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