Ë
    –\;j_  ã                   ó8   — d dl mZ d dlmZ g Zdad„ Zd„ Zdd„Zy)	é    )ÚImage)Ú
try_importÚpilc                 ó,   — | dvrt        d| › �«      ‚| ay)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]))
            <class 'PIL.Image.Image'>

            >>> # 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]))
            <class 'numpy.ndarray'>

            >>> shutil.rmtree(temp_dir)
    ©r   Úcv2Útensorú>Expected backend are one of ['pil', 'cv2', 'tensor'], but got N)Ú
ValueErrorÚ_image_backend)Úbackends    ú\G:\00. PROJECTS\API\Inventory\templateJSON\kerjaOCR\Lib\site-packages\paddle/vision/image.pyÚset_image_backendr      s,   € ðx Ð.Ñ.ÜØLÈWÈIÐVó
ð 	
ð �Nó    c                  ó   — t         S )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

    )r   © r   r   Úget_image_backendr   [   s
   € ô$ Ðr   Nc                 ó®   — |€t         }|dvrt        d|› �«      ‚|dk(  rt        j                  | «      S |dk(  rt	        d«      }|j                  | «      S y)ab  Load 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')

            >>> print(type(pil_img))
            <class 'PIL.Image.Image'>

            >>> # use opencv as backend
            >>> set_image_backend('cv2')

            >>> np_img = image_load(path)
            >>> print(type(np_img))
            <class 'numpy.ndarray'>

    Nr   r
   r   r   )r   r   r   Úopenr   Úimread)Úpathr   r   s      r   Ú
image_loadr   p   sn   € ðR €Ü ˆØÐ.Ñ.ÜØLÈWÈIÐVó
ð 	
ð �%ÒÜ�z‰z˜$ÓÐØ	�EÒ	Ü˜ÓˆØ�z‰z˜$ÓÐð 
r   )N)	ÚPILr   Úpaddle.utilsr   Ú__all__r   r   r   r   r   r   r   Ú<module>r      s(   ðõ å #à
€à€ò@òFô*4 r   