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Zero
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import os
from PIL import Image
import plotly.graph_objects as go
import numpy as np
def calc_cam_cone_pts_3d(c2w, fov_deg, zoom = 1.0):
fov_rad = np.deg2rad(fov_deg)
cam_x = c2w[0, -1]
cam_y = c2w[1, -1]
cam_z = c2w[2, -1]
corn1 = [np.tan(fov_rad / 2.0), np.tan(fov_rad / 2.0), -1.0]
corn2 = [-np.tan(fov_rad / 2.0), np.tan(fov_rad / 2.0), -1.0]
corn3 = [-np.tan(fov_rad / 2.0), -np.tan(fov_rad / 2.0), -1.0]
corn4 = [np.tan(fov_rad / 2.0), -np.tan(fov_rad / 2.0), -1.0]
corn5 = [0, np.tan(fov_rad / 2.0), -1.0]
corn1 = np.dot(c2w[:3, :3], corn1)
corn2 = np.dot(c2w[:3, :3], corn2)
corn3 = np.dot(c2w[:3, :3], corn3)
corn4 = np.dot(c2w[:3, :3], corn4)
corn5 = np.dot(c2w[:3, :3], corn5)
# Now attach as offset to actual 3D camera position:
corn1 = np.array(corn1) / np.linalg.norm(corn1, ord=2) * zoom
corn_x1 = cam_x + corn1[0]
corn_y1 = cam_y + corn1[1]
corn_z1 = cam_z + corn1[2]
corn2 = np.array(corn2) / np.linalg.norm(corn2, ord=2) * zoom
corn_x2 = cam_x + corn2[0]
corn_y2 = cam_y + corn2[1]
corn_z2 = cam_z + corn2[2]
corn3 = np.array(corn3) / np.linalg.norm(corn3, ord=2) * zoom
corn_x3 = cam_x + corn3[0]
corn_y3 = cam_y + corn3[1]
corn_z3 = cam_z + corn3[2]
corn4 = np.array(corn4) / np.linalg.norm(corn4, ord=2) * zoom
corn_x4 = cam_x + corn4[0]
corn_y4 = cam_y + corn4[1]
corn_z4 = cam_z + corn4[2]
corn5 = np.array(corn5) / np.linalg.norm(corn5, ord=2) * zoom
corn_x5 = cam_x + corn5[0]
corn_y5 = cam_y + corn5[1]
corn_z5 = cam_z + corn5[2]
xs = [cam_x, corn_x1, corn_x2, corn_x3, corn_x4, corn_x5]
ys = [cam_y, corn_y1, corn_y2, corn_y3, corn_y4, corn_y5]
zs = [cam_z, corn_z1, corn_z2, corn_z3, corn_z4, corn_z5]
return np.array([xs, ys, zs]).T
class CameraVisualizer:
def __init__(self, poses, legends, colors, images=None, mesh_path=None, camera_x=1.0):
self._fig = None
self._camera_x = camera_x
self._poses = poses
self._legends = legends
self._colors = colors
self._raw_images = None
self._bit_images = None
self._image_colorscale = None
self.set_images(images)
self._mesh = None
if mesh_path is not None and os.path.exists(mesh_path):
import trimesh
self._mesh = trimesh.load(mesh_path, force='mesh')
def set_images(self, images):
if images is not None:
self._raw_images = images
self._bit_images = []
self._image_colorscale = []
for img in images:
if img is None:
self._bit_images.append(None)
self._image_colorscale.append(None)
continue
bit_img, colorscale = self.encode_image(img)
self._bit_images.append(bit_img)
self._image_colorscale.append(colorscale)
def encode_image(self, raw_image):
'''
:param raw_image (H, W, 3) array of uint8 in [0, 255].
'''
# https://stackoverflow.com/questions/60685749/python-plotly-how-to-add-an-image-to-a-3d-scatter-plot
dum_img = Image.fromarray(np.ones((3, 3, 3), dtype='uint8')).convert('P', palette='WEB')
idx_to_color = np.array(dum_img.getpalette()).reshape((-1, 3))
bit_image = Image.fromarray(raw_image).convert('P', palette='WEB', dither=None)
# bit_image = Image.fromarray(raw_image.clip(0, 254)).convert(
# 'P', palette='WEB', dither=None)
colorscale = [[i / 255.0, 'rgb({}, {}, {})'.format(*rgb)] for i, rgb in enumerate(idx_to_color)]
return bit_image, colorscale
def update_figure(
self, scene_bounds,
base_radius=0.0, zoom_scale=1.0, fov_deg=50.,
mesh_z_shift=0.0, mesh_scale=1.0,
font_size=10,
show_background=False, show_grid=False, show_ticklabels=False
):
fig = go.Figure()
if self._mesh is not None:
fig.add_trace(
go.Mesh3d(
x=self._mesh.vertices[:, 0] * mesh_scale,
y=self._mesh.vertices[:, 2] * -mesh_scale,
z=(self._mesh.vertices[:, 1] + mesh_z_shift) * mesh_scale,
i=self._mesh.faces[:, 0],
j=self._mesh.faces[:, 1],
k=self._mesh.faces[:, 2],
color=None,
facecolor=None,
opacity=0.8,
lighting={'ambient': 1},
)
)
for i in range(len(self._poses)):
pose = self._poses[i]
clr = self._colors[i]
legend = self._legends[i]
edges = [(0, 1), (0, 2), (0, 3), (0, 4), (1, 2), (2, 3), (3, 4), (4, 1), (0, 5)]
cone = calc_cam_cone_pts_3d(pose, fov_deg)
radius = np.linalg.norm(pose[:3, -1])
if self._bit_images and self._bit_images[i]:
raw_image = self._raw_images[i]
bit_image = self._bit_images[i]
colorscale = self._image_colorscale[i]
(H, W, C) = raw_image.shape
z = np.zeros((H, W)) + base_radius
(x, y) = np.meshgrid(np.linspace(-1.0 * self._camera_x, 1.0 * self._camera_x, W), np.linspace(1.0, -1.0, H) * H / W)
xyz = np.concatenate([x[..., None], y[..., None], z[..., None]], axis=-1)
rot_xyz = np.matmul(xyz, pose[:3, :3].T) + pose[:3, -1]
x, y, z = rot_xyz[:, :, 0], rot_xyz[:, :, 1], rot_xyz[:, :, 2]
fig.add_trace(go.Surface(
x=x, y=y, z=z,
surfacecolor=bit_image,
cmin=0,
cmax=255,
colorscale=colorscale,
showscale=False,
lighting_diffuse=1.0,
lighting_ambient=1.0,
lighting_fresnel=1.0,
lighting_roughness=1.0,
lighting_specular=0.3))
for (i, edge) in enumerate(edges):
(x1, x2) = (cone[edge[0], 0], cone[edge[1], 0])
(y1, y2) = (cone[edge[0], 1], cone[edge[1], 1])
(z1, z2) = (cone[edge[0], 2], cone[edge[1], 2])
fig.add_trace(go.Scatter3d(
x=[x1, x2], y=[y1, y2], z=[z1, z2], mode='lines',
line=dict(color=clr, width=3),
name=legend, showlegend=(i == 0)))
# Add label.
if cone[0, 2] < 0:
fig.add_trace(go.Scatter3d(
x=[cone[0, 0]], y=[cone[0, 1]], z=[cone[0, 2] - 0.05], showlegend=False,
mode='text', text=legend, textfont=dict(color=clr, size=font_size), textposition='bottom center'))
else:
fig.add_trace(go.Scatter3d(
x=[cone[0, 0]], y=[cone[0, 1]], z=[cone[0, 2] + 0.05], showlegend=False,
mode='text', text=legend, textfont=dict(color=clr, size=font_size), textposition='top center'))
# look at the center of scene
fig.update_layout(
height=720,
autosize=True,
hovermode=False,
margin=go.layout.Margin(l=0, r=0, b=0, t=0),
showlegend=True,
legend=dict(
yanchor='bottom',
y=0.01,
xanchor='right',
x=0.99,
),
scene=dict(
aspectmode='manual',
aspectratio=dict(x=1, y=1, z=1),
camera=dict(
eye=dict(x=1.5, y=1.5, z=1.0),
center=dict(x=0.0, y=0.0, z=0.0),
up=dict(x=0.0, y=0.0, z=1.0)),
xaxis_title='x',
yaxis_title='y',
zaxis_title='z',
xaxis=dict(
range=[-scene_bounds, scene_bounds],
showticklabels=show_ticklabels,
showgrid=show_grid,
zeroline=False,
showbackground=show_background,
showspikes=False,
showline=False,
ticks=''),
yaxis=dict(
range=[-scene_bounds, scene_bounds],
showticklabels=show_ticklabels,
showgrid=show_grid,
zeroline=False,
showbackground=show_background,
showspikes=False,
showline=False,
ticks=''),
zaxis=dict(
range=[-scene_bounds, scene_bounds],
showticklabels=show_ticklabels,
showgrid=show_grid,
zeroline=False,
showbackground=show_background,
showspikes=False,
showline=False,
ticks='')
)
)
self._fig = fig
return fig |