classify_me / app.py
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import gradio as gr
from huggingface_hub import InferenceClient
from transformers import pipeline
pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
def predict(image):
predictions = pipeline(image)
return {p["label"]: p["score"] for p in predictions}
gr.Interface(
predict,
inputs=gr.Image(label="Upload hot dog candidate", type="filepath"),
outputs=gr.Label(num_top_classes=2),
title="Hot Dog? Or Not?",
).launch()
# if __name__ == "__main__":
# demo.launch()
#source:: https://medium.com/@sa.pieri.98/build-your-first-hugging-face-space-with-gradio-a-beginners-guide-14bc42d66887