# coding=utf-8
# Copyright 2021 The HuggingFace Inc. team.
#
# 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.

import base64
import logging
import os
from io import BytesIO
from typing import TYPE_CHECKING, Dict, Iterable, List, Optional, Tuple, Union

import PIL
import numpy as np
import requests
from packaging import version


def _is_numpy(x):
    return isinstance(x, np.ndarray)


def is_numpy_array(x):
    """
    Tests if `x` is a numpy array or not.
    """
    return _is_numpy(x)


def is_pil_image(img):
    return isinstance(img, PIL.Image.Image)


def is_valid_image(img):
    return is_pil_image(img) or is_numpy_array(img)


def valid_images(imgs):
    # If we have an list of images, make sure every image is valid
    if isinstance(imgs, (list, tuple)):
        for img in imgs:
            if not valid_images(img):
                return False
    # If not a list of tuple, we have been given a single image or batched tensor of images
    elif not is_valid_image(imgs):
        return False
    return True


def is_batched(img):
    if isinstance(img, (list, tuple)):
        return is_valid_image(img[0])
    return False


def is_scaled_image(image: np.ndarray) -> bool:
    """
    Checks to see whether the pixel values have already been rescaled to [0, 1].
    """
    if image.dtype == np.uint8:
        return False

    # It's possible the image has pixel values in [0, 255] but is of floating type
    return np.min(image) >= 0 and np.max(image) <= 1


def make_batched_images(images):
    """
    Accepts images in list or nested list format, and makes a list of images for preprocessing.

    Args:
        images (`Union[List[List[ImageInput]], List[ImageInput], ImageInput]`):
            The input image.

    Returns:
        list: A list of images.
    """
    if (
        isinstance(images, (list, tuple))
        and isinstance(images[0], (list, tuple))
        and is_valid_image(images[0][0])
    ):
        return [img for img_list in images for img in img_list]

    elif isinstance(images, (list, tuple)) and is_valid_image(images[0]):
        return images

    elif is_valid_image(images):
        return [images]

    raise ValueError(f"Could not make batched video from {images}")