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

# load model
learn = load_learner('seasons_model.pkl')
# categories = ('Fall', 'Winter', 'Spring', 'Summer')
categories = learn.dls.vocab

# classifier
def classify_image(img):
    pred,idx,probs = learn.predict(img)
    return dict(zip(categories,map(float,probs)))

# Gradio inputs
image = gr.inputs.Image(shape=(224,224))
label = gr.outputs.Label()
examples = ['fall_photo.jpeg', 'winter_photo.jpeg', 'spring_photo.jpeg', 'summer_photo.jpeg']

# Interface
iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
iface.launch(inline=False)