app.py

import gradio as gr
from PIL import Image

from backend import Infer

DEBUG = True

infer = Infer(DEBUG)


with gr.Blocks(analytics_enabled=False, title="DeepNAPSI") as demo:
    with gr.Column():
        gr.Markdown("## Welcome to the DeepNAPSI application!")
        gr.Markdown("Upload an image of the one hand and click **Predict NAPSI** to see the output.\n" \
                    "> Note: Make sure there are no identifying information present in the image. The prediction can take up to 1 minute.")
        with gr.Column():
            with gr.Row():
                image_input = gr.Image()
                example_images = gr.Examples(["assets/example_1.jpg", "assets/example_2.jpg", "assets/example_3.jpg"], image_input)
            with gr.Row():
                image_button = gr.Button("Predict NAPSI")
            outputs = []
            with gr.Row():
                outputs.append(gr.Number(label="DeepNAPSI Sum"))
                with gr.Column():
                    outputs.append(gr.Image())
                    outputs.append(gr.Number(label="DeepNAPSI Thumb"))
                with gr.Column():
                    outputs.append(gr.Image())
                    outputs.append(gr.Number(label="DeepNAPSI Index"))
                with gr.Column():
                    outputs.append(gr.Image())
                    outputs.append(gr.Number(label="DeepNAPSI Middle"))
                with gr.Column():
                    outputs.append(gr.Image())
                    outputs.append(gr.Number(label="DeepNAPSI Ring"))
                with gr.Column():
                    outputs.append(gr.Image())
                    outputs.append(gr.Number(label="DeepNAPSI Pinky"))
        image_button.click(infer.predict, inputs=image_input, outputs=outputs)

demo.launch(share=True)