mmpose.datasets.datasets.body.crowdpose_dataset 源代码

# Copyright (c) OpenMMLab. All rights reserved.
from mmpose.registry import DATASETS
from ..base import BaseCocoStyleDataset

[文档]@DATASETS.register_module() class CrowdPoseDataset(BaseCocoStyleDataset): """CrowdPose dataset for pose estimation. "CrowdPose: Efficient Crowded Scenes Pose Estimation and A New Benchmark", CVPR'2019. More details can be found in the `paper <>`__. CrowdPose keypoints:: 0: 'left_shoulder', 1: 'right_shoulder', 2: 'left_elbow', 3: 'right_elbow', 4: 'left_wrist', 5: 'right_wrist', 6: 'left_hip', 7: 'right_hip', 8: 'left_knee', 9: 'right_knee', 10: 'left_ankle', 11: 'right_ankle', 12: 'top_head', 13: 'neck' Args: ann_file (str): Annotation file path. Default: ''. bbox_file (str, optional): Detection result file path. If ``bbox_file`` is set, detected bboxes loaded from this file will be used instead of ground-truth bboxes. This setting is only for evaluation, i.e., ignored when ``test_mode`` is ``False``. Default: ``None``. data_mode (str): Specifies the mode of data samples: ``'topdown'`` or ``'bottomup'``. In ``'topdown'`` mode, each data sample contains one instance; while in ``'bottomup'`` mode, each data sample contains all instances in a image. Default: ``'topdown'`` metainfo (dict, optional): Meta information for dataset, such as class information. Default: ``None``. data_root (str, optional): The root directory for ``data_prefix`` and ``ann_file``. Default: ``None``. data_prefix (dict, optional): Prefix for training data. Default: ``dict(img=None, ann=None)``. filter_cfg (dict, optional): Config for filter data. Default: `None`. indices (int or Sequence[int], optional): Support using first few data in annotation file to facilitate training/testing on a smaller dataset. Default: ``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. Default: ``True``. pipeline (list, optional): Processing pipeline. Default: []. test_mode (bool, optional): ``test_mode=True`` means in test phase. Default: ``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. ``Basedataset`` can skip load annotations to save time by set ``lazy_init=False``. Default: ``False``. max_refetch (int, optional): If ``Basedataset.prepare_data`` get a None img. The maximum extra number of cycles to get a valid image. Default: 1000. """ METAINFO: dict = dict(from_file='configs/_base_/datasets/')
Read the Docs v: latest
On Read the Docs
Project Home

Free document hosting provided by Read the Docs.