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from depth import MidasDepth
import gradio as gr
import numpy as np
import tempfile
depth_estimator = MidasDepth()
def get_depth(rgb):
print("Estimating depth...")
rgb = rgb.convert("RGB")
depth = depth_estimator.get_depth(rgb)
print("Creating mesh...")
w, h = rgb.size
grid = np.mgrid[0:h, 0:w].transpose(1, 2, 0
).reshape(-1, 2)[..., ::-1]
flat_grid = grid[:, 1] * w + grid[:, 0]
positions = np.concatenate(((grid - np.array([[w, h]])
/ 2) / w * 2,
depth.flatten()[flat_grid][..., np.newaxis]),
axis=-1)
positions[:, :-1] *= positions[:, -1:]
positions[:, :2] *= -1
pick_edges = depth < 0
y, x = (t.flatten() for t in np.mgrid[0:h, 0:w])
faces = np.concatenate((
np.stack((y * w + x,
(y - 1) * w + x,
y * w + (x - 1)), axis=-1)
[(~pick_edges.flatten()) * (x > 0) * (y > 0)],
np.stack((y * w + x,
(y + 1) * w + x,
y * w + (x + 1)), axis=-1)
[(~pick_edges.flatten()) * (x < w - 1) * (y < h - 1)]
))
print("Writing...")
tf = tempfile.NamedTemporaryFile(suffix=".obj").name
save_obj(positions, np.asarray(rgb).reshape(-1, 3) / 255., faces, tf)
return rgb, (depth.clip(0, 64) * 1024).astype("uint16"), tf
def save_obj(positions, rgb, faces, filename):
with open(filename, "w") as f:
for position, color in zip(positions, rgb):
f.write(
f"v {' '.join(map(str, position))} {' '.join(map(str, color))}\n")
for face in faces:
f.write(f"f {' '.join(map(str, face))}\n")
gr.Interface(fn=get_depth, inputs=[
gr.components.Image(label="rgb", type="pil"),
], outputs=[
gr.components.Image(type="pil", label="image"),
gr.components.Image(type="numpy", label="depth"),
gr.components.Model3D(label="3d model")
]).launch(share=True)
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