阶段性完成SERDataset数据集加载

mmocr/datasets/ser_dataset.py

@@ -46,39 +46,46 @@ def load_data_list(self) -> List[dict]:
         data_list = super().load_data_list()
 
         # split text to several slices because of over-length
-        input_ids, bboxes, labels = [], [], []
-        segment_ids, position_ids = [], []
-        image_path = []
+        split_text_data_list = []
         for i in range(len(data_list)):
             start = 0
             cur_iter = 0
             while start < len(data_list[i]['input_ids']):
                 end = min(start + 510, len(data_list[i]['input_ids']))
-
-                input_ids.append([self.tokenizer.cls_token_id] +
-                                 data_list[i]['input_ids'][start:end] +
-                                 [self.tokenizer.sep_token_id])
-                bboxes.append([[0, 0, 0, 0]] +
-                              data_list[i]['bboxes'][start:end] +
-                              [[1000, 1000, 1000, 1000]])
-                labels.append([-100] + data_list[i]['labels'][start:end] +
-                              [-100])
-
-                cur_segment_ids = self.get_segment_ids(bboxes[-1])
-                cur_position_ids = self.get_position_ids(cur_segment_ids)
-                segment_ids.append(cur_segment_ids)
-                position_ids.append(cur_position_ids)
-                image_path.append(
-                    os.path.join(self.data_root, data_list[i]['img_path']))
+                # get input_ids
+                input_ids = [self.tokenizer.cls_token_id] + \
+                    data_list[i]['input_ids'][start:end] + \
+                    [self.tokenizer.sep_token_id]
+                # get bboxes
+                bboxes = [[0, 0, 0, 0]] + \
+                    data_list[i]['bboxes'][start:end] + \
+                    [[1000, 1000, 1000, 1000]]
+                # get labels
+                labels = [-100] + data_list[i]['labels'][start:end] + [-100]
+                # get segment_ids
+                segment_ids = self.get_segment_ids(bboxes)
+                # get position_ids
+                position_ids = self.get_position_ids(segment_ids)
+                # get img_path
+                img_path = os.path.join(self.data_root,
+                                        data_list[i]['img_path'])
+                # get attention_mask
+                attention_mask = [1] * len(input_ids)
+
+                data_info = {}
+                data_info['input_ids'] = input_ids
+                data_info['bboxes'] = bboxes
+                data_info['labels'] = labels
+                data_info['segment_ids'] = segment_ids
+                data_info['position_ids'] = position_ids
+                data_info['img_path'] = img_path
+                data_info['attention_mask '] = attention_mask
+                split_text_data_list.append(data_info)
 
                 start = end
                 cur_iter += 1
 
-        assert len(input_ids) == len(bboxes) == len(labels) == len(
-            segment_ids) == len(position_ids)
-        assert len(segment_ids) == len(image_path)
-
-        return data_list
+        return split_text_data_list
 
     def parse_data_info(self, raw_data_info: dict) -> Union[dict, List[dict]]:
         instances = raw_data_info['instances']

projects/LayoutLMv3/test.py

@@ -1,14 +1,23 @@
 from mmengine.config import Config
+from mmengine.registry import init_default_scope
 
 from mmocr.registry import DATASETS
 
 if __name__ == '__main__':
     cfg_path = '/Users/wangnu/Documents/GitHub/mmocr/projects/' \
         'LayoutLMv3/configs/layoutlmv3_xfund_zh.py'
     cfg = Config.fromfile(cfg_path)
+    init_default_scope(cfg.get('default_scope', 'mmocr'))
 
     dataset_cfg = cfg.train_dataset
     dataset_cfg['tokenizer'] = \
         '/Users/wangnu/Documents/GitHub/mmocr/data/layoutlmv3-base-chinese'
+
+    train_pipeline = [
+        dict(type='LoadImageFromFile', color_type='color'),
+        dict(type='Resize', scale=(224, 224))
+    ]
+    dataset_cfg['pipeline'] = train_pipeline
     ds = DATASETS.build(dataset_cfg)
-    print(ds[0])
+    data = ds[0]
+    print('hi')