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!pip install transformers | |
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} | |
import gradio as gr | |
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() |