Delete app.py

app.py

@@ -1,43 +0,0 @@
-import os
-import tempfile
-from fastapi import FastAPI, UploadFile, File, HTTPException
-from fastapi.responses import JSONResponse
-import tensorflow as tf
-from prediction import predict_eeg_recording
-
-app = FastAPI(title="EEG Epilepsy Prediction API")
-model = tf.keras.models.load_model('model1_2dcnn.h5')
-
-# ✅ Ajout du endpoint GET /
-@app.get("/")
-async def root():
-    return {"message": "Bienvenue sur l'API EEG Epilepsy. Utilisez POST /predict pour soumettre un fichier EDF."}
-
-@app.post("/predict")
-async def predict_endpoint(file: UploadFile = File(...)):
-    try:
-        suffix = os.path.splitext(file.filename)[1]
-        with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as tmp:
-            tmp.write(await file.read())
-            tmp_path = tmp.name
-    except Exception:
-        raise HTTPException(status_code=500, detail="Erreur lors de la sauvegarde temporaire")
-
-    try:
-        label, mean_prob, segment_probs = predict_eeg_recording(tmp_path, model, threshold=0.5)
-    except Exception as e:
-        os.remove(tmp_path)
-        raise HTTPException(status_code=400, detail=f"Erreur prédiction : {e}")
-    
-    os.remove(tmp_path)
-
-    response = {
-        "prediction": "epilepsy" if label == 1 else "no epilepsy",
-        "mean_probability": float(mean_prob),
-        "segment_probabilities": [float(p) for p in segment_probs]
-    }
-    return JSONResponse(content=response)
-
-if __name__ == "__main__":
-    import uvicorn
-    uvicorn.run("app:app", host="0.0.0.0", port=7860, reload=True)