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mmocr.datasets.ocr_dataset 源代码

# Copyright (c) OpenMMLab. All rights reserved.
from mmengine.dataset import BaseDataset

from mmocr.registry import DATASETS


[文档]@DATASETS.register_module() class OCRDataset(BaseDataset): r"""OCRDataset for text detection and text recognition. The annotation format is shown as follows. .. code-block:: none { "metainfo": { "dataset_type": "test_dataset", "task_name": "test_task" }, "data_list": [ { "img_path": "test_img.jpg", "height": 604, "width": 640, "instances": [ { "bbox": [0, 0, 10, 20], "bbox_label": 1, "mask": [0,0,0,10,10,20,20,0], "text": '123' }, { "bbox": [10, 10, 110, 120], "bbox_label": 2, "mask": [10,10],10,110,110,120,120,10]], "extra_anns": '456' } ] }, ] } Args: ann_file (str): Annotation file path. Defaults to ''. metainfo (dict, optional): Meta information for dataset, such as class information. Defaults to None. data_root (str, optional): The root directory for ``data_prefix`` and ``ann_file``. Defaults to None. data_prefix (dict): Prefix for training data. Defaults to dict(img_path=''). filter_cfg (dict, optional): Config for filter data. Defaults to None. indices (int or Sequence[int], optional): Support using first few data in annotation file to facilitate training/testing on a smaller dataset. Defaults to None which means using all ``data_infos``. serialize_data (bool, optional): Whether to hold memory using serialized objects, when enabled, data loader workers can use shared RAM from master process instead of making a copy. Defaults to True. pipeline (list, optional): Processing pipeline. Defaults to []. test_mode (bool, optional): ``test_mode=True`` means in test phase. Defaults to False. lazy_init (bool, optional): Whether to load annotation during instantiation. In some cases, such as visualization, only the meta information of the dataset is needed, which is not necessary to load annotation file. ``OCRdataset`` can skip load annotations to save time by set ``lazy_init=False``. Defaults to False. max_refetch (int, optional): If ``OCRdataset.prepare_data`` get a None img. The maximum extra number of cycles to get a valid image. Defaults to 1000. Note: OCRDataset collects meta information from `annotation file` (the lowest priority), ``OCRDataset.METAINFO``(medium) and `metainfo parameter` (highest) passed to constructors. The lower priority meta information will be overwritten by higher one. Examples: Assume the annotation file is given above. >>> class CustomDataset(OCRDataset): >>> METAINFO: dict = dict(task_name='custom_task', >>> dataset_type='custom_type') >>> metainfo=dict(task_name='custom_task_name') >>> custom_dataset = CustomDataset( >>> 'path/to/ann_file', >>> metainfo=metainfo) >>> # meta information of annotation file will be overwritten by >>> # `CustomDataset.METAINFO`. The merged meta information will >>> # further be overwritten by argument `metainfo`. >>> custom_dataset.metainfo {'task_name': custom_task_name, dataset_type: custom_type} """
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