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import gradio as gr |
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from run import get_model, detect_video |
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model = get_model() |
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def greet(video): |
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print(video, type(video)) |
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generated_pred = detect_video(video_path=video, model=model) |
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context_pred = 0.7490718364715576 |
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generated_output = f"Fake: {generated_pred*100:.2f}%" if generated_pred > 0.5 else f"Real: {(1-generated_pred)*100:.2f}%" |
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context_output = f"Fake: {context_pred*100:.2f}%" if context_pred > 0.5 else f"Real: {(1-context_pred)*100:.2f}%" |
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print(generated_output, '\n', context_output) |
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return generated_output, context_output |
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with gr.Blocks() as demo: |
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gr.Markdown("# Fake Video Detector") |
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with gr.Tabs(): |
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with gr.TabItem("Video Detect"): |
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with gr.Column(): |
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video_input = gr.Video(height=330) |
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video_button = gr.Button("detect") |
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detect_output = gr.Textbox(label="AI detect result") |
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context_output = gr.Textbox(label="Context detect result") |
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video_button.click(greet, inputs=video_input, outputs=[detect_output, context_output]) |
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demo.launch() |
