Spaces:
Running
Running
File size: 5,207 Bytes
9223079 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 |
"""
3D visualization based on plotly.
Works for a small number of points and cameras, might be slow otherwise.
1) Initialize a figure with `init_figure`
2) Add 3D points, camera frustums, or both as a pycolmap.Reconstruction
Written by Paul-Edouard Sarlin and Philipp Lindenberger.
"""
from typing import Optional
import numpy as np
import pycolmap
import plotly.graph_objects as go
def to_homogeneous(points):
pad = np.ones((points.shape[:-1] + (1,)), dtype=points.dtype)
return np.concatenate([points, pad], axis=-1)
def init_figure(height: int = 800) -> go.Figure:
"""Initialize a 3D figure."""
fig = go.Figure()
axes = dict(
visible=False,
showbackground=False,
showgrid=False,
showline=False,
showticklabels=True,
autorange=True,
)
fig.update_layout(
template="plotly_dark",
height=height,
scene_camera=dict(
eye=dict(x=0.0, y=-0.1, z=-2),
up=dict(x=0, y=-1.0, z=0),
projection=dict(type="orthographic"),
),
scene=dict(
xaxis=axes,
yaxis=axes,
zaxis=axes,
aspectmode="data",
dragmode="orbit",
),
margin=dict(l=0, r=0, b=0, t=0, pad=0),
legend=dict(orientation="h", yanchor="top", y=0.99, xanchor="left", x=0.1),
)
return fig
def plot_points(
fig: go.Figure,
pts: np.ndarray,
color: str = "rgba(255, 0, 0, 1)",
ps: int = 2,
colorscale: Optional[str] = None,
name: Optional[str] = None,
):
"""Plot a set of 3D points."""
x, y, z = pts.T
tr = go.Scatter3d(
x=x,
y=y,
z=z,
mode="markers",
name=name,
legendgroup=name,
marker=dict(size=ps, color=color, line_width=0.0, colorscale=colorscale),
)
fig.add_trace(tr)
def plot_camera(
fig: go.Figure,
R: np.ndarray,
t: np.ndarray,
K: np.ndarray,
color: str = "rgb(0, 0, 255)",
name: Optional[str] = None,
legendgroup: Optional[str] = None,
size: float = 1.0,
):
"""Plot a camera frustum from pose and intrinsic matrix."""
W, H = K[0, 2] * 2, K[1, 2] * 2
corners = np.array([[0, 0], [W, 0], [W, H], [0, H], [0, 0]])
if size is not None:
image_extent = max(size * W / 1024.0, size * H / 1024.0)
world_extent = max(W, H) / (K[0, 0] + K[1, 1]) / 0.5
scale = 0.5 * image_extent / world_extent
else:
scale = 1.0
corners = to_homogeneous(corners) @ np.linalg.inv(K).T
corners = (corners / 2 * scale) @ R.T + t
x, y, z = corners.T
rect = go.Scatter3d(
x=x,
y=y,
z=z,
line=dict(color=color),
legendgroup=legendgroup,
name=name,
marker=dict(size=0.0001),
showlegend=False,
)
fig.add_trace(rect)
x, y, z = np.concatenate(([t], corners)).T
i = [0, 0, 0, 0]
j = [1, 2, 3, 4]
k = [2, 3, 4, 1]
pyramid = go.Mesh3d(
x=x,
y=y,
z=z,
color=color,
i=i,
j=j,
k=k,
legendgroup=legendgroup,
name=name,
showlegend=False,
)
fig.add_trace(pyramid)
triangles = np.vstack((i, j, k)).T
vertices = np.concatenate(([t], corners))
tri_points = np.array([vertices[i] for i in triangles.reshape(-1)])
x, y, z = tri_points.T
pyramid = go.Scatter3d(
x=x,
y=y,
z=z,
mode="lines",
legendgroup=legendgroup,
name=name,
line=dict(color=color, width=1),
showlegend=False,
)
fig.add_trace(pyramid)
def plot_camera_colmap(
fig: go.Figure,
image: pycolmap.Image,
camera: pycolmap.Camera,
name: Optional[str] = None,
**kwargs
):
"""Plot a camera frustum from PyCOLMAP objects"""
plot_camera(
fig,
image.rotmat().T,
image.projection_center(),
camera.calibration_matrix(),
name=name or str(image.image_id),
**kwargs
)
def plot_cameras(fig: go.Figure, reconstruction: pycolmap.Reconstruction, **kwargs):
"""Plot a camera as a cone with camera frustum."""
for image_id, image in reconstruction.images.items():
plot_camera_colmap(
fig, image, reconstruction.cameras[image.camera_id], **kwargs
)
def plot_reconstruction(
fig: go.Figure,
rec: pycolmap.Reconstruction,
max_reproj_error: float = 6.0,
color: str = "rgb(0, 0, 255)",
name: Optional[str] = None,
min_track_length: int = 2,
points: bool = True,
cameras: bool = True,
cs: float = 1.0,
):
# Filter outliers
bbs = rec.compute_bounding_box(0.001, 0.999)
# Filter points, use original reproj error here
xyzs = [
p3D.xyz
for _, p3D in rec.points3D.items()
if (
(p3D.xyz >= bbs[0]).all()
and (p3D.xyz <= bbs[1]).all()
and p3D.error <= max_reproj_error
and p3D.track.length() >= min_track_length
)
]
if points:
plot_points(fig, np.array(xyzs), color=color, ps=1, name=name)
if cameras:
plot_cameras(fig, rec, color=color, legendgroup=name, size=cs)
|