app.py

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

model_path = Path('ImageDifferentiator.pkl')



# Re-save the model on a non-Windows system
learn = load_learner(model_path)
learn.export('ImageDifferentiator_export.pkl')

# Load the model using Fastai's load_learner
learn = load_learner('ImageDifferentiator_export.pkl')
labels = learn.dls.vocab

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)