app.py

import gradio as gr
# To solve problems with pathlib in load_learner
import pathlib
import platform
plt = platform.system()
if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath
    
from fastai.vision.all import load_learner, PILImage

learn = load_learner('model.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))}

title = "Bear Classifier"
description = "A prototype bear classifier developed with fastaiwith images from ddg. Created as a demo for Gradio and HuggingFace Spaces."
examples = [r'examples/grizzly_bear.jpg']


demo = gr.Interface(fn=predict, inputs="image", outputs="label", examples=examples)
demo.launch()