app.py

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

# load model
learn = load_learner('model.pkl')

# prediction function for model
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))}

# gradio app
title = "Whale model"
description = "Demo Gradio app for a ML image classifier using fast.ai"
examples = ['whale.jpeg']

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