fix config format

configs/e2e/e2e_r50_vd_pg.yml

@@ -69,10 +69,9 @@ Metric:
 Train:
   dataset:
     name: PGDataSet
-    data_dir: ./train_data/
+    data_dir: ./train_data/train
     label_file_list: [.././train_data/total_text/train/]
     ratio_list: [1.0]
-    data_format: icdar #two data format: icdar/textnet
     transforms:
       - DecodeImage: # load image
           img_mode: BGR
@@ -94,7 +93,7 @@ Train:
 Eval:
   dataset:
     name: PGDataSet
-    data_dir: ./train_data/
+    data_dir: ./train_data/test
     label_file_list: [./train_data/total_text/test/]
     transforms:
       - DecodeImage: # load image

doc/doc_ch/pgnet.md

@@ -30,6 +30,7 @@ PGNet算法细节详见[论文](https://www.aaai.org/AAAI21Papers/AAAI-2885.Wang
 测试集：Total-Text
 
 测试环境: NVIDIA Tesla V100-SXM2-16GB
+
 |PGNetA|det_precision|det_recall|det_f_score|e2e_precision|e2e_recall|e2e_f_score|FPS|下载|
 | --- | --- | --- | --- | --- | --- | --- | --- | --- |
 |Paper|85.30|86.80|86.1|-|-|61.7|38.20 (size=640)|-|

ppocr/data/pgnet_dataset.py

@@ -78,7 +78,10 @@ class PGDataSet(Dataset):
             file_name = substr[0]
             label = substr[1]
             img_path = os.path.join(self.data_dir, file_name)
-            img_id = int(data_line.split(".")[0][3:])
+            if self.mode.lower() == 'eval':
+                img_id = int(data_line.split(".")[0][7:])
+            else:
+                img_id = 0
             data = {'img_path': img_path, 'label': label, 'img_id': img_id}
             if not os.path.exists(img_path):
                 raise Exception("{} does not exist!".format(img_path))

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):