feat: return top 3

main.py

@@ -19,7 +19,10 @@ def classify_image(img):
     img_array = tf.keras.applications.efficientnet.preprocess_input(img_array)
     prediction = model.predict(img_array).flatten()
     confidences = {labels[i]: float(prediction[i]) for i in range(90)}
-    return confidences
+    # Sort the confidences dictionary by value and get the top 3 items
+    top_3_confidences = dict(sorted(confidences.items(), key=lambda item: item[1], reverse=True)[:3])
+    
+    return top_3_confidences
 
 @app.post("/predict")
 async def predict(file: bytes = File(...)):