test "hot dog? or not" model

app.py

@@ -1,12 +1,18 @@
 import gradio as gr
+from transformers import pipeline
 
-def greet(name, intensity):
-        return "hello, " + name + "!" * int(intensity)
+pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
 
-demo = gr.Interface(
-    fn=greet,
-    input=["text", "slider"],
-    output=["text"],
+def predict(input_img):
+    predictions = pipeline(input_img)
+    return input_img, {p["label"]: p["score"] for p in predictions}
+
+gradio_app =  gr.Interface(
+    fn=predict,
+    inputs=gr.Image(label="Selece 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?",
 )
 
-demo.launch()
+if __name__ == "__main__":
+    gradio_app.launch()