app.py

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

learn = load_learner('model_0.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 = "What is this landscape?"
description = "A landscape typology helper. This model can classify if a landscape is 3 types: forest - rural - water"
examples = ['forest.jpg','rural.jpg','water.jpg']
enable_queue=True

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