| import gradio as gr |
| from transformers import pipeline |
|
|
| pipeline = pipeline(task="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 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() |
