Update main.py

main.py

@@ -40,6 +40,9 @@ recog_session = ort.InferenceSession(recog_path_local)
 df = pd.read_parquet(card_data_path)
 ref_embeddings = np.vstack(df['embedding'].values).astype(np.float32)
 
+card_metadata = df[['card_id', 'name', 'uri', 'card_url', 'image_url', 'lang', 'rarity', 'set_name', 'set']].to_dict('records')
+del df  # Free DataFrame memory after extracting needed data
+
 task_config = {
     "recog": {"image_width": 160, "image_height": 224, "means": [0.5, 0.5, 0.5], "stds": [0.5, 0.5, 0.5]},
     "corner": {"image_width": 256, "image_height": 256, "means": [0.5, 0.5, 0.5], "stds": [0.5, 0.5, 0.5]},
@@ -179,7 +182,7 @@ async def predict(file: UploadFile = File(...)) -> Card:
     best_sim = float(similarities[best_idx])
     
     # Retrieve card metadata from dataframe using integer position
-    card_info = df.iloc[best_idx]
+    card_info = card_metadata[best_idx]
         
     # End timing
     t1 = time.perf_counter()