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	87bcb5df21
	
	
	
		
			
			* add style transfer model * add examples for generation model * add unit test * add speed comparison * add speed comparison * add variable for constant * add preprocessor and postprocessor * add preprocessor and postprocessor * fix * fix according to review Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
		
			
				
	
	
		
			47 lines
		
	
	
		
			1.8 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			47 lines
		
	
	
		
			1.8 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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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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| 
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| import fastdeploy as fd
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| import cv2
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| import os
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| import numpy as np
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| 
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| 
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| def test_animegan():
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|     model_name = 'animegan_v1_hayao_60'
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|     model_path = fd.download_model(
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|         name=model_name, path='./resources', format='paddle')
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|     test_img = 'https://bj.bcebos.com/paddlehub/fastdeploy/style_transfer_testimg.jpg'
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|     label_img = 'https://bj.bcebos.com/paddlehub/fastdeploy/style_transfer_result.png'
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|     fd.download(test_img, "./resources")
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|     fd.download(label_img, "./resources")
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|     # use default backend
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|     runtime_option = fd.RuntimeOption()
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|     runtime_option.set_paddle_mkldnn(False)
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|     model_file = os.path.join(model_path, "model.pdmodel")
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|     params_file = os.path.join(model_path, "model.pdiparams")
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|     animegan = fd.vision.generation.AnimeGAN(
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|         model_file, params_file, runtime_option=runtime_option)
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| 
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|     src_img = cv2.imread("./resources/style_transfer_testimg.jpg")
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|     label_img = cv2.imread("./resources/style_transfer_result.png")
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|     res = animegan.predict(src_img)
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| 
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|     diff = np.fabs(res.astype(np.float32) - label_img.astype(np.float32)) / 255
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|     assert diff.max() < 1e-04, "There's diff in prediction."
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| 
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| 
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| if __name__ == "__main__":
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|     test_animegan()
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