# 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.

# This code is based on https://github.com/DeepVoltaire/AutoAugment/blob/master/autoaugment.py

from PIL import Image, ImageEnhance, ImageOps
import numpy as np
import random


class ImageNetPolicy(object):
    """ Randomly choose one of the best 24 Sub-policies on ImageNet.

        Example:
        >>> policy = ImageNetPolicy()
        >>> transformed = policy(image)

        Example as a PyTorch Transform:
        >>> transform=transforms.Compose([
        >>>     transforms.Resize(256),
        >>>     ImageNetPolicy(),
        >>>     transforms.ToTensor()])
    """

    def __init__(self, fillcolor=(128, 128, 128)):
        self.policies = [
            SubPolicy(0.4, "posterize", 8, 0.6, "rotate", 9, fillcolor),
            SubPolicy(0.6, "solarize", 5, 0.6, "autocontrast", 5, fillcolor),
            SubPolicy(0.8, "equalize", 8, 0.6, "equalize", 3, fillcolor),
            SubPolicy(0.6, "posterize", 7, 0.6, "posterize", 6, fillcolor),
            SubPolicy(0.4, "equalize", 7, 0.2, "solarize", 4, fillcolor),
            SubPolicy(0.4, "equalize", 4, 0.8, "rotate", 8, fillcolor),
            SubPolicy(0.6, "solarize", 3, 0.6, "equalize", 7, fillcolor),
            SubPolicy(0.8, "posterize", 5, 1.0, "equalize", 2, fillcolor),
            SubPolicy(0.2, "rotate", 3, 0.6, "solarize", 8, fillcolor),
            SubPolicy(0.6, "equalize", 8, 0.4, "posterize", 6, fillcolor),
            SubPolicy(0.8, "rotate", 8, 0.4, "color", 0, fillcolor),
            SubPolicy(0.4, "rotate", 9, 0.6, "equalize", 2, fillcolor),
            SubPolicy(0.0, "equalize", 7, 0.8, "equalize", 8, fillcolor),
            SubPolicy(0.6, "invert", 4, 1.0, "equalize", 8, fillcolor),
            SubPolicy(0.6, "color", 4, 1.0, "contrast", 8, fillcolor),
            SubPolicy(0.8, "rotate", 8, 1.0, "color", 2, fillcolor),
            SubPolicy(0.8, "color", 8, 0.8, "solarize", 7, fillcolor),
            SubPolicy(0.4, "sharpness", 7, 0.6, "invert", 8, fillcolor),
            SubPolicy(0.6, "shearX", 5, 1.0, "equalize", 9, fillcolor),
            SubPolicy(0.4, "color", 0, 0.6, "equalize", 3, fillcolor),
            SubPolicy(0.4, "equalize", 7, 0.2, "solarize", 4, fillcolor),
            SubPolicy(0.6, "solarize", 5, 0.6, "autocontrast", 5, fillcolor),
            SubPolicy(0.6, "invert", 4, 1.0, "equalize", 8, fillcolor),
            SubPolicy(0.6, "color", 4, 1.0, "contrast", 8, fillcolor),
            SubPolicy(0.8, "equalize", 8, 0.6, "equalize", 3, fillcolor)
        ]

    def __call__(self, img, policy_idx=None):
        if policy_idx is None or not isinstance(policy_idx, int):
            policy_idx = random.randint(0, len(self.policies) - 1)
        else:
            policy_idx = policy_idx % len(self.policies)
        return self.policies[policy_idx](img)

    def __repr__(self):
        return "AutoAugment ImageNet Policy"


class CIFAR10Policy(object):
    """ Randomly choose one of the best 25 Sub-policies on CIFAR10.

        Example:
        >>> policy = CIFAR10Policy()
        >>> transformed = policy(image)

        Example as a PyTorch Transform:
        >>> transform=transforms.Compose([
        >>>     transforms.Resize(256),
        >>>     CIFAR10Policy(),
        >>>     transforms.ToTensor()])
    """

    def __init__(self, fillcolor=(128, 128, 128)):
        self.policies = [
            SubPolicy(0.1, "invert", 7, 0.2, "contrast", 6, fillcolor),
            SubPolicy(0.7, "rotate", 2, 0.3, "translateX", 9, fillcolor),
            SubPolicy(0.8, "sharpness", 1, 0.9, "sharpness", 3, fillcolor),
            SubPolicy(0.5, "shearY", 8, 0.7, "translateY", 9, fillcolor),
            SubPolicy(0.5, "autocontrast", 8, 0.9, "equalize", 2, fillcolor),
            SubPolicy(0.2, "shearY", 7, 0.3, "posterize", 7, fillcolor),
            SubPolicy(0.4, "color", 3, 0.6, "brightness", 7, fillcolor),
            SubPolicy(0.3, "sharpness", 9, 0.7, "brightness", 9, fillcolor),
            SubPolicy(0.6, "equalize", 5, 0.5, "equalize", 1, fillcolor),
            SubPolicy(0.6, "contrast", 7, 0.6, "sharpness", 5, fillcolor),
            SubPolicy(0.7, "color", 7, 0.5, "translateX", 8, fillcolor),
            SubPolicy(0.3, "equalize", 7, 0.4, "autocontrast", 8, fillcolor),
            SubPolicy(0.4, "translateY", 3, 0.2, "sharpness", 6, fillcolor),
            SubPolicy(0.9, "brightness", 6, 0.2, "color", 8, fillcolor),
            SubPolicy(0.5, "solarize", 2, 0.0, "invert", 3, fillcolor),
            SubPolicy(0.2, "equalize", 0, 0.6, "autocontrast", 0, fillcolor),
            SubPolicy(0.2, "equalize", 8, 0.8, "equalize", 4, fillcolor),
            SubPolicy(0.9, "color", 9, 0.6, "equalize", 6, fillcolor),
            SubPolicy(0.8, "autocontrast", 4, 0.2, "solarize", 8, fillcolor),
            SubPolicy(0.1, "brightness", 3, 0.7, "color", 0, fillcolor),
            SubPolicy(0.4, "solarize", 5, 0.9, "autocontrast", 3, fillcolor),
            SubPolicy(0.9, "translateY", 9, 0.7, "translateY", 9, fillcolor),
            SubPolicy(0.9, "autocontrast", 2, 0.8, "solarize", 3, fillcolor),
            SubPolicy(0.8, "equalize", 8, 0.1, "invert", 3, fillcolor),
            SubPolicy(0.7, "translateY", 9, 0.9, "autocontrast", 1, fillcolor)
        ]

    def __call__(self, img, policy_idx=None):
        if policy_idx is None or not isinstance(policy_idx, int):
            policy_idx = random.randint(0, len(self.policies) - 1)
        else:
            policy_idx = policy_idx % len(self.policies)
        return self.policies[policy_idx](img)

    def __repr__(self):
        return "AutoAugment CIFAR10 Policy"


class SVHNPolicy(object):
    """ Randomly choose one of the best 25 Sub-policies on SVHN.

        Example:
        >>> policy = SVHNPolicy()
        >>> transformed = policy(image)

        Example as a PyTorch Transform:
        >>> transform=transforms.Compose([
        >>>     transforms.Resize(256),
        >>>     SVHNPolicy(),
        >>>     transforms.ToTensor()])
    """

    def __init__(self, fillcolor=(128, 128, 128)):
        self.policies = [
            SubPolicy(0.9, "shearX", 4, 0.2, "invert", 3, fillcolor),
            SubPolicy(0.9, "shearY", 8, 0.7, "invert", 5, fillcolor),
            SubPolicy(0.6, "equalize", 5, 0.6, "solarize", 6, fillcolor),
            SubPolicy(0.9, "invert", 3, 0.6, "equalize", 3, fillcolor),
            SubPolicy(0.6, "equalize", 1, 0.9, "rotate", 3, fillcolor),
            SubPolicy(0.9, "shearX", 4, 0.8, "autocontrast", 3, fillcolor),
            SubPolicy(0.9, "shearY", 8, 0.4, "invert", 5, fillcolor),
            SubPolicy(0.9, "shearY", 5, 0.2, "solarize", 6, fillcolor),
            SubPolicy(0.9, "invert", 6, 0.8, "autocontrast", 1, fillcolor),
            SubPolicy(0.6, "equalize", 3, 0.9, "rotate", 3, fillcolor),
            SubPolicy(0.9, "shearX", 4, 0.3, "solarize", 3, fillcolor),
            SubPolicy(0.8, "shearY", 8, 0.7, "invert", 4, fillcolor),
            SubPolicy(0.9, "equalize", 5, 0.6, "translateY", 6, fillcolor),
            SubPolicy(0.9, "invert", 4, 0.6, "equalize", 7, fillcolor),
            SubPolicy(0.3, "contrast", 3, 0.8, "rotate", 4, fillcolor),
            SubPolicy(0.8, "invert", 5, 0.0, "translateY", 2, fillcolor),
            SubPolicy(0.7, "shearY", 6, 0.4, "solarize", 8, fillcolor),
            SubPolicy(0.6, "invert", 4, 0.8, "rotate", 4, fillcolor),
            SubPolicy(
                0.3, "shearY", 7, 0.9, "translateX", 3, fillcolor), SubPolicy(
                    0.1, "shearX", 6, 0.6, "invert", 5, fillcolor), SubPolicy(
                        0.7, "solarize", 2, 0.6, "translateY", 7,
                        fillcolor), SubPolicy(0.8, "shearY", 4, 0.8, "invert",
                                              8, fillcolor), SubPolicy(
                                                  0.7, "shearX", 9, 0.8,
                                                  "translateY", 3,
                                                  fillcolor), SubPolicy(
                                                      0.8, "shearY", 5, 0.7,
                                                      "autocontrast", 3,
                                                      fillcolor),
            SubPolicy(0.7, "shearX", 2, 0.1, "invert", 5, fillcolor)
        ]

    def __call__(self, img, policy_idx=None):
        if policy_idx is None or not isinstance(policy_idx, int):
            policy_idx = random.randint(0, len(self.policies) - 1)
        else:
            policy_idx = policy_idx % len(self.policies)
        return self.policies[policy_idx](img)

    def __repr__(self):
        return "AutoAugment SVHN Policy"


class SubPolicy(object):
    def __init__(self,
                 p1,
                 operation1,
                 magnitude_idx1,
                 p2,
                 operation2,
                 magnitude_idx2,
                 fillcolor=(128, 128, 128)):
        ranges = {
            "shearX": np.linspace(0, 0.3, 10),
            "shearY": np.linspace(0, 0.3, 10),
            "translateX": np.linspace(0, 150 / 331, 10),
            "translateY": np.linspace(0, 150 / 331, 10),
            "rotate": np.linspace(0, 30, 10),
            "color": np.linspace(0.0, 0.9, 10),
            "posterize": np.round(np.linspace(8, 4, 10), 0).astype(np.int),
            "solarize": np.linspace(256, 0, 10),
            "contrast": np.linspace(0.0, 0.9, 10),
            "sharpness": np.linspace(0.0, 0.9, 10),
            "brightness": np.linspace(0.0, 0.9, 10),
            "autocontrast": [0] * 10,
            "equalize": [0] * 10,
            "invert": [0] * 10
        }

        # from https://stackoverflow.com/questions/5252170/specify-image-filling-color-when-rotating-in-python-with-pil-and-setting-expand
        def rotate_with_fill(img, magnitude):
            rot = img.convert("RGBA").rotate(magnitude)
            return Image.composite(rot,
                                   Image.new("RGBA", rot.size, (128, ) * 4),
                                   rot).convert(img.mode)

        func = {
            "shearX": lambda img, magnitude: img.transform(
                img.size, Image.AFFINE, (1, magnitude * random.choice([-1, 1]), 0, 0, 1, 0),
                Image.BICUBIC, fillcolor=fillcolor),
            "shearY": lambda img, magnitude: img.transform(
                img.size, Image.AFFINE, (1, 0, 0, magnitude * random.choice([-1, 1]), 1, 0),
                Image.BICUBIC, fillcolor=fillcolor),
            "translateX": lambda img, magnitude: img.transform(
                img.size, Image.AFFINE, (1, 0, magnitude * img.size[0] * random.choice([-1, 1]), 0, 1, 0),
                fillcolor=fillcolor),
            "translateY": lambda img, magnitude: img.transform(
                img.size, Image.AFFINE, (1, 0, 0, 0, 1, magnitude * img.size[1] * random.choice([-1, 1])),
                fillcolor=fillcolor),
            "rotate": lambda img, magnitude: rotate_with_fill(img, magnitude),
            # "rotate": lambda img, magnitude: img.rotate(magnitude * random.choice([-1, 1])),
            "color": lambda img, magnitude: ImageEnhance.Color(img).enhance(1 + magnitude * random.choice([-1, 1])),
            "posterize": lambda img, magnitude: ImageOps.posterize(img, magnitude),
            "solarize": lambda img, magnitude: ImageOps.solarize(img, magnitude),
            "contrast": lambda img, magnitude: ImageEnhance.Contrast(img).enhance(
                1 + magnitude * random.choice([-1, 1])),
            "sharpness": lambda img, magnitude: ImageEnhance.Sharpness(img).enhance(
                1 + magnitude * random.choice([-1, 1])),
            "brightness": lambda img, magnitude: ImageEnhance.Brightness(img).enhance(
                1 + magnitude * random.choice([-1, 1])),
            "autocontrast": lambda img, magnitude: ImageOps.autocontrast(img),
            "equalize": lambda img, magnitude: ImageOps.equalize(img),
            "invert": lambda img, magnitude: ImageOps.invert(img)
        }

        self.p1 = p1
        self.operation1 = func[operation1]
        self.magnitude1 = ranges[operation1][magnitude_idx1]
        self.p2 = p2
        self.operation2 = func[operation2]
        self.magnitude2 = ranges[operation2][magnitude_idx2]

    def __call__(self, img):
        if random.random() < self.p1:
            img = self.operation1(img, self.magnitude1)
        if random.random() < self.p2:
            img = self.operation2(img, self.magnitude2)
        return img
