whyekit-motional
commented
1 year ago @glebss I think you are close :smile:
The dots in your rendering probably belong to lane dividers / road dividers that are behind the hill
I made some edits to your code (and left you some comments to explain why I made those changes), and chosen another sample to better show the rendered lane dividers / road dividers:
import numpy as np
from PIL import Image
from pyquaternion import Quaternion
import matplotlib.pyplot as plt
from nuscenes.map_expansion.map_api import NuScenesMap
from nuscenes.nuscenes import NuScenes
from nuscenes.utils.geometry_utils import view_points
dataroot = '/data/sets/nuscenes/'
nusc = NuScenes(version='v1.0-mini', dataroot=dataroot, verbose=True)
nusc_map = NuScenesMap(dataroot=dataroot, map_name='singapore-onenorth')
patch_radius = 50 # 1000 is too much, and will lead to map objects which are too far away from the camera being rendered.
near_plane = 1e-8
sample_token = nusc.sample[0]['token']
layer_names = ['road_divider', 'lane_divider']
camera_channel = 'CAM_FRONT'
sample_record = nusc.get('sample', sample_token)
scene_record = nusc.get('scene', sample_record['scene_token'])
log_record = nusc.get('log', scene_record['log_token'])
log_location = log_record['location']
assert log_location == nusc_map.map_name
cam_token = sample_record['data'][camera_channel]
cam_record = nusc.get('sample_data', cam_token)
cam_path = nusc.get_sample_data_path(cam_token)
im = Image.open(cam_path)
im_size = im.size
cs_record = nusc.get('calibrated_sensor', cam_record['calibrated_sensor_token'])
cam_intrinsic = np.array(cs_record['camera_intrinsic'])
poserecord = nusc.get('ego_pose', cam_record['ego_pose_token'])
ego_pose = poserecord['translation']
box_coords = (
ego_pose[0] - patch_radius,
ego_pose[1] - patch_radius,
ego_pose[0] + patch_radius,
ego_pose[1] + patch_radius,
)
records_in_patch = nusc_map.explorer.get_records_in_patch(box_coords, layer_names)
fig = plt.figure(figsize=(9, 16))
ax = fig.add_axes([0, 0, 1, 1])
ax.set_xlim(0, im_size[0])
ax.set_ylim(0, im_size[1])
ax.imshow(im)
for layer_name in layer_names:
for token in records_in_patch[layer_name]:
record = nusc_map.explorer.map_api.get(layer_name, token)
line_token = record['line_token']
line = nusc_map.explorer.map_api.extract_line(line_token)
points = np.array(line.xy)
points = np.vstack((points, np.zeros((1, points.shape[1]))))
# Transform into the ego vehicle frame for the timestamp of the image.
points = points - np.array(poserecord['translation']).reshape((-1, 1))
points = np.dot(Quaternion(poserecord['rotation']).rotation_matrix.T, points)
# Transform into camera.
points = points - np.array(cs_record['translation']).reshape((-1, 1))
points = np.dot(Quaternion(cs_record['rotation']).rotation_matrix.T, points)
# depths = points[2, :]
# behind = depths < near_plane
# if np.all(behind):
# continue
# Get points belonging to the map objects which are not behind the camera,
# and not too far away in front of the camera.
depths = points[2, :]
points = points[:, (depths > 0) & (depths < patch_radius)]
points = view_points(points, cam_intrinsic, normalize=True)
inside = np.ones(points.shape[1], dtype=bool)
inside = np.logical_and(inside, points[0, :] > 1)
inside = np.logical_and(inside, points[0, :] < im.size[0] - 1)
inside = np.logical_and(inside, points[1, :] > 1)
inside = np.logical_and(inside, points[1, :] < im.size[1] - 1)
if np.all(np.logical_not(inside)):
continue
points = points[:2, :]
points = [(p0, p1) for (p0, p1) in zip(points[0], points[1])]
xs = [p[0] for p in points]
ys = [p[1] for p in points]
# plt.scatter(xs, ys, s=1, c='r')
plt.plot(xs, ys, 'ro', linestyle="--") # Render using lines instead, since the markings are lines.
plt.axis('off')
ax.invert_yaxis()The above edits produce the following rendering:
glebss
Hello.
I am trying to extract the
road_dividerandlane_dividerlayers from the map and convert them to the markup in the camera image. I use the source code from the render_map_in_image function as a basis.Below is the code I use:
However, this code doesn't work right. The resulting rendered lines look like this:
In what part of the presented code am I doing something wrong? Any help is appreciated.
Thanks.