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OpenPCDet/tools/visual_utils/visualize_utils.py

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2025-09-21 20:19:38 +08:00
import mayavi.mlab as mlab
import numpy as np
import torch
box_colormap = [
[1, 1, 1],
[0, 1, 0],
[0, 1, 1],
[1, 1, 0],
]
def check_numpy_to_torch(x):
if isinstance(x, np.ndarray):
return torch.from_numpy(x).float(), True
return x, False
def rotate_points_along_z(points, angle):
"""
Args:
points: (B, N, 3 + C)
angle: (B), angle along z-axis, angle increases x ==> y
Returns:
"""
points, is_numpy = check_numpy_to_torch(points)
angle, _ = check_numpy_to_torch(angle)
cosa = torch.cos(angle)
sina = torch.sin(angle)
zeros = angle.new_zeros(points.shape[0])
ones = angle.new_ones(points.shape[0])
rot_matrix = torch.stack((
cosa, sina, zeros,
-sina, cosa, zeros,
zeros, zeros, ones
), dim=1).view(-1, 3, 3).float()
points_rot = torch.matmul(points[:, :, 0:3], rot_matrix)
points_rot = torch.cat((points_rot, points[:, :, 3:]), dim=-1)
return points_rot.numpy() if is_numpy else points_rot
def boxes_to_corners_3d(boxes3d):
"""
7 -------- 4
/| /|
6 -------- 5 .
| | | |
. 3 -------- 0
|/ |/
2 -------- 1
Args:
boxes3d: (N, 7) [x, y, z, dx, dy, dz, heading], (x, y, z) is the box center
Returns:
"""
boxes3d, is_numpy = check_numpy_to_torch(boxes3d)
template = boxes3d.new_tensor((
[1, 1, -1], [1, -1, -1], [-1, -1, -1], [-1, 1, -1],
[1, 1, 1], [1, -1, 1], [-1, -1, 1], [-1, 1, 1],
)) / 2
corners3d = boxes3d[:, None, 3:6].repeat(1, 8, 1) * template[None, :, :]
corners3d = rotate_points_along_z(corners3d.view(-1, 8, 3), boxes3d[:, 6]).view(-1, 8, 3)
corners3d += boxes3d[:, None, 0:3]
return corners3d.numpy() if is_numpy else corners3d
def visualize_pts(pts, fig=None, bgcolor=(0, 0, 0), fgcolor=(1.0, 1.0, 1.0),
show_intensity=False, size=(600, 600), draw_origin=True):
if not isinstance(pts, np.ndarray):
pts = pts.cpu().numpy()
if fig is None:
fig = mlab.figure(figure=None, bgcolor=bgcolor, fgcolor=fgcolor, engine=None, size=size)
if show_intensity:
G = mlab.points3d(pts[:, 0], pts[:, 1], pts[:, 2], pts[:, 3], mode='point',
colormap='gnuplot', scale_factor=1, figure=fig)
else:
G = mlab.points3d(pts[:, 0], pts[:, 1], pts[:, 2], mode='point',
colormap='gnuplot', scale_factor=1, figure=fig)
if draw_origin:
mlab.points3d(0, 0, 0, color=(1, 1, 1), mode='cube', scale_factor=0.2)
mlab.plot3d([0, 3], [0, 0], [0, 0], color=(0, 0, 1), tube_radius=0.1)
mlab.plot3d([0, 0], [0, 3], [0, 0], color=(0, 1, 0), tube_radius=0.1)
mlab.plot3d([0, 0], [0, 0], [0, 3], color=(1, 0, 0), tube_radius=0.1)
return fig
def draw_sphere_pts(pts, color=(0, 1, 0), fig=None, bgcolor=(0, 0, 0), scale_factor=0.2):
if not isinstance(pts, np.ndarray):
pts = pts.cpu().numpy()
if fig is None:
fig = mlab.figure(figure=None, bgcolor=bgcolor, fgcolor=None, engine=None, size=(600, 600))
if isinstance(color, np.ndarray) and color.shape[0] == 1:
color = color[0]
color = (color[0] / 255.0, color[1] / 255.0, color[2] / 255.0)
if isinstance(color, np.ndarray):
pts_color = np.zeros((pts.__len__(), 4), dtype=np.uint8)
pts_color[:, 0:3] = color
pts_color[:, 3] = 255
G = mlab.points3d(pts[:, 0], pts[:, 1], pts[:, 2], np.arange(0, pts_color.__len__()), mode='sphere',
scale_factor=scale_factor, figure=fig)
G.glyph.color_mode = 'color_by_scalar'
G.glyph.scale_mode = 'scale_by_vector'
G.module_manager.scalar_lut_manager.lut.table = pts_color
else:
mlab.points3d(pts[:, 0], pts[:, 1], pts[:, 2], mode='sphere', color=color,
colormap='gnuplot', scale_factor=scale_factor, figure=fig)
mlab.points3d(0, 0, 0, color=(1, 1, 1), mode='cube', scale_factor=0.2)
mlab.plot3d([0, 3], [0, 0], [0, 0], color=(0, 0, 1), line_width=3, tube_radius=None, figure=fig)
mlab.plot3d([0, 0], [0, 3], [0, 0], color=(0, 1, 0), line_width=3, tube_radius=None, figure=fig)
mlab.plot3d([0, 0], [0, 0], [0, 3], color=(1, 0, 0), line_width=3, tube_radius=None, figure=fig)
return fig
def draw_grid(x1, y1, x2, y2, fig, tube_radius=None, color=(0.5, 0.5, 0.5)):
mlab.plot3d([x1, x1], [y1, y2], [0, 0], color=color, tube_radius=tube_radius, line_width=1, figure=fig)
mlab.plot3d([x2, x2], [y1, y2], [0, 0], color=color, tube_radius=tube_radius, line_width=1, figure=fig)
mlab.plot3d([x1, x2], [y1, y1], [0, 0], color=color, tube_radius=tube_radius, line_width=1, figure=fig)
mlab.plot3d([x1, x2], [y2, y2], [0, 0], color=color, tube_radius=tube_radius, line_width=1, figure=fig)
return fig
def draw_multi_grid_range(fig, grid_size=20, bv_range=(-60, -60, 60, 60)):
for x in range(bv_range[0], bv_range[2], grid_size):
for y in range(bv_range[1], bv_range[3], grid_size):
fig = draw_grid(x, y, x + grid_size, y + grid_size, fig)
return fig
def draw_scenes(points, gt_boxes=None, ref_boxes=None, ref_scores=None, ref_labels=None):
if not isinstance(points, np.ndarray):
points = points.cpu().numpy()
if ref_boxes is not None and not isinstance(ref_boxes, np.ndarray):
ref_boxes = ref_boxes.cpu().numpy()
if gt_boxes is not None and not isinstance(gt_boxes, np.ndarray):
gt_boxes = gt_boxes.cpu().numpy()
if ref_scores is not None and not isinstance(ref_scores, np.ndarray):
ref_scores = ref_scores.cpu().numpy()
if ref_labels is not None and not isinstance(ref_labels, np.ndarray):
ref_labels = ref_labels.cpu().numpy()
fig = visualize_pts(points)
fig = draw_multi_grid_range(fig, bv_range=(0, -40, 80, 40))
if gt_boxes is not None:
corners3d = boxes_to_corners_3d(gt_boxes)
fig = draw_corners3d(corners3d, fig=fig, color=(0, 0, 1), max_num=100)
if ref_boxes is not None and len(ref_boxes) > 0:
ref_corners3d = boxes_to_corners_3d(ref_boxes)
if ref_labels is None:
fig = draw_corners3d(ref_corners3d, fig=fig, color=(0, 1, 0), cls=ref_scores, max_num=100)
else:
for k in range(ref_labels.min(), ref_labels.max() + 1):
cur_color = tuple(box_colormap[k % len(box_colormap)])
mask = (ref_labels == k)
fig = draw_corners3d(ref_corners3d[mask], fig=fig, color=cur_color, cls=ref_scores[mask], max_num=100)
mlab.view(azimuth=-179, elevation=54.0, distance=104.0, roll=90.0)
return fig
def draw_corners3d(corners3d, fig, color=(1, 1, 1), line_width=2, cls=None, tag='', max_num=500, tube_radius=None):
"""
:param corners3d: (N, 8, 3)
:param fig:
:param color:
:param line_width:
:param cls:
:param tag:
:param max_num:
:return:
"""
import mayavi.mlab as mlab
num = min(max_num, len(corners3d))
for n in range(num):
b = corners3d[n] # (8, 3)
if cls is not None:
if isinstance(cls, np.ndarray):
mlab.text3d(b[6, 0], b[6, 1], b[6, 2], '%.2f' % cls[n], scale=(0.3, 0.3, 0.3), color=color, figure=fig)
else:
mlab.text3d(b[6, 0], b[6, 1], b[6, 2], '%s' % cls[n], scale=(0.3, 0.3, 0.3), color=color, figure=fig)
for k in range(0, 4):
i, j = k, (k + 1) % 4
mlab.plot3d([b[i, 0], b[j, 0]], [b[i, 1], b[j, 1]], [b[i, 2], b[j, 2]], color=color, tube_radius=tube_radius,
line_width=line_width, figure=fig)
i, j = k + 4, (k + 1) % 4 + 4
mlab.plot3d([b[i, 0], b[j, 0]], [b[i, 1], b[j, 1]], [b[i, 2], b[j, 2]], color=color, tube_radius=tube_radius,
line_width=line_width, figure=fig)
i, j = k, k + 4
mlab.plot3d([b[i, 0], b[j, 0]], [b[i, 1], b[j, 1]], [b[i, 2], b[j, 2]], color=color, tube_radius=tube_radius,
line_width=line_width, figure=fig)
i, j = 0, 5
mlab.plot3d([b[i, 0], b[j, 0]], [b[i, 1], b[j, 1]], [b[i, 2], b[j, 2]], color=color, tube_radius=tube_radius,
line_width=line_width, figure=fig)
i, j = 1, 4
mlab.plot3d([b[i, 0], b[j, 0]], [b[i, 1], b[j, 1]], [b[i, 2], b[j, 2]], color=color, tube_radius=tube_radius,
line_width=line_width, figure=fig)
return fig