Merge branch 'dygraph' into fix_starnet

ppocr/utils/e2e_metric/Deteval.py

@@ -26,7 +26,7 @@ def get_socre(gt_dir, img_id, pred_dict):
         n = len(pred_dict)
         for i in range(n):
             points = pred_dict[i]['points']
-            text = pred_dict[i]['text']
+            text = pred_dict[i]['texts']
             point = ",".join(map(str, points.reshape(-1, )))
             det.append([point, text])
         return det

ppocr/utils/e2e_utils/extract_textpoint_fast.py

@@ -21,6 +21,7 @@ import math
 
 import numpy as np
 from itertools import groupby
+from cv2.ximgproc import thinning as thin
 from skimage.morphology._skeletonize import thin
 
 

ppocr/utils/e2e_utils/pgnet_pp_utils.py

@@ -64,7 +64,7 @@ class PGNet_PostProcess(object):
                                                 src_w, src_h, self.valid_set)
         data = {
             'points': poly_list,
-            'strs': keep_str_list,
+            'texts': keep_str_list,
         }
         return data
 
@@ -176,6 +176,6 @@ class PGNet_PostProcess(object):
                 exit(-1)
         data = {
             'points': poly_list,
-            'strs': keep_str_list,
+            'texts': keep_str_list,
         }
         return data

tools/infer/predict_e2e.py

@@ -122,7 +122,7 @@ class TextE2E(object):
         else:
             raise NotImplementedError
         post_result = self.postprocess_op(preds, shape_list)
-        points, strs = post_result['points'], post_result['strs']
+        points, strs = post_result['points'], post_result['texts']
         dt_boxes = self.filter_tag_det_res_only_clip(points, ori_im.shape)
         elapse = time.time() - starttime
         return dt_boxes, strs, elapse

tools/infer_e2e.py

@@ -103,7 +103,7 @@ def main():
             images = paddle.to_tensor(images)
             preds = model(images)
             post_result = post_process_class(preds, shape_list)
-            points, strs = post_result['points'], post_result['strs']
+            points, strs = post_result['points'], post_result['texts']
             # write resule
             dt_boxes_json = []
             for poly, str in zip(points, strs):