecognizer::Run(cv::Mat img,
 }
 
 void StructureLayoutRecognizer::LoadModel(const std::string &model_dir) {
-  AnalysisConfig config;
+  paddle_infer::Config config;
   if (Utility::PathExists(model_dir + "/inference.pdmodel") &&
       Utility::PathExists(model_dir + "/inference.pdiparams")) {
     config.SetModel(model_dir + "/inference.pdmodel",
@@ -105,7 +105,7 @@ void StructureLayoutRecognizer::LoadModel(const std::string &model_dir) {
                     model_dir + "/model.pdiparams");
   } else {
     std::cerr << "[ERROR] not find model.pdiparams or inference.pdiparams in "
-              << model_dir << endl;
+              << model_dir << std::endl;
     exit(1);
   }
 
@@ -144,6 +144,6 @@ void StructureLayoutRecognizer::LoadModel(const std::string &model_dir) {
   config.EnableMemoryOptim();
   config.DisableGlogInfo();
 
-  this->predictor_ = CreatePredictor(config);
+  this->predictor_ = paddle_infer::CreatePredictor(config);
 }
 } // namespace PaddleOCR

deploy/cpp_infer/src/structure_table.cpp

@@ -34,7 +34,7 @@ void StructureTableRecognizer::Run(
        beg_img_no += this->table_batch_num_) {
     // preprocess
     auto preprocess_start = std::chrono::steady_clock::now();
-    int end_img_no = min(img_num, beg_img_no + this->table_batch_num_);
+    int end_img_no = std::min(img_num, beg_img_no + this->table_batch_num_);
     int batch_num = end_img_no - beg_img_no;
     std::vector<cv::Mat> norm_img_batch;
     std::vector<int> width_list;
@@ -118,7 +118,7 @@ void StructureTableRecognizer::Run(
 }
 
 void StructureTableRecognizer::LoadModel(const std::string &model_dir) {
-  AnalysisConfig config;
+  paddle_infer::Config config;
   config.SetModel(model_dir + "/inference.pdmodel",
                   model_dir + "/inference.pdiparams");
 
@@ -157,6 +157,6 @@ void StructureTableRecognizer::LoadModel(const std::string &model_dir) {
   config.EnableMemoryOptim();
   config.DisableGlogInfo();
 
-  this->predictor_ = CreatePredictor(config);
+  this->predictor_ = paddle_infer::CreatePredictor(config);
 }
 } // namespace PaddleOCR

deploy/cpp_infer/src/utility.cpp

@@ -66,7 +66,7 @@ void Utility::VisualizeBboxes(const cv::Mat &srcimg,
 }
 
 void Utility::VisualizeBboxes(const cv::Mat &srcimg,
-                              StructurePredictResult &structure_result,
+                              const StructurePredictResult &structure_result,
                               const std::string &save_path) {
   cv::Mat img_vis;
   srcimg.copyTo(img_vis);
@@ -281,7 +281,7 @@ void Utility::print_result(const std::vector<OCRPredictResult> &ocr_result) {
   }
 }
 
-cv::Mat Utility::crop_image(cv::Mat &img, std::vector<int> &box) {
+cv::Mat Utility::crop_image(cv::Mat &img, const std::vector<int> &box) {
   cv::Mat crop_im;
   int crop_x1 = std::max(0, box[0]);
   int crop_y1 = std::max(0, box[1]);
@@ -298,6 +298,12 @@ cv::Mat Utility::crop_image(cv::Mat &img, std::vector<int> &box) {
   return crop_im;
 }
 
+cv::Mat Utility::crop_image(cv::Mat &img, const std::vector<float> &box) {
+  std::vector<int> box_int = {(int)box[0], (int)box[1], (int)box[2],
+                              (int)box[3]};
+  return crop_image(img, box_int);
+}
+
 void Utility::sorted_boxes(std::vector<OCRPredictResult> &ocr_result) {
   std::sort(ocr_result.begin(), ocr_result.end(), Utility::comparison_box);
   if (ocr_result.size() > 0) {