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import gradio as gr |
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from inference import combined_inference_live |
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from model_loader import EXTENDED_MODELS |
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with gr.Blocks() as app: |
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gr.Markdown("# Live Object Detection: Full vs. Slicing-Based Detection") |
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gr.Markdown(""" |
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**How It Works**: |
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- **Full Inference**: Runs a single pass over the entire frame. |
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- **Slicing Detection**: Divides the frame into patches, detects objects, applies Non-Maximum Suppression (NMS). |
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- **Outputs retain the original BGR format for color accuracy**. |
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""") |
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with gr.Row(): |
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webcam = gr.Image(sources="webcam", streaming=True, label="Webcam Feed") |
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model_dd = gr.Dropdown(label="Select Model", choices=list(EXTENDED_MODELS.keys()), value="YOLOv8") |
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with gr.Row(): |
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conf_slider = gr.Slider(0, 1.0, value=0.25, step=0.05, label="Confidence Threshold") |
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slice_slider = gr.Slider(128, 1024, value=512, step=1, label="Slice Size") |
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overlap_slider = gr.Slider(0.0, 0.5, value=0.2, step=0.05, label="Overlap Rate") |
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fi_output = gr.Image(label="Full Inference") |
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slice_output = gr.Image(label="Slicing + NMS") |
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webcam.stream( |
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fn=combined_inference_live, |
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inputs=[webcam, model_dd, conf_slider, slice_slider, overlap_slider], |
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outputs=[fi_output, slice_output] |
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) |
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app.launch() |
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