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# Copyright (c) OpenMMLab. All rights reserved.
from typing import Optional
import numpy as np
from mmcv.transforms import LoadImageFromFile
from mmpose.registry import TRANSFORMS
@TRANSFORMS.register_module()
class LoadImage(LoadImageFromFile):
"""Load an image from file or from the np.ndarray in ``results['img']``.
Required Keys:
- img_path
- img (optional)
Modified Keys:
- img
- img_shape
- ori_shape
- img_path (optional)
Args:
to_float32 (bool): Whether to convert the loaded image to a float32
numpy array. If set to False, the loaded image is an uint8 array.
Defaults to False.
color_type (str): The flag argument for :func:``mmcv.imfrombytes``.
Defaults to 'color'.
imdecode_backend (str): The image decoding backend type. The backend
argument for :func:``mmcv.imfrombytes``.
See :func:``mmcv.imfrombytes`` for details.
Defaults to 'cv2'.
backend_args (dict, optional): Arguments to instantiate the preifx of
uri corresponding backend. Defaults to None.
ignore_empty (bool): Whether to allow loading empty image or file path
not existent. Defaults to False.
"""
def transform(self, results: dict) -> Optional[dict]:
"""The transform function of :class:`LoadImage`.
Args:
results (dict): The result dict
Returns:
dict: The result dict.
"""
if 'img' not in results:
# Load image from file by :meth:`LoadImageFromFile.transform`
results = super().transform(results)
else:
img = results['img']
assert isinstance(img, np.ndarray)
if self.to_float32:
img = img.astype(np.float32)
if 'img_path' not in results:
results['img_path'] = None
results['img_shape'] = img.shape[:2]
results['ori_shape'] = img.shape[:2]
return results
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