advance db post_process

deploy/cpp_infer/src/ocr_det.cpp

@@ -108,9 +108,11 @@ void DBDetector::Run(cv::Mat &img,
   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, bit_map, this->det_db_box_thresh_, this->det_db_unclip_ratio_);
+      pred_map, dilation_map, this->det_db_box_thresh_, this->det_db_unclip_ratio_);
 
   boxes = post_processor_.FilterTagDetRes(boxes, ratio_h, ratio_w, srcimg);
 

deploy/cpp_infer/src/postprocess_op.cpp

@@ -294,7 +294,7 @@ PostProcessor::FilterTagDetRes(std::vector<std::vector<std::vector<int>>> boxes,
                           pow(boxes[n][0][1] - boxes[n][1][1], 2)));
     rect_height = int(sqrt(pow(boxes[n][0][0] - boxes[n][3][0], 2) +
                            pow(boxes[n][0][1] - boxes[n][3][1], 2)));
-    if (rect_width <= 10 || rect_height <= 10)
+    if (rect_width <= 4 || rect_height <= 4)
       continue;
     root_points.push_back(boxes[n]);
   }

deploy/cpp_infer/tools/config.txt

@@ -10,7 +10,7 @@ use_zero_copy_run 1
 max_side_len  960
 det_db_thresh  0.3
 det_db_box_thresh  0.5
-det_db_unclip_ratio  2.0
+det_db_unclip_ratio  1.6
 det_model_dir  ./inference/det_db
 
 # cls config

deploy/lite/config.txt

@@ -1,4 +1,4 @@
 max_side_len  960
 det_db_thresh  0.3
 det_db_box_thresh  0.5
-det_db_unclip_ratio  2.0
+det_db_unclip_ratio  1.6

deploy/lite/db_post_process.cc

@@ -293,7 +293,7 @@ FilterTagDetRes(std::vector<std::vector<std::vector<int>>> boxes, float ratio_h,
     rect_height =
         static_cast<int>(sqrt(pow(boxes[n][0][0] - boxes[n][3][0], 2) +
                               pow(boxes[n][0][1] - boxes[n][3][1], 2)));
-    if (rect_width <= 10 || rect_height <= 10)
+    if (rect_width <= 4 || rect_height <= 4)
       continue;
     root_points.push_back(boxes[n]);
   }

deploy/lite/ocr_db_crnn.cc

@@ -289,8 +289,10 @@ RunDetModel(std::shared_ptr<PaddlePredictor> predictor, cv::Mat img,
   const double maxvalue = 255;
   cv::Mat bit_map;
   cv::threshold(cbuf_map, bit_map, threshold, maxvalue, cv::THRESH_BINARY);
-
-  auto boxes = BoxesFromBitmap(pred_map, bit_map, Config);
+  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);
+  auto boxes = BoxesFromBitmap(pred_map, dilation_map, Config);
 
   std::vector<std::vector<std::vector<int>>> filter_boxes =
       FilterTagDetRes(boxes, ratio_hw[0], ratio_hw[1], srcimg);

ppocr/postprocess/db_postprocess.py

@@ -37,6 +37,7 @@ class DBPostProcess(object):
         self.max_candidates = params['max_candidates']
         self.unclip_ratio = params['unclip_ratio']
         self.min_size = 3
+        self.dilation_kernel = np.array([[1, 1], [1, 1]])
 
     def boxes_from_bitmap(self, pred, _bitmap, dest_width, dest_height):
         '''
@@ -140,8 +141,9 @@ class DBPostProcess(object):
         boxes_batch = []
         for batch_index in range(pred.shape[0]):
             height, width = pred.shape[-2:]
-            tmp_boxes, tmp_scores = self.boxes_from_bitmap(
-                pred[batch_index], segmentation[batch_index], width, height)
+
+            mask = cv2.dilate(np.array(segmentation[batch_index]).astype(np.uint8), self.dilation_kernel)
+            tmp_boxes, tmp_scores = self.boxes_from_bitmap(pred[batch_index], mask, width, height)
 
             boxes = []
             for k in range(len(tmp_boxes)):

tools/infer/utility.py

@@ -47,7 +47,7 @@ def parse_args():
     # DB parmas
     parser.add_argument("--det_db_thresh", type=float, default=0.3)
     parser.add_argument("--det_db_box_thresh", type=float, default=0.5)
-    parser.add_argument("--det_db_unclip_ratio", type=float, default=2.0)
+    parser.add_argument("--det_db_unclip_ratio", type=float, default=1.6)
 
     # EAST parmas
     parser.add_argument("--det_east_score_thresh", type=float, default=0.8)
@@ -64,7 +64,7 @@ def parse_args():
     parser.add_argument("--rec_model_dir", type=str)
     parser.add_argument("--rec_image_shape", type=str, default="3, 32, 320")
     parser.add_argument("--rec_char_type", type=str, default='ch')
-    parser.add_argument("--rec_batch_num", type=int, default=30)
+    parser.add_argument("--rec_batch_num", type=int, default=6)
     parser.add_argument("--max_text_length", type=int, default=25)
     parser.add_argument(
         "--rec_char_dict_path",