Update app.py

app.py

@@ -71,11 +71,11 @@ def predict(text,img):
       top_N_images.append(l[index])
     return scores,top_N_images
 
-  search_query = text
+  #search_query = text
 
   with torch.no_grad():
       # Encode and normalize the description using CLIP
-      text_encoded = model.encode_text(clip.tokenize(search_query).to(device))
+      text_encoded = model.encode_text(clip.tokenize(text).to(device))
       text_encoded /= text_encoded.norm(dim=-1, keepdim=True)
 
   similarity = text_encoded.cpu().numpy() @ image_features.cpu().numpy().T