Update app.py

app.py

@@ -1,20 +1,22 @@
 import gradio as gr
 from transformers import pipeline
 
+# Load the image classification model
 pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
 
+# Define the prediction function
 def predict(input_img):
     predictions = pipeline(input_img)
     return input_img, {p["label"]: p["score"] for p in predictions} 
 
+# Set up the Gradio interface
 gradio_app = gr.Interface(
-    predict,
+    fn=predict,
     inputs=gr.Image(label="Select hot dog candidate", sources=['upload', 'webcam'], type="pil"),
     outputs=[gr.Image(label="Processed Image"), gr.Label(label="Result", num_top_classes=2)],
-    title="Hot Dog? Or Not?",
-    interface.launch(share=True)
-
+    title="Hot Dog? Or Not?"
 )
 
+# Launch the Gradio app with public link
 if __name__ == "__main__":
-    gradio_app.launch()
+    gradio_app.launch(share=True)