add hotdog demo

app.py

@@ -1,7 +1,18 @@
 import gradio as gr
+from transformers import pipeline
 
-def greet(name):
-    return "Hello " + name + "!!"
+pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+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?",
+)
+
+if __name__ == "__main__":
+    gradio_app.launch()

requirements.txt

@@ -0,0 +1,4 @@
+transformers
+diffusers
+torch
+numpy