classfify_breed / app.py
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from fastai.vision.all import *
import gradio as gr
learn = load_learner('export.pkl')
labels = learn.dls.vocab
def predict(img):
img = PILImage.create(img)
pred,pred_idx,probs = learn.predict(img)
return {labels[i]: float(probs[i]) for i in range(len(labels))}
demo = gr.Interface(
fn=predict,
inputs=gr.Image(type="pil", image_mode="RGB", height=512, width=512, sources=["upload"]),
outputs=gr.Label(num_top_classes=3),
title="Image Classifier",
description="Upload an image; the app resizes to 512Γ—512 inside predict()."
)
if __name__ == "__main__":
demo.launch() # trΓͺn Spaces khΓ΄ng dΓΉng share=True