Create app.py

app.py

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+# Use a pipeline as a high-level helper
+import gradio as gr
+from transformers import pipeline
+
+
+pipe = pipeline("image-classification", model="julien-c/hotdog-not-hotdog")
+
+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 dot candiadate", 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()