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import gradio as gr
from fastai.vision.all import *
from huggingface_hub import from_pretrained_fastai
learn = from_pretrained_fastai("Ener3122/Seasons_Classifier")
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))}
title = "Seasons predictor"
description = "As long as there isn't water, it might guess right"
gr.Interface(
fn=predict,
inputs=gr.Image(),
outputs=gr.Label(num_top_classes=4),
title=title,
description=description,
).launch()