|jUddlmZddlmZmZmZmZddlmZddl m Z ddl m Z er:ddl mZddlmZddlmZedZd ed <eeeejefZd ed <gZd ad ed <ddZddZ dddZdS)) annotations) TYPE_CHECKINGAnyLiteralUnion)Image) TypeAlias) try_importN)Tensorpilcv2tensorr _ImageBackend_ImageDataTyper _image_backendbackendreturnNonec6|dvrtd||adS)ab Specifies the backend used to load images in class :ref:`api_paddle_datasets_ImageFolder` and :ref:`api_paddle_datasets_DatasetFolder` . Now support backends are pillow and opencv. If backend not set, will use 'pil' as default. Args: backend (str): Name of the image load backend, should be one of {'pil', 'cv2'}. Examples: .. code-block:: python >>> import os >>> import shutil >>> import tempfile >>> import numpy as np >>> from PIL import Image >>> from paddle.vision import DatasetFolder >>> from paddle.vision import set_image_backend >>> set_image_backend('pil') >>> def make_fake_dir(): ... data_dir = tempfile.mkdtemp() ... ... for i in range(2): ... sub_dir = os.path.join(data_dir, 'class_' + str(i)) ... if not os.path.exists(sub_dir): ... os.makedirs(sub_dir) ... for j in range(2): ... fake_img = Image.fromarray((np.random.random((32, 32, 3)) * 255).astype('uint8')) ... fake_img.save(os.path.join(sub_dir, str(j) + '.png')) ... return data_dir >>> temp_dir = make_fake_dir() >>> pil_data_folder = DatasetFolder(temp_dir) >>> for items in pil_data_folder: ... break >>> print(type(items[0])) >>> # use opencv as backend >>> set_image_backend('cv2') >>> cv2_data_folder = DatasetFolder(temp_dir) >>> for items in cv2_data_folder: ... break >>> print(type(items[0])) >>> shutil.rmtree(temp_dir) r >Expected backend are one of ['pil', 'cv2', 'tensor'], but got N) ValueErrorr)rs c/lsinfo/ai/hellotax_ai/data_center/backend/venv/lib/python3.11/site-packages/paddle/vision/image.pyset_image_backendr&s9x... VW V V   NNNctS)a7 Gets the name of the package used to load images Returns: str: backend of image load. Examples: .. code-block:: python >>> from paddle.vision import get_image_backend >>> backend = get_image_backend() >>> print(backend) pil )rrrget_image_backendris $ rpathstr_ImageBackend | None_ImageDataType | Nonec|t}|dvrtd||dkrtj|S|dkr$t d}||SdS)arLoad an image. Args: path (str): Path of the image. backend (str, optional): The image decoding backend type. Options are `cv2`, `pil`, `None`. If backend is None, the global _imread_backend specified by :ref:`api_paddle_vision_set_image_backend` will be used. Default: None. Returns: PIL.Image or np.array: Loaded image. Examples: .. code-block:: python >>> import numpy as np >>> from PIL import Image >>> from paddle.vision import image_load, set_image_backend >>> fake_img = Image.fromarray((np.random.random((32, 32, 3)) * 255).astype('uint8')) >>> path = 'temp.png' >>> fake_img.save(path) >>> set_image_backend('pil') >>> pil_img = image_load(path).convert('RGB') # type: ignore >>> print(type(pil_img)) >>> # use opencv as backend >>> set_image_backend('cv2') >>> np_img = image_load(path) >>> print(type(np_img)) Nr rr r)rrropenr imread)rrrs r image_loadr&~sV ... VW V V   %z$ E  zz$  r)rrrr)rr)N)rr rr!rr") __future__rtypingrrrrPILrtyping_extensionsr paddle.utilsr numpy.typingnpt PIL.ImagePILImagepaddler r__annotations__NDArrayr__all__rrrr&rrrr4s[#""""""555555555555''''''######J++++++&'=>M>>>> %fh C8H&H INIIII  %%%%%@@@@F,046 6 6 6 6 6 6 r