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 os | |
| import numpy as np | |
| import cv2 | |
| from utils.config import ArgsParser, load_config, override_config | |
| from utils.logging import get_logger | |
| from engine import style_samplers, corpus_generators, text_drawers, predictors, writers | |
| class ImageSynthesiser(object): | |
| def __init__(self): | |
| self.FLAGS = ArgsParser().parse_args() | |
| self.config = load_config(self.FLAGS.config) | |
| self.config = override_config(self.config, options=self.FLAGS.override) | |
| self.output_dir = self.config["Global"]["output_dir"] | |
| if not os.path.exists(self.output_dir): | |
| os.mkdir(self.output_dir) | |
| self.logger = get_logger( | |
| log_file='{}/predict.log'.format(self.output_dir)) | |
| self.text_drawer = text_drawers.StdTextDrawer(self.config) | |
| predictor_method = self.config["Predictor"]["method"] | |
| assert predictor_method is not None | |
| self.predictor = getattr(predictors, predictor_method)(self.config) | |
| def synth_image(self, corpus, style_input, language="en"): | |
| corpus_list, text_input_list = self.text_drawer.draw_text( | |
| corpus, language, style_input_width=style_input.shape[1]) | |
| synth_result = self.predictor.predict(style_input, text_input_list) | |
| return synth_result | |
| class DatasetSynthesiser(ImageSynthesiser): | |
| def __init__(self): | |
| super(DatasetSynthesiser, self).__init__() | |
| self.tag = self.FLAGS.tag | |
| self.output_num = self.config["Global"]["output_num"] | |
| corpus_generator_method = self.config["CorpusGenerator"]["method"] | |
| self.corpus_generator = getattr(corpus_generators, | |
| corpus_generator_method)(self.config) | |
| style_sampler_method = self.config["StyleSampler"]["method"] | |
| assert style_sampler_method is not None | |
| self.style_sampler = style_samplers.DatasetSampler(self.config) | |
| self.writer = writers.SimpleWriter(self.config, self.tag) | |
| def synth_dataset(self): | |
| for i in range(self.output_num): | |
| style_data = self.style_sampler.sample() | |
| style_input = style_data["image"] | |
| corpus_language, text_input_label = self.corpus_generator.generate() | |
| text_input_label_list, text_input_list = self.text_drawer.draw_text( | |
| text_input_label, | |
| corpus_language, | |
| style_input_width=style_input.shape[1]) | |
| text_input_label = "".join(text_input_label_list) | |
| synth_result = self.predictor.predict(style_input, text_input_list) | |
| fake_fusion = synth_result["fake_fusion"] | |
| self.writer.save_image(fake_fusion, text_input_label) | |
| self.writer.save_label() | |
| self.writer.merge_label() | |