mirror of
https://github.com/facebookresearch/pytorch3d.git
synced 2026-09-14 03:05:46 +08:00
fdaf9bd6fe
Summary: This diff was automatically generated by the Pyre per-target upgrade tool. It removes `# pyre-fixme` or `pyrefly: ignore` comments that are no longer needed because the underlying type errors have been resolved. Note that it will also aim to ensure type checking runs cleanly, and will add suppressions to existing type errors. #pyreupgrade Differential Revision: D116557086 fbshipit-source-id: 1337613d4fb3ab79bd3a733f3a4c9a499a72f971
114 lines
3.8 KiB
Python
114 lines
3.8 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
|
# All rights reserved.
|
|
#
|
|
# This source code is licensed under the BSD-style license found in the
|
|
# LICENSE file in the root directory of this source tree.
|
|
|
|
# pyre-unsafe
|
|
|
|
from typing import Any, Optional
|
|
|
|
import numpy as np
|
|
from PIL import Image, ImageDraw
|
|
from pytorch3d.renderer.mesh import TexturesUV
|
|
|
|
|
|
def texturesuv_image_matplotlib(
|
|
texture: TexturesUV,
|
|
*,
|
|
texture_index: int = 0,
|
|
radius: float = 1,
|
|
color=(1.0, 0.0, 0.0),
|
|
subsample: Optional[int] = 10000,
|
|
origin: str = "upper",
|
|
) -> None: # pragma: no cover
|
|
"""
|
|
Plot the texture image for one element of a TexturesUV with
|
|
matplotlib together with verts_uvs positions circled.
|
|
In particular a value in verts_uvs which is never referenced
|
|
in faces_uvs will still be plotted.
|
|
This is for debugging purposes, e.g. to align the map with
|
|
the uv coordinates. In particular, matplotlib
|
|
is used which is not an official dependency of PyTorch3D.
|
|
|
|
Args:
|
|
texture: a TexturesUV object with one mesh
|
|
texture_index: index in the batch to plot
|
|
radius: plotted circle radius in pixels
|
|
color: any matplotlib-understood color for the circles.
|
|
subsample: if not None, number of points to plot.
|
|
Otherwise all points are plotted.
|
|
origin: "upper" or "lower" like matplotlib.imshow .
|
|
upper (the default) matches texturesuv_image_PIL.
|
|
"""
|
|
|
|
import matplotlib.pyplot as plt
|
|
from matplotlib.patches import Circle
|
|
|
|
texture_image = texture.maps_padded()
|
|
centers = texture.centers_for_image(index=texture_index).numpy()
|
|
|
|
ax = plt.gca()
|
|
ax.imshow(texture_image[texture_index].detach().cpu().numpy(), origin=origin)
|
|
|
|
n_points = centers.shape[0]
|
|
if subsample is None or n_points <= subsample:
|
|
indices = range(n_points)
|
|
else:
|
|
indices = np.random.choice(n_points, subsample, replace=False)
|
|
for i in indices:
|
|
# setting clip_on=False makes it obvious when
|
|
# we have UV coordinates outside the correct range
|
|
# `ndarray[Any, Any]`.
|
|
ax.add_patch(Circle(centers[i], radius, color=color, clip_on=False))
|
|
|
|
|
|
def texturesuv_image_PIL(
|
|
texture: TexturesUV,
|
|
*,
|
|
texture_index: int = 0,
|
|
radius: float = 1,
|
|
color: Any = "red",
|
|
subsample: Optional[int] = 10000,
|
|
): # pragma: no cover
|
|
"""
|
|
Return a PIL image of the texture image of one element of the batch
|
|
from a TexturesUV, together with the verts_uvs positions circled.
|
|
In particular a value in verts_uvs which is never referenced
|
|
in faces_uvs will still be plotted.
|
|
This is for debugging purposes, e.g. to align the map with
|
|
the uv coordinates. In particular, matplotlib
|
|
is used which is not an official dependency of PyTorch3D.
|
|
|
|
Args:
|
|
texture: a TexturesUV object with one mesh
|
|
texture_index: index in the batch to plot
|
|
radius: plotted circle radius in pixels
|
|
color: any PIL-understood color for the circles.
|
|
subsample: if not None, number of points to plot.
|
|
Otherwise all points are plotted.
|
|
|
|
Returns:
|
|
PIL Image object.
|
|
"""
|
|
|
|
centers = texture.centers_for_image(index=texture_index).numpy()
|
|
texture_image = texture.maps_padded()
|
|
texture_array = (texture_image[texture_index] * 255).cpu().numpy().astype(np.uint8)
|
|
|
|
image = Image.fromarray(texture_array)
|
|
draw = ImageDraw.Draw(image)
|
|
|
|
n_points = centers.shape[0]
|
|
if subsample is None or n_points <= subsample:
|
|
indices = range(n_points)
|
|
else:
|
|
indices = np.random.choice(n_points, subsample, replace=False)
|
|
|
|
for i in indices:
|
|
x = centers[i][0]
|
|
y = centers[i][1]
|
|
draw.ellipse([(x - radius, y - radius), (x + radius, y + radius)], fill=color)
|
|
|
|
return image
|