Update app.py

app.py

@@ -1,6 +1,7 @@
 from transformers import ViTFeatureExtractor, ViTForImageClassification
 from PIL import Image
 import torch.nn.functional as F
+import time
 
 
 feature_extractor = ViTFeatureExtractor.from_pretrained('google/vit-base-patch16-224')
@@ -13,6 +14,7 @@ def predict(image):
     predicted_class_prob = F.softmax(logits, dim=-1).detach().numpy().max()
     predicted_class_idx = logits.argmax(-1).item()
     label = model.config.id2label[predicted_class_idx].split(",")[0]
+    time.sleep(2)
     return {label: float(predicted_class_prob)}
  
 import gradio as gr