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)