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app.py

@@ -1,12 +1,18 @@
 import gradio as gr
+from transformers import pipeline
 
-def greet(name, intensity):
-    return "Hello world 2!!!" * intensity + name + "!"
+pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
 
-demo = gr.Interface(
-    fn=greet,
-    inputs=["text", "slider"],
-    outputs=["text"],
+def predict(input_img):
+    predictions = pipeline(input_img)
+    return input_img, {p["label"]: p["score"] for p in predictions} 
+
+gradio_app = gr.Interface(
+    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?",
 )
 
-demo.launch()
+if __name__ == "__main__":
+    gradio_app.launch()