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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 os | |
| import cv2 | |
| import sys | |
| import glob | |
| __dir__ = os.path.dirname(os.path.abspath(__file__)) | |
| sys.path.append(__dir__) | |
| sys.path.append(os.path.abspath(os.path.join(__dir__, '..'))) | |
| from utils.config import ArgsParser | |
| from engine.synthesisers import ImageSynthesiser | |
| def synth_image(): | |
| args = ArgsParser().parse_args() | |
| image_synthesiser = ImageSynthesiser() | |
| style_image_path = args.style_image | |
| img = cv2.imread(style_image_path) | |
| text_corpus = args.text_corpus | |
| language = args.language | |
| synth_result = image_synthesiser.synth_image(text_corpus, img, language) | |
| fake_fusion = synth_result["fake_fusion"] | |
| fake_text = synth_result["fake_text"] | |
| fake_bg = synth_result["fake_bg"] | |
| cv2.imwrite("fake_fusion.jpg", fake_fusion) | |
| cv2.imwrite("fake_text.jpg", fake_text) | |
| cv2.imwrite("fake_bg.jpg", fake_bg) | |
| def batch_synth_images(): | |
| image_synthesiser = ImageSynthesiser() | |
| corpus_file = "../StyleTextRec_data/test_20201208/test_text_list.txt" | |
| style_data_dir = "../StyleTextRec_data/test_20201208/style_images/" | |
| save_path = "./output_data/" | |
| corpus_list = [] | |
| with open(corpus_file, "rb") as fin: | |
| lines = fin.readlines() | |
| for line in lines: | |
| substr = line.decode("utf-8").strip("\n").split("\t") | |
| corpus_list.append(substr) | |
| style_img_list = glob.glob("{}/*.jpg".format(style_data_dir)) | |
| corpus_num = len(corpus_list) | |
| style_img_num = len(style_img_list) | |
| for cno in range(corpus_num): | |
| for sno in range(style_img_num): | |
| corpus, lang = corpus_list[cno] | |
| style_img_path = style_img_list[sno] | |
| img = cv2.imread(style_img_path) | |
| synth_result = image_synthesiser.synth_image(corpus, img, lang) | |
| fake_fusion = synth_result["fake_fusion"] | |
| fake_text = synth_result["fake_text"] | |
| fake_bg = synth_result["fake_bg"] | |
| for tp in range(2): | |
| if tp == 0: | |
| prefix = "%s/c%d_s%d_" % (save_path, cno, sno) | |
| else: | |
| prefix = "%s/s%d_c%d_" % (save_path, sno, cno) | |
| cv2.imwrite("%s_fake_fusion.jpg" % prefix, fake_fusion) | |
| cv2.imwrite("%s_fake_text.jpg" % prefix, fake_text) | |
| cv2.imwrite("%s_fake_bg.jpg" % prefix, fake_bg) | |
| cv2.imwrite("%s_input_style.jpg" % prefix, img) | |
| print(cno, corpus_num, sno, style_img_num) | |
| if __name__ == '__main__': | |
| # batch_synth_images() | |
| synth_image() | |