fix error return

app.py

@@ -30,28 +30,38 @@ def embedding_input(text_input):
     return text_emb
 
 def embedding_img():
-    global images
-    img_batch = imagenette['image']
-
-    images = processor(
-        text = None,
-        images = img_batch,
-        return_tensors = 'pt'
-    )['pixel_values'].to(device)
-    batch_emb = model.get_image_features(pixel_values =img_batch)
-    batch_emb = batch_emb.squeeze(0)
-    image_arr = batch_emb.cpu().detach().numpy()
+    global images, image_arr
+    load_data()
+    sample_idx= np.random.randint(0, len(imagenette)+1, 100).tolist()
+    images = [imagenette[i]['image'] for i in sample_idx]
+    batch_sie = 5
+    image_arr = None
+    for i in tqdm(range(0, len(images), batch_sie)):
+        time.sleep(1)
+        batch = images[i:i+batch_sie]
 
+        batch = processor(
+            text = None,
+            images = batch,
+            return_tensors= 'pt',
+            padding = True
+        )['pixel_values'].to(device)
+        batch_emb = model.get_image_features(pixel_values = batch)
+        batch_emb = batch_emb.squeeze(0)
+        batch_emb = batch_emb.cpu().detach().numpy()
+        
+        if image_arr is None:
+            image_arr = batch_emb
+            
+        else:
+            image_arr = np.concatenate((image_arr, batch_emb), axis = 0)
     return image_arr
 
 def norm_val(text_input):
-    image_arr = embedding_img()
-    time.sleep(5)
     text_emb = embedding_input(text_input)
-
-    image_arr = (image_arr.T / np.linalg.norm(image_arr, axis = 1)).T
+    image_emb = (image_arr.T / np.linalg.norm(image_arr, axis = 1)).T
     text_emb = text_emb.cpu().detach().numpy()
-    scores = np.dot(text_emb, image_arr.T)
+    scores = np.dot(text_emb, image_emb.T)
     top_k = 1
     idx = np.argsort(-scores[0])[:top_k]
     return images[idx[0]]
@@ -61,6 +71,7 @@ def norm_val(text_input):
 
 
 if __name__ == "__main__":
+    embedding_img()
     load_data()
     iface = gr.Interface(fn=norm_val, inputs="text", outputs="image")
     iface.launch(inline = False )