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  1. app.py +23 -0
  2. best.pt +3 -0
  3. requirements.txt +4 -0
app.py ADDED
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+ import gradio as gr
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+ from ultralytics import YOLO
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+
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+ # Load the YOLO model
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+ model = YOLO('best.pt')
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+
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+ def predict(img):
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+
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+ results = model(img)
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+ annotated_frame = results[0].plot()
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+ return annotated_frame
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+
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+ # Create the Gradio interface
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+ iface = gr.Interface(
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+ fn=predict,
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+ inputs=gr.Image(label="Input Image", type="filepath"),
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+ outputs="image",
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+ title="Rat Paw Detector",
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+ description="Upload an image to detect rat paws"
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+ )
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+
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+ # Launch the Gradio interface
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+ iface.launch(share=True)
best.pt ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:016663c7243bbaf34fe923ddec534fb32bf558efa7b326f6a3b9adcb581de29c
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+ size 6209625
requirements.txt ADDED
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+ ultralytics
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+ gradio
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+ numpy
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+ pillow