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- # copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
- #
- # 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.
- import math
- import cv2
- import numpy as np
- import random
- from PIL import Image
- from .rec_img_aug import resize_norm_img
- class SSLRotateResize(object):
- def __init__(
- self, image_shape, padding=False, select_all=True, mode="train", **kwargs
- ):
- self.image_shape = image_shape
- self.padding = padding
- self.select_all = select_all
- self.mode = mode
- def __call__(self, data):
- img = data["image"]
- data["image_r90"] = cv2.rotate(img, cv2.ROTATE_90_CLOCKWISE)
- data["image_r180"] = cv2.rotate(data["image_r90"], cv2.ROTATE_90_CLOCKWISE)
- data["image_r270"] = cv2.rotate(data["image_r180"], cv2.ROTATE_90_CLOCKWISE)
- images = []
- for key in ["image", "image_r90", "image_r180", "image_r270"]:
- images.append(
- resize_norm_img(
- data.pop(key), image_shape=self.image_shape, padding=self.padding
- )[0]
- )
- data["image"] = np.stack(images, axis=0)
- data["label"] = np.array(list(range(4)))
- if not self.select_all:
- data["image"] = data["image"][0::2] # just choose 0 and 180
- data["label"] = data["label"][0:2] # label needs to be continuous
- if self.mode == "test":
- data["image"] = data["image"][0]
- data["label"] = data["label"][0]
- return data
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