Update app.py
Browse files
app.py
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@@ -2,21 +2,29 @@ import gradio as gr
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from fastai.vision.all import load_learner, PILImage
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from huggingface_hub import hf_hub_download
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MODEL_REPO = "Clau31/aptos-practica1"
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MODEL_FILE = "model.pkl"
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model_path = hf_hub_download(repo_id=MODEL_REPO, filename=MODEL_FILE)
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learn = load_learner(model_path)
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def predict(img):
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img = PILImage.create(img)
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pred, pred_idx, probs = learn.predict(img)
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return {str(i): float(probs[i]) for i in range(len(probs))}
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fn=predict,
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inputs=gr.Image(type="pil"),
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outputs=gr.Label(num_top_classes=5),
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title="APTOS 2019 – Detección de Ceguera",
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description="
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)
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from fastai.vision.all import load_learner, PILImage
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from huggingface_hub import hf_hub_download
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# Repo del modelo
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MODEL_REPO = "Clau31/aptos-practica1"
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MODEL_FILE = "model.pkl"
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# Descargar y cargar el modelo
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model_path = hf_hub_download(repo_id=MODEL_REPO, filename=MODEL_FILE)
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learn = load_learner(model_path)
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# Función de predicción
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def predict(img):
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img = PILImage.create(img)
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pred, pred_idx, probs = learn.predict(img)
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return {str(i): float(probs[i]) for i in range(len(probs))}
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# Interfaz Gradio
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demo = gr.Interface(
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fn=predict,
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inputs=gr.Image(type="pil"),
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outputs=gr.Label(num_top_classes=5),
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title="APTOS 2019 – Detección de Ceguera",
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description="Modelo de clasificación entrenado con FastAI"
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)
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if __name__ == "__main__":
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demo.queue()
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demo.launch()
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