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

model_path = Path('ImageDifferentiator.pkl')

# Explicitly specify map_location and use cpu if needed
learn = load_learner(model_path, cpu=True)
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))}

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