Spaces:
Runtime error
Runtime error
| # 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 | |