Create app.py
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app.py
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import gradio as gr
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from fastai.vision.all import load_learner, PILImage
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# Carga el modelo exportado (export.pkl) que hayas subido al repositorio
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model = load_learner('export.pkl')
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# Función de predicción
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def predict_image(img_path):
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img = PILImage.create(img_path)
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pred, pred_idx, probs = model.predict(img)
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return {str(pred): float(probs[pred_idx])}
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# Interfaz Gradio
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def main():
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iface = gr.Interface(
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fn=predict_image,
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inputs=gr.Image(type='filepath', label='Sube una imagen de documento Tobacco'),
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outputs=gr.Label(num_top_classes=3, label='Predicciones'),
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title='Clasificador Tobacco-3482',
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description='Clasifica imágenes del dataset Tobacco-3482 en sus categorías.'
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)
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# En Spaces, share=True no es necesario
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iface.launch()
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if __name__ == '__main__':
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main()
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