import gradio as gr from utils import colorize from PIL import Image import tempfile def predict_depth(model, image): depth = model.infer_pil(image) return depth def create_demo(model): gr.Markdown("### Depth Prediction demo") with gr.Row(): input_image = gr.Image(label="Input Image", type='pil', elem_id='img-display-input').style(height="auto") depth_image = gr.Image(label="Depth Map", elem_id='img-display-output') raw_file = gr.File(label="16-bit raw depth, multiplier:256") submit = gr.Button("Submit") def on_submit(image): depth = predict_depth(model, image) colored_depth = colorize(depth, cmap='gray_r') tmp = tempfile.NamedTemporaryFile(suffix='.png', delete=False) raw_depth = Image.fromarray((depth*256).astype('uint16')) raw_depth.save(tmp.name) return [colored_depth, tmp.name] submit.click(on_submit, inputs=[input_image], outputs=[depth_image, raw_file]) # examples = gr.Examples(examples=["examples/person_1.jpeg", "examples/person_2.jpeg", "examples/person-leaves.png", "examples/living-room.jpeg"], # inputs=[input_image])