pytorch-image-models/timm/data/auto_augment.py

""" Auto Augment
Implementation adapted from:
    https://github.com/tensorflow/tpu/blob/master/models/official/efficientnet/autoaugment.py
Papers: https://arxiv.org/abs/1805.09501 and https://arxiv.org/abs/1906.11172

Hacked together by Ross Wightman
"""
import random
import math
from PIL import Image, ImageOps, ImageEnhance
import PIL
import numpy as np


_PIL_VER = tuple([int(x) for x in PIL.__version__.split('.')[:2]])

_FILL = (128, 128, 128)

# This signifies the max integer that the controller RNN could predict for the
# augmentation scheme.
_MAX_LEVEL = 10.

_HPARAMS_DEFAULT = dict(
    translate_const=250,
    img_mean=_FILL,
)

_RANDOM_INTERPOLATION = (Image.NEAREST, Image.BILINEAR, Image.BICUBIC)


def _interpolation(kwargs):
    interpolation = kwargs.pop('resample', Image.NEAREST)
    if isinstance(interpolation, (list, tuple)):
        return random.choice(interpolation)
    else:
        return interpolation


def _check_args_tf(kwargs):
    if 'fillcolor' in kwargs and _PIL_VER < (5, 0):
        kwargs.pop('fillcolor')
    kwargs['resample'] = _interpolation(kwargs)


def shear_x(img, factor, **kwargs):
    _check_args_tf(kwargs)
    return img.transform(img.size, Image.AFFINE, (1, factor, 0, 0, 1, 0), **kwargs)


def shear_y(img, factor, **kwargs):
    _check_args_tf(kwargs)
    return img.transform(img.size, Image.AFFINE, (1, 0, 0, factor, 1, 0), **kwargs)


def translate_x_rel(img, pct, **kwargs):
    pixels = pct * img.size[0]
    _check_args_tf(kwargs)
    return img.transform(img.size, Image.AFFINE, (1, 0, pixels, 0, 1, 0), **kwargs)


def translate_y_rel(img, pct, **kwargs):
    pixels = pct * img.size[1]
    _check_args_tf(kwargs)
    return img.transform(img.size, Image.AFFINE, (1, 0, 0, 0, 1, pixels), **kwargs)


def translate_x_abs(img, pixels, **kwargs):
    _check_args_tf(kwargs)
    return img.transform(img.size, Image.AFFINE, (1, 0, pixels, 0, 1, 0), **kwargs)


def translate_y_abs(img, pixels, **kwargs):
    _check_args_tf(kwargs)
    return img.transform(img.size, Image.AFFINE, (1, 0, 0, 0, 1, pixels), **kwargs)


def rotate(img, degrees, **kwargs):
    _check_args_tf(kwargs)
    if _PIL_VER >= (5, 2):
        return img.rotate(degrees, **kwargs)
    elif _PIL_VER >= (5, 0):
        w, h = img.size
        post_trans = (0, 0)
        rotn_center = (w / 2.0, h / 2.0)
        angle = -math.radians(degrees)
        matrix = [
            round(math.cos(angle), 15),
            round(math.sin(angle), 15),
            0.0,
            round(-math.sin(angle), 15),
            round(math.cos(angle), 15),
            0.0,
        ]

        def transform(x, y, matrix):
            (a, b, c, d, e, f) = matrix
            return a * x + b * y + c, d * x + e * y + f

        matrix[2], matrix[5] = transform(
            -rotn_center[0] - post_trans[0], -rotn_center[1] - post_trans[1], matrix
        )
        matrix[2] += rotn_center[0]
        matrix[5] += rotn_center[1]
        return img.transform(img.size, Image.AFFINE, matrix, **kwargs)
    else:
        return img.rotate(degrees, resample=kwargs['resample'])


def auto_contrast(img, **__):
    return ImageOps.autocontrast(img)


def invert(img, **__):
    return ImageOps.invert(img)


def equalize(img, **__):
    return ImageOps.equalize(img)


def solarize(img, thresh, **__):
    return ImageOps.solarize(img, thresh)


def solarize_add(img, add, thresh=128, **__):
    lut = []
    for i in range(256):
        if i < thresh:
            lut.append(min(255, i + add))
        else:
            lut.append(i)
    if img.mode in ("L", "RGB"):
        if img.mode == "RGB" and len(lut) == 256:
            lut = lut + lut + lut
        return img.point(lut)
    else:
        return img


def posterize(img, bits_to_keep, **__):
    if bits_to_keep >= 8:
        return img
    bits_to_keep = max(1, bits_to_keep)  # prevent all 0 images
    return ImageOps.posterize(img, bits_to_keep)


def contrast(img, factor, **__):
    return ImageEnhance.Contrast(img).enhance(factor)


def color(img, factor, **__):
    return ImageEnhance.Color(img).enhance(factor)


def brightness(img, factor, **__):
    return ImageEnhance.Brightness(img).enhance(factor)


def sharpness(img, factor, **__):
    return ImageEnhance.Sharpness(img).enhance(factor)


def _randomly_negate(v):
    """With 50% prob, negate the value"""
    return -v if random.random() > 0.5 else v


def _rotate_level_to_arg(level):
    # range [-30, 30]
    level = (level / _MAX_LEVEL) * 30.
    level = _randomly_negate(level)
    return (level,)


def _enhance_level_to_arg(level):
    # range [0.1, 1.9]
    return ((level / _MAX_LEVEL) * 1.8 + 0.1,)


def _shear_level_to_arg(level):
    # range [-0.3, 0.3]
    level = (level / _MAX_LEVEL) * 0.3
    level = _randomly_negate(level)
    return (level,)


def _translate_abs_level_to_arg(level, translate_const):
    level = (level / _MAX_LEVEL) * float(translate_const)
    level = _randomly_negate(level)
    return (level,)


def _translate_rel_level_to_arg(level):
    # range [-0.45, 0.45]
    level = (level / _MAX_LEVEL) * 0.45
    level = _randomly_negate(level)
    return (level,)


def level_to_arg(hparams):
    return {
        'AutoContrast': lambda level: (),
        'Equalize': lambda level: (),
        'Invert': lambda level: (),
        'Rotate': _rotate_level_to_arg,
        # FIXME these are both different from original impl as I believe there is a bug,
        # not sure what is the correct alternative, hence 2 options that look better
        'Posterize': lambda level: (int((level / _MAX_LEVEL) * 4) + 4,),  # range [4, 8]
        'Posterize2': lambda level: (4 - int((level / _MAX_LEVEL) * 4),),  # range [4, 0]
        'Solarize': lambda level: (int((level / _MAX_LEVEL) * 256),),  # range [0, 256]
        'SolarizeAdd': lambda level: (int((level / _MAX_LEVEL) * 110),),  # range [0, 110]
        'Color': _enhance_level_to_arg,
        'Contrast': _enhance_level_to_arg,
        'Brightness': _enhance_level_to_arg,
        'Sharpness': _enhance_level_to_arg,
        'ShearX': _shear_level_to_arg,
        'ShearY': _shear_level_to_arg,
        'TranslateX': lambda level: _translate_abs_level_to_arg(level, hparams['translate_const']),
        'TranslateY': lambda level: _translate_abs_level_to_arg(level, hparams['translate_const']),
        'TranslateXRel': lambda level: _translate_rel_level_to_arg(level),
        'TranslateYRel': lambda level: _translate_rel_level_to_arg(level),
    }


NAME_TO_OP = {
    'AutoContrast': auto_contrast,
    'Equalize': equalize,
    'Invert': invert,
    'Rotate': rotate,
    'Posterize': posterize,
    'Posterize2': posterize,
    'Solarize': solarize,
    'SolarizeAdd': solarize_add,
    'Color': color,
    'Contrast': contrast,
    'Brightness': brightness,
    'Sharpness': sharpness,
    'ShearX': shear_x,
    'ShearY': shear_y,
    'TranslateX': translate_x_abs,
    'TranslateY': translate_y_abs,
    'TranslateXRel': translate_x_rel,
    'TranslateYRel': translate_y_rel,
}


class AutoAugmentOp:

    def __init__(self, name, prob, magnitude, hparams={}):
        self.aug_fn = NAME_TO_OP[name]
        self.level_fn = level_to_arg(hparams)[name]
        self.prob = prob
        self.magnitude = magnitude
        # If std deviation of magnitude is > 0, we introduce some randomness
        # in the usually fixed policy and sample magnitude from normal dist
        # with mean magnitude and std-dev of magnitude_std.
        # NOTE This is being tested as it's not in paper or reference impl.
        self.magnitude_std = 0.5  # FIXME add arg/hparam
        self.kwargs = {
            'fillcolor': hparams['img_mean'] if 'img_mean' in hparams else _FILL,
            'resample': hparams['interpolation'] if 'interpolation' in hparams else _RANDOM_INTERPOLATION
        }

    def __call__(self, img):
        if self.prob < random.random():
            return img
        magnitude = self.magnitude
        if self.magnitude_std and self.magnitude_std > 0:
            magnitude = random.gauss(magnitude, self.magnitude_std)
        magnitude = min(_MAX_LEVEL, max(0, magnitude))
        level_args = self.level_fn(magnitude)
        return self.aug_fn(img, *level_args, **self.kwargs)


def auto_augment_policy_v0(hparams=_HPARAMS_DEFAULT):
    # ImageNet policy from TPU EfficientNet impl, cannot find
    # a paper reference.
    policy = [
        [('Equalize', 0.8, 1), ('ShearY', 0.8, 4)],
        [('Color', 0.4, 9), ('Equalize', 0.6, 3)],
        [('Color', 0.4, 1), ('Rotate', 0.6, 8)],
        [('Solarize', 0.8, 3), ('Equalize', 0.4, 7)],
        [('Solarize', 0.4, 2), ('Solarize', 0.6, 2)],
        [('Color', 0.2, 0), ('Equalize', 0.8, 8)],
        [('Equalize', 0.4, 8), ('SolarizeAdd', 0.8, 3)],
        [('ShearX', 0.2, 9), ('Rotate', 0.6, 8)],
        [('Color', 0.6, 1), ('Equalize', 1.0, 2)],
        [('Invert', 0.4, 9), ('Rotate', 0.6, 0)],
        [('Equalize', 1.0, 9), ('ShearY', 0.6, 3)],
        [('Color', 0.4, 7), ('Equalize', 0.6, 0)],
        [('Posterize', 0.4, 6), ('AutoContrast', 0.4, 7)],
        [('Solarize', 0.6, 8), ('Color', 0.6, 9)],
        [('Solarize', 0.2, 4), ('Rotate', 0.8, 9)],
        [('Rotate', 1.0, 7), ('TranslateYRel', 0.8, 9)],
        [('ShearX', 0.0, 0), ('Solarize', 0.8, 4)],
        [('ShearY', 0.8, 0), ('Color', 0.6, 4)],
        [('Color', 1.0, 0), ('Rotate', 0.6, 2)],
        [('Equalize', 0.8, 4), ('Equalize', 0.0, 8)],
        [('Equalize', 1.0, 4), ('AutoContrast', 0.6, 2)],
        [('ShearY', 0.4, 7), ('SolarizeAdd', 0.6, 7)],
        [('Posterize', 0.8, 2), ('Solarize', 0.6, 10)],
        [('Solarize', 0.6, 8), ('Equalize', 0.6, 1)],
        [('Color', 0.8, 6), ('Rotate', 0.4, 5)],
    ]
    pc = [[AutoAugmentOp(*a, hparams) for a in sp] for sp in policy]
    return pc


def auto_augment_policy_original(hparams=_HPARAMS_DEFAULT):
    # ImageNet policy from https://arxiv.org/abs/1805.09501
    policy = [
        [('Posterize', 0.4, 8), ('Rotate', 0.6, 9)],
        [('Solarize', 0.6, 5), ('AutoContrast', 0.6, 5)],
        [('Equalize', 0.8, 8), ('Equalize', 0.6, 3)],
        [('Posterize', 0.6, 7), ('Posterize', 0.6, 6)],
        [('Equalize', 0.4, 7), ('Solarize', 0.2, 4)],
        [('Equalize', 0.4, 4), ('Rotate', 0.8, 8)],
        [('Solarize', 0.6, 3), ('Equalize', 0.6, 7)],
        [('Posterize', 0.8, 5), ('Equalize', 1.0, 2)],
        [('Rotate', 0.2, 3), ('Solarize', 0.6, 8)],
        [('Equalize', 0.6, 8), ('Posterize', 0.4, 6)],
        [('Rotate', 0.8, 8), ('Color', 0.4, 0)],
        [('Rotate', 0.4, 9), ('Equalize', 0.6, 2)],
        [('Equalize', 0.0, 7), ('Equalize', 0.8, 8)],
        [('Invert', 0.6, 4), ('Equalize', 1.0, 8)],
        [('Color', 0.6, 4), ('Contrast', 1.0, 8)],
        [('Rotate', 0.8, 8), ('Color', 1.0, 2)],
        [('Color', 0.8, 8), ('Solarize', 0.8, 7)],
        [('Sharpness', 0.4, 7), ('Invert', 0.6, 8)],
        [('ShearX', 0.6, 5), ('Equalize', 1.0, 9)],
        [('Color', 0.4, 0), ('Equalize', 0.6, 3)],
        [('Equalize', 0.4, 7), ('Solarize', 0.2, 4)],
        [('Solarize', 0.6, 5), ('AutoContrast', 0.6, 5)],
        [('Invert', 0.6, 4), ('Equalize', 1.0, 8)],
        [('Color', 0.6, 4), ('Contrast', 1.0, 8)],
        [('Equalize', 0.8, 8), ('Equalize', 0.6, 3)],
    ]
    pc = [[AutoAugmentOp(*a, hparams) for a in sp] for sp in policy]
    return pc


def auto_augment_policy(name='v0', hparams=_HPARAMS_DEFAULT):
    if name == 'original':
        return auto_augment_policy_original(hparams)
    elif name == 'v0':
        return auto_augment_policy_v0(hparams)
    else:
        assert False, 'Unknown AA policy (%s)' % name


class AutoAugment:

    def __init__(self, policy):
        self.policy = policy

    def __call__(self, img):
        sub_policy = random.choice(self.policy)
        for op in sub_policy:
            img = op(img)
        return img