cp of 7550 (#7566)

* fix table cpp infer bug

* update vis

* update doc

* change default tale dict to ch

deploy/cpp_infer/include/args.h

@@ -54,6 +54,7 @@ DECLARE_string(table_model_dir);
 DECLARE_int32(table_max_len);
 DECLARE_int32(table_batch_num);
 DECLARE_string(table_char_dict_path);
+DECLARE_bool(merge_no_span_structure);
 // forward related
 DECLARE_bool(det);
 DECLARE_bool(rec);

deploy/cpp_infer/include/paddlestructure.h

@@ -54,15 +54,12 @@ private:
              std::vector<double> &time_info_det,
              std::vector<double> &time_info_rec,
              std::vector<double> &time_info_cls);
-  std::string
-  rebuild_table(std::vector<std::string> rec_html_tags,
-                std::vector<std::vector<std::vector<int>>> rec_boxes,
-                std::vector<OCRPredictResult> &ocr_result);
+  std::string rebuild_table(std::vector<std::string> rec_html_tags,
+                            std::vector<std::vector<int>> rec_boxes,
+                            std::vector<OCRPredictResult> &ocr_result);
 
-  float iou(std::vector<std::vector<int>> &box1,
-            std::vector<std::vector<int>> &box2);
-  float dis(std::vector<std::vector<int>> &box1,
-            std::vector<std::vector<int>> &box2);
+  float iou(std::vector<int> &box1, std::vector<int> &box2);
+  float dis(std::vector<int> &box1, std::vector<int> &box2);
 
   static bool comparison_dis(const std::vector<float> &dis1,
                              const std::vector<float> &dis2) {

deploy/cpp_infer/include/postprocess_op.h

@@ -92,14 +92,13 @@ private:
 
 class TablePostProcessor {
 public:
-  void init(std::string label_path);
-  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,
-      std::vector<std::vector<std::string>> &rec_html_tag_batch,
-      std::vector<std::vector<std::vector<std::vector<int>>>> &rec_boxes_batch,
-      std::vector<int> &width_list, std::vector<int> &height_list);
+  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,
+           std::vector<std::vector<std::string>> &rec_html_tag_batch,
+           std::vector<std::vector<std::vector<int>>> &rec_boxes_batch,
+           std::vector<int> &width_list, std::vector<int> &height_list);
 
 private:
   std::vector<std::string> label_list_;

deploy/cpp_infer/include/structure_table.h

@@ -44,7 +44,8 @@ public:
       const int &gpu_mem, const int &cpu_math_library_num_threads,
       const bool &use_mkldnn, const string &label_path,
       const bool &use_tensorrt, const std::string &precision,
-      const int &table_batch_num, const int &table_max_len) {
+      const int &table_batch_num, const int &table_max_len,
+      const bool &merge_no_span_structure) {
     this->use_gpu_ = use_gpu;
     this->gpu_id_ = gpu_id;
     this->gpu_mem_ = gpu_mem;
@@ -55,7 +56,7 @@ public:
     this->table_batch_num_ = table_batch_num;
     this->table_max_len_ = table_max_len;
 
-    this->post_processor_.init(label_path);
+    this->post_processor_.init(label_path, merge_no_span_structure);
     LoadModel(model_dir);
   }
 
@@ -65,7 +66,7 @@ public:
   void Run(std::vector<cv::Mat> img_list,
            std::vector<std::vector<std::string>> &rec_html_tags,
            std::vector<float> &rec_scores,
-           std::vector<std::vector<std::vector<std::vector<int>>>> &rec_boxes,
+           std::vector<std::vector<std::vector<int>>> &rec_boxes,
            std::vector<double> &times);
 
 private:

deploy/cpp_infer/include/utility.h

@@ -42,6 +42,7 @@ struct OCRPredictResult {
 
 struct StructurePredictResult {
   std::vector<int> box;
+  std::vector<std::vector<int>> cell_box;
   std::string type;
   std::vector<OCRPredictResult> text_res;
   std::string html;
@@ -56,6 +57,10 @@ public:
                               const std::vector<OCRPredictResult> &ocr_result,
                               const std::string &save_path);
 
+  static void VisualizeBboxes(const cv::Mat &srcimg,
+                              const StructurePredictResult &structure_result,
+                              const std::string &save_path);
+
   template <class ForwardIterator>
   inline static size_t argmax(ForwardIterator first, ForwardIterator last) {
     return std::distance(first, std::max_element(first, last));
@@ -81,6 +86,9 @@ public:
 
   static void sorted_boxes(std::vector<OCRPredictResult> &ocr_result);
 
+  static std::vector<int> xyxyxyxy2xyxy(std::vector<std::vector<int>> &box);
+  static std::vector<int> xyxyxyxy2xyxy(std::vector<int> &box);
+
 private:
   static bool comparison_box(const OCRPredictResult &result1,
                              const OCRPredictResult &result2) {

deploy/cpp_infer/readme.md

@@ -350,6 +350,7 @@ More parameters are as follows,
 |table_model_dir|string|-|Address of table recognition inference model|
 |table_char_dict_path|string|../../ppocr/utils/dict/table_structure_dict.txt|dictionary file|
 |table_max_len|int|488|The size of the long side of the input image of the table recognition model, the final input image size of the network is（table_max_len，table_max_len）|
+|merge_no_span_structure|bool|true|Whether to merge <td> and </td> to <td></td|
 
 
 * Multi-language inference is also supported in PaddleOCR, you can refer to [recognition tutorial](../../doc/doc_en/recognition_en.md) for more supported languages and models in PaddleOCR. Specifically, if you want to infer using multi-language models, you just need to modify values of `rec_char_dict_path` and `rec_model_dir`.

deploy/cpp_infer/readme_ch.md

@@ -359,6 +359,7 @@ CUDNN_LIB_DIR=/your_cudnn_lib_dir
 |table_model_dir|string|-|表格识别模型inference model地址|
 |table_char_dict_path|string|../../ppocr/utils/dict/table_structure_dict.txt|字典文件|
 |table_max_len|int|488|表格识别模型输入图像长边大小，最终网络输入图像大小为（table_max_len，table_max_len）|
+|merge_no_span_structure|bool|true|是否合并<td> 和 </td> 为<td></td>|
 
 
 * PaddleOCR也支持多语言的预测，更多支持的语言和模型可以参考[识别文档](../../doc/doc_ch/recognition.md)中的多语言字典与模型部分，如果希望进行多语言预测，只需将修改`rec_char_dict_path`（字典文件路径）以及`rec_model_dir`（inference模型路径）字段即可。

deploy/cpp_infer/src/args.cpp

@@ -55,8 +55,10 @@ DEFINE_int32(rec_img_w, 320, "rec image width");
 DEFINE_string(table_model_dir, "", "Path of table struture inference model.");
 DEFINE_int32(table_max_len, 488, "max len size of input image.");
 DEFINE_int32(table_batch_num, 1, "table_batch_num.");
+DEFINE_bool(merge_no_span_structure, true,
+            "Whether merge <td> and </td> to <td></td>");
 DEFINE_string(table_char_dict_path,
-              "../../ppocr/utils/dict/table_structure_dict.txt",
+              "../../ppocr/utils/dict/table_structure_dict_ch.txt",
               "Path of dictionary.");
 
 // ocr forward related

deploy/cpp_infer/src/main.cpp

@@ -120,6 +120,7 @@ void structure(std::vector<cv::String> &cv_all_img_names) {
       engine.structure(cv_all_img_names, false, FLAGS_table);
   for (int i = 0; i < cv_all_img_names.size(); i++) {
     cout << "predict img: " << cv_all_img_names[i] << endl;
+    cv::Mat srcimg = cv::imread(cv_all_img_names[i], cv::IMREAD_COLOR);
     for (int j = 0; j < structure_results[i].size(); j++) {
       std::cout << j << "\ttype: " << structure_results[i][j].type
                 << ", region: [";
@@ -129,6 +130,11 @@ void structure(std::vector<cv::String> &cv_all_img_names) {
                 << structure_results[i][j].box[3] << "], res: ";
       if (structure_results[i][j].type == "table") {
         std::cout << structure_results[i][j].html << std::endl;
+        std::string file_name = Utility::basename(cv_all_img_names[i]);
+
+        Utility::VisualizeBboxes(srcimg, structure_results[i][j],
+                                 FLAGS_output + "/" + std::to_string(j) + "_" +
+                                     file_name);
       } else {
         Utility::print_result(structure_results[i][j].text_res);
       }

deploy/cpp_infer/src/paddlestructure.cpp

@@ -27,7 +27,7 @@ PaddleStructure::PaddleStructure() {
         FLAGS_table_model_dir, FLAGS_use_gpu, FLAGS_gpu_id, FLAGS_gpu_mem,
         FLAGS_cpu_threads, FLAGS_enable_mkldnn, FLAGS_table_char_dict_path,
         FLAGS_use_tensorrt, FLAGS_precision, FLAGS_table_batch_num,
-        FLAGS_table_max_len);
+        FLAGS_table_max_len, FLAGS_merge_no_span_structure);
   }
 };
 
@@ -42,7 +42,7 @@ PaddleStructure::structure(std::vector<cv::String> cv_all_img_names,
   std::vector<std::vector<StructurePredictResult>> structure_results;
 
   if (!Utility::PathExists(FLAGS_output) && FLAGS_det) {
-    mkdir(FLAGS_output.c_str(), 0777);
+    Utility::CreateDir(FLAGS_output);
   }
   for (int i = 0; i < cv_all_img_names.size(); ++i) {
     std::vector<StructurePredictResult> structure_result;
@@ -84,7 +84,7 @@ void PaddleStructure::table(cv::Mat img,
   // predict structure
   std::vector<std::vector<std::string>> structure_html_tags;
   std::vector<float> structure_scores(1, 0);
-  std::vector<std::vector<std::vector<std::vector<int>>>> structure_boxes;
+  std::vector<std::vector<std::vector<int>>> structure_boxes;
   std::vector<double> structure_imes;
   std::vector<cv::Mat> img_list;
   img_list.push_back(img);
@@ -103,20 +103,15 @@ void PaddleStructure::table(cv::Mat img,
     this->det(img_list[i], ocr_result, time_info_det);
     // crop image
     std::vector<cv::Mat> rec_img_list;
+    std::vector<int> ocr_box;
     for (int j = 0; j < ocr_result.size(); j++) {
-      int x_collect[4] = {ocr_result[j].box[0][0], ocr_result[j].box[1][0],
-                          ocr_result[j].box[2][0], ocr_result[j].box[3][0]};
-      int y_collect[4] = {ocr_result[j].box[0][1], ocr_result[j].box[1][1],
-                          ocr_result[j].box[2][1], ocr_result[j].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));
-      std::vector<int> box{max(0, left - expand_pixel),
-                           max(0, top - expand_pixel),
-                           min(img_list[i].cols, right + expand_pixel),
-                           min(img_list[i].rows, bottom + expand_pixel)};
-      cv::Mat crop_img = Utility::crop_image(img_list[i], box);
+      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);
+
+      cv::Mat crop_img = Utility::crop_image(img_list[i], ocr_box);
       rec_img_list.push_back(crop_img);
     }
     // rec
@@ -125,38 +120,37 @@ void PaddleStructure::table(cv::Mat img,
     html = this->rebuild_table(structure_html_tags[i], structure_boxes[i],
                                ocr_result);
     structure_result.html = html;
+    structure_result.cell_box = structure_boxes[i];
     structure_result.html_score = structure_scores[i];
   }
 };
 
-std::string PaddleStructure::rebuild_table(
-    std::vector<std::string> structure_html_tags,
-    std::vector<std::vector<std::vector<int>>> structure_boxes,
-    std::vector<OCRPredictResult> &ocr_result) {
+std::string
+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<int> ocr_box;
+  std::vector<int> structure_box;
   for (int i = 0; i < ocr_result.size(); i++) {
+    ocr_box = Utility::xyxyxyxy2xyxy(ocr_result[i].box);
+    ocr_box[0] -= 1;
+    ocr_box[1] -= 1;
+    ocr_box[2] += 1;
+    ocr_box[3] += 1;
     std::vector<std::vector<float>> dis_list(structure_boxes.size(),
                                              std::vector<float>(3, 100000.0));
     for (int j = 0; j < structure_boxes.size(); j++) {
-      int x_collect[4] = {ocr_result[i].box[0][0], ocr_result[i].box[1][0],
-                          ocr_result[i].box[2][0], ocr_result[i].box[3][0]};
-      int y_collect[4] = {ocr_result[i].box[0][1], ocr_result[i].box[1][1],
-                          ocr_result[i].box[2][1], ocr_result[i].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));
-      std::vector<std::vector<int>> box(2, std::vector<int>(2, 0));
-      box[0][0] = left - 1;
-      box[0][1] = top - 1;
-      box[1][0] = right + 1;
-      box[1][1] = bottom + 1;
-
-      dis_list[j][0] = this->dis(box, structure_boxes[j]);
-      dis_list[j][1] = 1 - this->iou(box, structure_boxes[j]);
+      if (structure_boxes[i].size() == 8) {
+        structure_box = Utility::xyxyxyxy2xyxy(structure_boxes[j]);
+      } else {
+        structure_box = structure_boxes[j];
+      }
+      dis_list[j][0] = this->dis(ocr_box, structure_box);
+      dis_list[j][1] = 1 - this->iou(ocr_box, structure_box);
       dis_list[j][2] = j;
     }
     // find min dis idx
@@ -164,6 +158,7 @@ std::string PaddleStructure::rebuild_table(
               PaddleStructure::comparison_dis);
     matched[dis_list[0][2]].push_back(ocr_result[i].text);
   }
+
   // get pred html
   std::string html_str = "";
   int td_tag_idx = 0;
@@ -221,19 +216,18 @@ std::string PaddleStructure::rebuild_table(
   return html_str;
 }
 
-float PaddleStructure::iou(std::vector<std::vector<int>> &box1,
-                           std::vector<std::vector<int>> &box2) {
-  int area1 = max(0, box1[1][0] - box1[0][0]) * max(0, box1[1][1] - box1[0][1]);
-  int area2 = max(0, box2[1][0] - box2[0][0]) * max(0, box2[1][1] - box2[0][1]);
+float PaddleStructure::iou(std::vector<int> &box1, std::vector<int> &box2) {
+  int area1 = max(0, box1[2] - box1[0]) * max(0, box1[3] - box1[1]);
+  int area2 = max(0, box2[2] - box2[0]) * max(0, box2[3] - box2[1]);
 
   // computing the sum_area
   int sum_area = area1 + area2;
 
   // find the each point of intersect rectangle
-  int x1 = max(box1[0][0], box2[0][0]);
-  int y1 = max(box1[0][1], box2[0][1]);
-  int x2 = min(box1[1][0], box2[1][0]);
-  int y2 = min(box1[1][1], box2[1][1]);
+  int x1 = max(box1[0], box2[0]);
+  int y1 = max(box1[1], box2[1]);
+  int x2 = min(box1[2], box2[2]);
+  int y2 = min(box1[3], box2[3]);
 
   // judge if there is an intersect
   if (y1 >= y2 || x1 >= x2) {
@@ -244,17 +238,16 @@ float PaddleStructure::iou(std::vector<std::vector<int>> &box1,
   }
 }
 
-float PaddleStructure::dis(std::vector<std::vector<int>> &box1,
-                           std::vector<std::vector<int>> &box2) {
-  int x1_1 = box1[0][0];
-  int y1_1 = box1[0][1];
-  int x2_1 = box1[1][0];
-  int y2_1 = box1[1][1];
+float PaddleStructure::dis(std::vector<int> &box1, std::vector<int> &box2) {
+  int x1_1 = box1[0];
+  int y1_1 = box1[1];
+  int x2_1 = box1[2];
+  int y2_1 = box1[3];
 
-  int x1_2 = box2[0][0];
-  int y1_2 = box2[0][1];
-  int x2_2 = box2[1][0];
-  int y2_2 = box2[1][1];
+  int x1_2 = box2[0];
+  int y1_2 = box2[1];
+  int x2_2 = box2[2];
+  int y2_2 = box2[3];
 
   float dis =
       abs(x1_2 - x1_1) + abs(y1_2 - y1_1) + abs(x2_2 - x2_1) + abs(y2_2 - y2_1);

deploy/cpp_infer/src/postprocess_op.cpp

@@ -352,8 +352,21 @@ std::vector<std::vector<std::vector<int>>> DBPostProcessor::FilterTagDetRes(
   return root_points;
 }
 
-void TablePostProcessor::init(std::string label_path) {
+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);
 }
@@ -363,12 +376,12 @@ void TablePostProcessor::Run(
     std::vector<float> &rec_scores, std::vector<int> &loc_preds_shape,
     std::vector<int> &structure_probs_shape,
     std::vector<std::vector<std::string>> &rec_html_tag_batch,
-    std::vector<std::vector<std::vector<std::vector<int>>>> &rec_boxes_batch,
+    std::vector<std::vector<std::vector<int>>> &rec_boxes_batch,
     std::vector<int> &width_list, std::vector<int> &height_list) {
   for (int batch_idx = 0; batch_idx < structure_probs_shape[0]; batch_idx++) {
     // image tags and boxs
     std::vector<std::string> rec_html_tags;
-    std::vector<std::vector<std::vector<int>>> rec_boxes;
+    std::vector<std::vector<int>> rec_boxes;
 
     float score = 0.f;
     int count = 0;
@@ -378,7 +391,7 @@ void TablePostProcessor::Run(
     // step
     for (int step_idx = 0; step_idx < structure_probs_shape[1]; step_idx++) {
       std::string html_tag;
-      std::vector<std::vector<int>> rec_box;
+      std::vector<int> rec_box;
       // html tag
       int step_start_idx = (batch_idx * structure_probs_shape[1] + step_idx) *
                            structure_probs_shape[2];
@@ -399,17 +412,19 @@ void TablePostProcessor::Run(
       count += 1;
       score += char_score;
       rec_html_tags.push_back(html_tag);
+
       // box
       if (html_tag == "<td>" || html_tag == "<td" || html_tag == "<td></td>") {
-        for (int point_idx = 0; point_idx < loc_preds_shape[2];
-             point_idx += 2) {
-          std::vector<int> point(2, 0);
+        for (int point_idx = 0; point_idx < loc_preds_shape[2]; point_idx++) {
           step_start_idx = (batch_idx * structure_probs_shape[1] + step_idx) *
                                loc_preds_shape[2] +
                            point_idx;
-          point[0] = int(loc_preds[step_start_idx] * width_list[batch_idx]);
-          point[1] =
-              int(loc_preds[step_start_idx + 1] * height_list[batch_idx]);
+          float point = loc_preds[step_start_idx];
+          if (point_idx % 2 == 0) {
+            point = int(point * width_list[batch_idx]);
+          } else {
+            point = int(point * height_list[batch_idx]);
+          }
           rec_box.push_back(point);
         }
         rec_boxes.push_back(rec_box);

deploy/cpp_infer/src/structure_table.cpp

@@ -20,7 +20,7 @@ void StructureTableRecognizer::Run(
     std::vector<cv::Mat> img_list,
     std::vector<std::vector<std::string>> &structure_html_tags,
     std::vector<float> &structure_scores,
-    std::vector<std::vector<std::vector<std::vector<int>>>> &structure_boxes,
+    std::vector<std::vector<std::vector<int>>> &structure_boxes,
     std::vector<double> &times) {
   std::chrono::duration<float> preprocess_diff =
       std::chrono::steady_clock::now() - std::chrono::steady_clock::now();
@@ -89,8 +89,7 @@ void StructureTableRecognizer::Run(
     auto postprocess_start = std::chrono::steady_clock::now();
     std::vector<std::vector<std::string>> structure_html_tag_batch;
     std::vector<float> structure_score_batch;
-    std::vector<std::vector<std::vector<std::vector<int>>>>
-        structure_boxes_batch;
+    std::vector<std::vector<std::vector<int>>> structure_boxes_batch;
     this->post_processor_.Run(loc_preds, structure_probs, structure_score_batch,
                               predict_shape0, predict_shape1,
                               structure_html_tag_batch, structure_boxes_batch,

deploy/cpp_infer/src/utility.cpp

@@ -65,6 +65,37 @@ void Utility::VisualizeBboxes(const cv::Mat &srcimg,
             << std::endl;
 }
 
+void Utility::VisualizeBboxes(const cv::Mat &srcimg,
+                              const StructurePredictResult &structure_result,
+                              const std::string &save_path) {
+  cv::Mat img_vis;
+  srcimg.copyTo(img_vis);
+  for (int n = 0; n < structure_result.cell_box.size(); n++) {
+    if (structure_result.cell_box[n].size() == 8) {
+      cv::Point rook_points[4];
+      for (int m = 0; m < structure_result.cell_box[n].size(); m += 2) {
+        rook_points[m / 2] =
+            cv::Point(int(structure_result.cell_box[n][m]),
+                      int(structure_result.cell_box[n][m + 1]));
+      }
+      const cv::Point *ppt[1] = {rook_points};
+      int npt[] = {4};
+      cv::polylines(img_vis, ppt, npt, 1, 1, CV_RGB(0, 255, 0), 2, 8, 0);
+    } else if (structure_result.cell_box[n].size() == 4) {
+      cv::Point rook_points[2];
+      rook_points[0] = cv::Point(int(structure_result.cell_box[n][0]),
+                                 int(structure_result.cell_box[n][1]));
+      rook_points[1] = cv::Point(int(structure_result.cell_box[n][2]),
+                                 int(structure_result.cell_box[n][3]));
+      cv::rectangle(img_vis, rook_points[0], rook_points[1], CV_RGB(0, 255, 0),
+                    2, 8, 0);
+    }
+  }
+
+  cv::imwrite(save_path, img_vis);
+  std::cout << "The table visualized image saved in " + save_path << std::endl;
+}
+
 // list all files under a directory
 void Utility::GetAllFiles(const char *dir_name,
                           std::vector<std::string> &all_inputs) {
@@ -268,13 +299,46 @@ cv::Mat Utility::crop_image(cv::Mat &img, std::vector<int> &area) {
 
 void Utility::sorted_boxes(std::vector<OCRPredictResult> &ocr_result) {
   std::sort(ocr_result.begin(), ocr_result.end(), Utility::comparison_box);
-
-  for (int i = 0; i < ocr_result.size() - 1; i++) {
-    if (abs(ocr_result[i + 1].box[0][1] - ocr_result[i].box[0][1]) < 10 &&
-        (ocr_result[i + 1].box[0][0] < ocr_result[i].box[0][0])) {
-      std::swap(ocr_result[i], ocr_result[i + 1]);
+  if (ocr_result.size() > 0) {
+    for (int i = 0; i < ocr_result.size() - 1; i++) {
+      for (int j = i; j > 0; j--) {
+        if (abs(ocr_result[j + 1].box[0][1] - ocr_result[j].box[0][1]) < 10 &&
+            (ocr_result[j + 1].box[0][0] < ocr_result[j].box[0][0])) {
+          std::swap(ocr_result[i], ocr_result[i + 1]);
+        }
+      }
     }
   }
 }
 
+std::vector<int> Utility::xyxyxyxy2xyxy(std::vector<std::vector<int>> &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));
+  std::vector<int> box1(4, 0);
+  box1[0] = left;
+  box1[1] = top;
+  box1[2] = right;
+  box1[3] = bottom;
+  return box1;
+}
+
+std::vector<int> Utility::xyxyxyxy2xyxy(std::vector<int> &box) {
+  int x_collect[4] = {box[0], box[2], box[4], box[6]};
+  int y_collect[4] = {box[1], box[3], box[5], box[7]};
+  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));
+  std::vector<int> box1(4, 0);
+  box1[0] = left;
+  box1[1] = top;
+  box1[2] = right;
+  box1[3] = bottom;
+  return box1;
+}
+
 } // namespace PaddleOCR
\ No newline at end of file

ppstructure/utility.py

@@ -32,7 +32,7 @@ def init_args():
     parser.add_argument(
         "--table_char_dict_path",
         type=str,
-        default="../ppocr/utils/dict/table_structure_dict.txt")
+        default="../ppocr/utils/dict/table_structure_dict_ch.txt")
     # params for layout
     parser.add_argument("--layout_model_dir", type=str)
     parser.add_argument(