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PaddleClas/ppcls/data/preprocess/ops/randaugment.py

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# Copyright (c) 2021 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/heartInsert/randaugment
# reference: https://arxiv.org/abs/1909.13719
import random
from .operators import RawColorJitter
from paddle.vision.transforms import transforms as T
import numpy as np
from PIL import Image, ImageEnhance, ImageOps
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 cutout(image, pad_size, replace=0):
image_np = np.array(image)
image_height, image_width, _ = image_np.shape
# Sample the center location in the image where the zero mask will be applied.
cutout_center_height = np.random.randint(0, image_height + 1)
cutout_center_width = np.random.randint(0, image_width + 1)
lower_pad = np.maximum(0, cutout_center_height - pad_size)
upper_pad = np.maximum(0, image_height - cutout_center_height - pad_size)
left_pad = np.maximum(0, cutout_center_width - pad_size)
right_pad = np.maximum(0, image_width - cutout_center_width - pad_size)
cutout_shape = [
image_height - (lower_pad + upper_pad),
image_width - (left_pad + right_pad)
]
padding_dims = [[lower_pad, upper_pad], [left_pad, right_pad]]
mask = np.pad(np.zeros(
cutout_shape, dtype=image_np.dtype),
padding_dims,
constant_values=1)
mask = np.expand_dims(mask, -1)
mask = np.tile(mask, [1, 1, 3])
image_np = np.where(
np.equal(mask, 0),
np.full_like(
image_np, fill_value=replace, dtype=image_np.dtype),
image_np)
return Image.fromarray(image_np)
class RandAugment(object):
def __init__(self, num_layers=2, magnitude=5, fillcolor=(128, 128, 128)):
self.num_layers = num_layers
self.magnitude = magnitude
self.max_level = 10
abso_level = self.magnitude / self.max_level
self.level_map = {
"shearX": 0.3 * abso_level,
"shearY": 0.3 * abso_level,
"translateX": 150.0 / 331 * abso_level,
"translateY": 150.0 / 331 * abso_level,
"rotate": 30 * abso_level,
"color": 0.9 * abso_level,
"posterize": int(4.0 * abso_level),
"solarize": 256.0 * abso_level,
"contrast": 0.9 * abso_level,
"sharpness": 0.9 * abso_level,
"brightness": 0.9 * abso_level,
"autocontrast": 0,
"equalize": 0,
"invert": 0
}
# 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)
rnd_ch_op = random.choice
self.func = {
"shearX": lambda img, magnitude: img.transform(
img.size,
Image.AFFINE,
(1, magnitude * rnd_ch_op([-1, 1]), 0, 0, 1, 0),
Image.BICUBIC,
fillcolor=fillcolor),
"shearY": lambda img, magnitude: img.transform(
img.size,
Image.AFFINE,
(1, 0, 0, magnitude * rnd_ch_op([-1, 1]), 1, 0),
Image.BICUBIC,
fillcolor=fillcolor),
"translateX": lambda img, magnitude: img.transform(
img.size,
Image.AFFINE,
(1, 0, magnitude * img.size[0] * rnd_ch_op([-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] * rnd_ch_op([-1, 1])),
fillcolor=fillcolor),
"rotate": lambda img, magnitude: rotate_with_fill(img, magnitude),
"color": lambda img, magnitude: ImageEnhance.Color(img).enhance(
1 + magnitude * rnd_ch_op([-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 * rnd_ch_op([-1, 1])),
"sharpness": lambda img, magnitude:
ImageEnhance.Sharpness(img).enhance(
1 + magnitude * rnd_ch_op([-1, 1])),
"brightness": lambda img, magnitude:
ImageEnhance.Brightness(img).enhance(
1 + magnitude * rnd_ch_op([-1, 1])),
"autocontrast": lambda img, _:
ImageOps.autocontrast(img),
"equalize": lambda img, _: ImageOps.equalize(img),
"invert": lambda img, _: ImageOps.invert(img)
}
def __call__(self, img):
avaiable_op_names = list(self.level_map.keys())
for layer_num in range(self.num_layers):
op_name = np.random.choice(avaiable_op_names)
img = self.func[op_name](img, self.level_map[op_name])
return img
class RandomApply(object):
def __init__(self, p, transforms):
self.p = p
ts = []
for t in transforms:
for key in t.keys():
ts.append(eval(key)(**t[key]))
self.trans = T.Compose(ts)
def __call__(self, img):
if self.p < np.random.rand(1):
return img
timg = self.trans(img)
return timg
## RandAugment_EfficientNetV2 code below ##
class RandAugmentV2(RandAugment):
"""Customed RandAugment for EfficientNetV2"""
def __init__(self,
num_layers=2,
magnitude=5,
progress_magnitude=None,
fillcolor=(128, 128, 128)):
super().__init__(num_layers, magnitude, fillcolor)
self.progress_magnitude = progress_magnitude
abso_level = self.magnitude / self.max_level
self.level_map = {
"shearX": 0.3 * abso_level,
"shearY": 0.3 * abso_level,
"translateX": 100.0 * abso_level,
"translateY": 100.0 * abso_level,
"rotate": 30 * abso_level,
"color": 1.8 * abso_level + 0.1,
"posterize": int(4.0 * abso_level),
"solarize": int(256.0 * abso_level),
"solarize_add": int(110.0 * abso_level),
"contrast": 1.8 * abso_level + 0.1,
"sharpness": 1.8 * abso_level + 0.1,
"brightness": 1.8 * abso_level + 0.1,
"autocontrast": 0,
"equalize": 0,
"invert": 0,
"cutout": int(40 * abso_level)
}
# 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)
rnd_ch_op = random.choice
self.func = {
"shearX": lambda img, magnitude: img.transform(
img.size,
Image.AFFINE,
(1, magnitude * rnd_ch_op([-1, 1]), 0, 0, 1, 0),
Image.NEAREST,
fillcolor=fillcolor),
"shearY": lambda img, magnitude: img.transform(
img.size,
Image.AFFINE,
(1, 0, 0, magnitude * rnd_ch_op([-1, 1]), 1, 0),
Image.NEAREST,
fillcolor=fillcolor),
"translateX": lambda img, magnitude: img.transform(
img.size,
Image.AFFINE,
(1, 0, magnitude * rnd_ch_op([-1, 1]), 0, 1, 0),
Image.NEAREST,
fillcolor=fillcolor),
"translateY": lambda img, magnitude: img.transform(
img.size,
Image.AFFINE,
(1, 0, 0, 0, 1, magnitude * rnd_ch_op([-1, 1])),
Image.NEAREST,
fillcolor=fillcolor),
"rotate": lambda img, magnitude: rotate_with_fill(img, magnitude * rnd_ch_op([-1, 1])),
"color": lambda img, magnitude: ImageEnhance.Color(img).enhance(magnitude),
"posterize": lambda img, magnitude:
ImageOps.posterize(img, magnitude),
"solarize": lambda img, magnitude:
ImageOps.solarize(img, magnitude),
"solarize_add": lambda img, magnitude:
solarize_add(img, magnitude),
"contrast": lambda img, magnitude:
ImageEnhance.Contrast(img).enhance(magnitude),
"sharpness": lambda img, magnitude:
ImageEnhance.Sharpness(img).enhance(magnitude),
"brightness": lambda img, magnitude:
ImageEnhance.Brightness(img).enhance(magnitude),
"autocontrast": lambda img, _:
ImageOps.autocontrast(img),
"equalize": lambda img, _: ImageOps.equalize(img),
"invert": lambda img, _: ImageOps.invert(img),
"cutout": lambda img, magnitude: cutout(img, magnitude, replace=fillcolor[0])
}
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