import gradio as gr


# create nnunet input types
# run nnunet
# export




def predict(img):
    return "cat"


demo = gr.Interface(
    fn=predict,
    inputs=gr.File(file_count="single", file_types=[".mha", ".nii.gz", ".nii"]),
#     outputs=(
#         gr.File()
#     )
# ,
    outputs=gr.Label(num_top_classes=3),
)

demo.launch(server_name="0.0.0.0", server_port=7860)