#   Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from __future__ import annotations

from typing import TYPE_CHECKING, Any, Literal, TypeAlias

from PIL import Image

from paddle.utils import try_import

if TYPE_CHECKING:
    import numpy.typing as npt
    from PIL.Image import Image as PILImage

    from paddle import Tensor

    _ImageBackend: TypeAlias = Literal["pil", "cv2", "tensor"]
    _ImageDataType: TypeAlias = Tensor | PILImage | npt.NDArray[Any]

__all__ = []

_image_backend: _ImageBackend = 'pil'


def set_image_backend(backend: _ImageBackend) -> None:
    """
    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:: pycon

            >>> 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)
    """
    global _image_backend
    if backend not in ['pil', 'cv2', 'tensor']:
        raise ValueError(
            f"Expected backend are one of ['pil', 'cv2', 'tensor'], but got {backend}"
        )
    _image_backend = backend


def get_image_backend() -> _ImageBackend:
    """
    Gets the name of the package used to load images

    Returns:
        str: backend of image load.

    Examples:

        .. code-block:: pycon

            >>> from paddle.vision import get_image_backend

            >>> backend = get_image_backend()
            >>> print(backend)
            pil

    """
    return _image_backend


def image_load(
    path: str, backend: _ImageBackend | None = None
) -> _ImageDataType | None:
    """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:: pycon

            >>> 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))
            <class 'PIL.Image.Image'>

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

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

    """

    if backend is None:
        backend = _image_backend
    if backend not in ['pil', 'cv2', 'tensor']:
        raise ValueError(
            f"Expected backend are one of ['pil', 'cv2', 'tensor'], but got {backend}"
        )

    if backend == 'pil':
        return Image.open(path)
    elif backend == 'cv2':
        cv2 = try_import('cv2')
        return cv2.imread(path)