Update app.py

app.py

@@ -1,23 +1,25 @@
-import gradio as gr
-from transformers import pipeline
-
-# Load the pre-trained Image Classification pipeline
-classifier = pipeline("image-classification", model="google/vit-base-patch16-224")
-
-def predict(image):
-    # Get predictions from the model
-    results = classifier(image)
-    # Reformat for Gradio's Label component: {"Label": Score}
-    return {res["label"]: res["score"] for res in results}
-
-# Define the Gradio Interface
-demo = gr.Interface(
-    fn=predict, 
-    inputs=gr.Image(type="pil"), 
-    outputs=gr.Label(num_top_classes=3),
-    title="AI Image Classifier",
-    description="Upload any image to see what the Vision Transformer thinks it is!"
-)
-
-if __name__ == "__main__":
-    demo.launch()
+import gradio as gr
+from transformers import pipeline
+
+# Load the pre-trained Image Classification pipeline
+classifier = pipeline("image-classification", model="google/vit-base-patch16-224")
+
+def predict(image):
+    # Get predictions from the model
+    results = classifier(image)
+    # Reformat for Gradio's Label component: {"Label": Score}
+    return {res["label"]: res["score"] for res in results}
+
+# Define the Gradio Interface
+demo = gr.Interface(
+    fn=predict, 
+    inputs=gr.Image(type="pil"), 
+    outputs=gr.Label(num_top_classes=3),
+    title="AI Image Classifier",
+    description="Upload any image to see what the Vision Transformer thinks it is!"
+)
+
+if __name__ == "__main__":
+    demo.launch()
+
+