from fastai.vision.all import * import gradio as gr def is_classical(x): return x[0].isupper() # Cell learn = load_learner('interior.pkl') # Cell categories = ('classical','japandi','minimal','poho','earthy') def classify_image(img): pred,idx,probs = learn.predict(img) return dict(zip(categories, map(float,probs))) # Cell image = gr.inputs.Image(shape=(192, 192)) label = gr.outputs.Label() examples = ['classical.jpg','japandi.jpg','minimal.jpg','poho.jpg','earthy.jpg'] intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) intf.launch()