# 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): 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, fillcolor=(128, 128, 128)): super().__init__(num_layers, magnitude, fillcolor) abso_level = self.magnitude / self.max_level # [5.0~10.0/10.0]=[0.5, 1.0] 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) } 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]) }