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Update app.py
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app.py
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import os, torchvision, transformers
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from functools import partial
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import gradio as gr
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from
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from .inference import LiveInfer
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logger = transformers.logging.get_logger('liveinfer')
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# python -m demo.app --resume_from_checkpoint ...
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liveinfer = LiveInfer()
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css = """
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#gr_title {text-align: center;}
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#gr_video {max-height: 480px;}
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import os, torchvision, transformers, subprocess
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from functools import partial
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import gradio as gr
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from inference import LiveInfer
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logger = transformers.logging.get_logger('liveinfer')
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# python -m demo.app --resume_from_checkpoint ...
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liveinfer = LiveInfer()
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def ffmpeg_once(src_path: str, dst_path: str, *, fps: int = None, resolution: int = None, pad: str = '#000000', mode='bicubic'):
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os.makedirs(os.path.dirname(dst_path), exist_ok=True)
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command = [
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'./ffmpeg/ffmpeg',
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'-y',
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'-sws_flags', mode,
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'-i', src_path,
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'-an',
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'-threads', '10',
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]
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if fps is not None:
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command += ['-r', str(fps)]
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if resolution is not None:
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command += ['-vf', f"scale='if(gt(iw\\,ih)\\,{resolution}\\,-2)':'if(gt(iw\\,ih)\\,-2\\,{resolution})',pad={resolution}:{resolution}:(ow-iw)/2:(oh-ih)/2:color='{pad}'"]
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command += [dst_path]
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subprocess.run(command, check=True)
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css = """
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#gr_title {text-align: center;}
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#gr_video {max-height: 480px;}
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