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