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# Use a pipeline as a high-level helper
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['lbale']: p["score"] for p in predictions}
import gradio as gr
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() |