Update app.py

app.py

@@ -1,16 +1,16 @@
 import gradio as gr
 import torch
-from transformers import ViTFeatureExtractor, ViTForImageClassification
+from transformers import ViTImageProcessor, ViTForImageClassification
 from PIL import Image
 
 # Load the pre-trained model and feature extractor
 model_name = "google/vit-base-patch16-224"
-feature_extractor = ViTFeatureExtractor.from_pretrained(model_name)
+image_processor = ViTImageProcessor.from_pretrained(model_name)
 model = ViTForImageClassification.from_pretrained(model_name)
 
 # Define the prediction function
 def predict(image):
-    inputs = feature_extractor(images=image, return_tensors="pt")
+    inputs = image_processor(images=image, return_tensors="pt")
     outputs = model(**inputs)
     logits = outputs.logits
     predicted_class_idx = logits.argmax(-1).item()
@@ -19,8 +19,8 @@ def predict(image):
 # Create the Gradio interface
 iface = gr.Interface(
     fn=predict,
-    inputs=gr.inputs.Sketchpad(),
-    outputs=gr.outputs.Label(),
+    inputs=gr.components.Sketchpad(),
+    outputs=gr.components.Label(),
     title="Drawing Classifier",
     description="Draw something and the model will try to identify it!"
 )