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43 lines
1.3 KiB
Python
43 lines
1.3 KiB
Python
import cv2, argparse
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import imageio
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from tqdm import tqdm
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import numpy as np
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from modelscope.outputs import OutputKeys
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from modelscope.pipelines import pipeline
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from modelscope.utils.constant import Tasks
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def process(args):
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style = args.style
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print('choose style %s'%style)
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reader = imageio.get_reader(args.video_path)
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fps = reader.get_meta_data()['fps']
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writer = imageio.get_writer(args.save_path, mode='I', fps=fps, codec='libx264')
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if style == "anime":
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style = ""
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else:
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style = '-' + style
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model_name = 'damo/cv_unet_person-image-cartoon' + style + '_compound-models'
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img_cartoon = pipeline(Tasks.image_portrait_stylization, model=model_name)
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for _, img in tqdm(enumerate(reader)):
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result = img_cartoon(img[..., ::-1])
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res = result[OutputKeys.OUTPUT_IMG]
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writer.append_data(res[..., ::-1].astype(np.uint8))
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writer.close()
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print('finished!')
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print('result saved to %s'% args.save_path)
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser.add_argument('--video_path', type=str, default='PATH/TO/YOUR/MP4')
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parser.add_argument('--save_path', type=str, default='res.mp4')
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parser.add_argument('--style', type=str, default='anime')
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args = parser.parse_args()
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process(args)
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