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https://github.com/PaddlePaddle/PaddleClas.git
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1f8cfbd69d
Fix RandomErasing, RandAugment to be consistent with Timm and compatible with earlier PaddleClas. Add ColorJitter implemented by PaddleVision and TimmAutoAugment borrowed from Timm Lib.
91 lines
3.0 KiB
Python
91 lines
3.0 KiB
Python
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#This code is adapted from https://github.com/zhunzhong07/Random-Erasing, and refer to Timm.
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from functools import partial
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import math
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import random
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import numpy as np
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class Pixels(object):
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def __init__(self, mode="const", mean=[0., 0., 0.]):
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self._mode = mode
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self._mean = mean
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def __call__(self, h=224, w=224, c=3):
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if self._mode == "rand":
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return np.random.normal(size=(1, 1, 3))
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elif self._mode == "pixel":
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return np.random.normal(size=(h, w, c))
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elif self._mode == "const":
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return self._mean
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else:
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raise Exception(
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"Invalid mode in RandomErasing, only support \"const\", \"rand\", \"pixel\""
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)
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class RandomErasing(object):
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"""RandomErasing.
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"""
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def __init__(self,
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EPSILON=0.5,
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sl=0.02,
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sh=0.4,
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r1=0.3,
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mean=[0., 0., 0.],
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attempt=100,
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use_log_aspect=False,
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mode='const'):
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self.EPSILON = eval(EPSILON) if isinstance(EPSILON, str) else EPSILON
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self.sl = eval(sl) if isinstance(sl, str) else sl
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self.sh = eval(sh) if isinstance(sh, str) else sh
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r1 = eval(r1) if isinstance(r1, str) else r1
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self.r1 = (math.log(r1), math.log(1 / r1)) if use_log_aspect else (
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r1, 1 / r1)
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self.use_log_aspect = use_log_aspect
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self.attempt = attempt
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self.get_pixels = Pixels(mode, mean)
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def __call__(self, img):
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if random.random() > self.EPSILON:
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return img
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for _ in range(self.attempt):
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area = img.shape[0] * img.shape[1]
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target_area = random.uniform(self.sl, self.sh) * area
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aspect_ratio = random.uniform(*self.r1)
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if self.use_log_aspect:
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aspect_ratio = math.exp(aspect_ratio)
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h = int(round(math.sqrt(target_area * aspect_ratio)))
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w = int(round(math.sqrt(target_area / aspect_ratio)))
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if w < img.shape[1] and h < img.shape[0]:
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pixels = self.get_pixels(h, w, img.shape[2])
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x1 = random.randint(0, img.shape[0] - h)
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y1 = random.randint(0, img.shape[1] - w)
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if img.shape[2] == 3:
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img[x1:x1 + h, y1:y1 + w, :] = pixels
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else:
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img[x1:x1 + h, y1:y1 + w, 0] = pixels[0]
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return img
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return img
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