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63 lines
2.3 KiB
Python
63 lines
2.3 KiB
Python
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
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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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import numpy as np
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import random
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import cv2
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class DatasetSampler(object):
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def __init__(self, config):
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self.image_home = config["StyleSampler"]["image_home"]
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label_file = config["StyleSampler"]["label_file"]
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self.dataset_with_label = config["StyleSampler"]["with_label"]
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self.height = config["Global"]["image_height"]
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self.index = 0
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with open(label_file, "r") as f:
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label_raw = f.read()
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self.path_label_list = label_raw.split("\n")[:-1]
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assert len(self.path_label_list) > 0
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random.shuffle(self.path_label_list)
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def sample(self):
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if self.index >= len(self.path_label_list):
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random.shuffle(self.path_label_list)
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self.index = 0
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if self.dataset_with_label:
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path_label = self.path_label_list[self.index]
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rel_image_path, label = path_label.split('\t')
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else:
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rel_image_path = self.path_label_list[self.index]
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label = None
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img_path = "{}/{}".format(self.image_home, rel_image_path)
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image = cv2.imread(img_path)
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origin_height = image.shape[0]
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ratio = self.height / origin_height
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width = int(image.shape[1] * ratio)
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height = int(image.shape[0] * ratio)
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image = cv2.resize(image, (width, height))
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self.index += 1
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if label:
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return {"image": image, "label": label}
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else:
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return {"image": image}
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def duplicate_image(image, width):
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image_width = image.shape[1]
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dup_num = width // image_width + 1
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image = np.tile(image, reps=[1, dup_num, 1])
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cropped_image = image[:, :width, :]
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return cropped_image
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