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Update app.py
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app.py
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@@ -23,11 +23,8 @@ class GradioBackend:
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def to(self, device):
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self.infer.model.to(device)
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gradio_backend = GradioBackend()
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with gr.Blocks() as demo:
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gr.Markdown("## LiveCC Real-Time Commentary and Conversation - Gradio Demo")
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gr.Markdown("### [LiveCC: Learning Video LLM with Streaming Speech Transcription at Scale (CVPR 2025)](https://showlab.github.io/livecc/)")
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gr.Markdown("1️⃣ Select Mode, Real-Time Commentary (LiveCC) or Conversation (Common QA)")
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@@ -38,6 +35,9 @@ with gr.Blocks() as demo:
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gr_video_state = gr.JSON({}, visible=False) # only record video state, belong to gr_state but lightweight
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gr_static_trigger = gr.Number(value=0, visible=False) # control start streaming or stop
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gr_dynamic_trigger = gr.Number(value=0, visible=False) # for continuous refresh
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with gr.Row():
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with gr.Column():
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gr_video = gr.Video(
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def to(self, device):
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self.infer.model.to(device)
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with gr.Blocks() as demo:
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gr.Markdown("## LiveCC Real-Time Commentary and Conversation - Gradio Demo")
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gr.Markdown("### [LiveCC: Learning Video LLM with Streaming Speech Transcription at Scale (CVPR 2025)](https://showlab.github.io/livecc/)")
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gr.Markdown("1️⃣ Select Mode, Real-Time Commentary (LiveCC) or Conversation (Common QA)")
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gr_video_state = gr.JSON({}, visible=False) # only record video state, belong to gr_state but lightweight
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gr_static_trigger = gr.Number(value=0, visible=False) # control start streaming or stop
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gr_dynamic_trigger = gr.Number(value=0, visible=False) # for continuous refresh
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gradio_backend = GradioBackend()
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with gr.Row():
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with gr.Column():
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gr_video = gr.Video(
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