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

learn = load_learner('model.pkl')

categories = ('Cloudy','Rain','Shine Or Partly Cloudy','Sunrise') 
def classify_image(img):
        pred,idx,probs = learn.predict(img)
        return dict(zip(categories,map(float,probs)))

examples = ['cloudy.jpg','rain.jpg','shine.jpg','sunrise.jpg']

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