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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')
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=["cat.png"],
inputs=[input_image]) |