import gradio as gr
from fastai.vision.all import *

def is_cat(x): return x[0].isupper()

learn = load_learner('model.pkl')

labels = learn.dls.vocab
print(f"LABELS: {labels}")
def predict(img):
    img = PILImage.create(img)
    pred,pred_idx,probs = learn.predict(img)
    print(f"{pred=}    {pred_idx=}     {probs}")
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch()