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mmedit.datasets.mscoco_dataset

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MSCoCoDataset

MSCoCo 2014 dataset.

class mmedit.datasets.mscoco_dataset.MSCoCoDataset(ann_file: str = '', metainfo: Optional[dict] = None, data_root: str = '', drop_caption_rate=0.0, phase='train', year=2014, data_prefix: Union[str, dict] = '', extensions: Sequence[str] = ('.jpg', '.jpeg', '.png', '.ppm', '.bmp', '.pgm', '.tif'), lazy_init: bool = False, classes: Union[str, Sequence[str], None] = None, **kwargs)[source]

Bases: mmedit.datasets.basic_conditional_dataset.BasicConditionalDataset

MSCoCo 2014 dataset.

Parameters
  • 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) – The root directory for data_prefix and ann_file. Defaults to ‘’.

  • drop_caption_rate (float, optional) – Rate of dropping caption, used for training. Defaults to 0.0.

  • phase (str, optional) – Subdataset used for certain phase, can be set to train, test and val. Defaults to ‘train’.

  • year (int, optional) – Version of CoCo dataset, can be set to 2014 and 2017. Defaults to 2014.

  • data_prefix (str | dict) – Prefix for the data. Defaults to ‘’.

  • extensions (Sequence[str]) – A sequence of allowed extensions. Defaults to (‘.jpg’, ‘.jpeg’, ‘.png’, ‘.ppm’, ‘.bmp’, ‘.pgm’, ‘.tif’).

  • lazy_init (bool) – 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. Basedataset can skip load annotations to save time by set lazy_init=False. Defaults to False.

  • **kwargs – Other keyword arguments in BaseDataset.

METAINFO[source]
load_data_list()[source]

Load image paths and gt_labels.

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