Update app.py

app.py

@@ -11,22 +11,26 @@ import pickletools
 from transformers import AutoTokenizer, CLIPTextModelWithProjection
 
 # loading the train dataset
-with open('clip_train.pkl', 'rb') as f: 
-    temp_d = pickletools.dis(f)
+# with open('clip_train.pkl', 'rb') as f: 
+#     temp_d = pickletools.dis(f)
     # train_xv = temp_d['image'].astype(np.float64)   # Array of image features : np ndarray
     # train_xt = temp_d['text'].astype(np.float64)    # Array of text features : np ndarray
     # train_yv  = temp_d['label']                     # Array of labels 
-    train_yt  = temp_d['label']                     # Array of labels 
+    # train_yt  = temp_d['label']                     # Array of labels 
     # ids = list(temp_d['ids'])                       # image names == len(images)
 
+train_yt = np.load("train_yt.npy")
+
 # loading the test dataset
-with open('clip_test.pkl', 'rb') as f:
-    temp_d = pickletools.dis(f)
+# with open('clip_test.pkl', 'rb') as f:
+    # temp_d = pickletools.dis(f)
     # test_xv = temp_d['image'].astype(np.float64)
-    test_xt = temp_d['text'].astype(np.float64)
+    # test_xt = temp_d['text'].astype(np.float64)
     # test_yv = temp_d['label']
     # test_yt = temp_d['label']
 
+test_xt = np.load("test_xt.npy")
+
 # Map the image ids to the corresponding image URLs
 image_map_name = 'pascal_dataset.csv'
 df = pd.read_csv(image_map_name)