The self.set_attributes is a method in the sub-class. Is this a good design ? Perhaps the super class should only do a basic setup and actual setup should be sub-classes ?

class Sensor:
    initial_ts = 0.0
    initial_loc = carla.Location()
    initial_rot = carla.Rotation()

    def __init__(self, vehicle, world, actor_list, output_folder, transform):
        self.queue = queue.Queue()
        self.bp = self.set_attributes(world.get_blueprint_library())

Hello @jedeschaud ,

The code for the function:

def transform_lidar_to_camera(lidar_transform, camera_transform):
    R_camera_vehicle = rotation_carla(camera_transform.rotation)
    R_lidar_vehicle = np.identity(3) #rotation_carla(lidar_tranform.rotation) #we want the lidar frame to have x forward
    R_lidar_camera = R_camera_vehicle.T.dot(R_lidar_vehicle)
    T_lidar_camera = R_camera_vehicle.T.dot(translation_carla(np.array([[lidar_transform.location.x],[lidar_transform.location.y],[lidar_transform.location.z]])-np.array([[camera_transform.location.x],[camera_transform.location.y],[camera_transform.location.z]])))
    return np.vstack((np.hstack((R_lidar_camera, T_lidar_camera)), [0,0,0,1]))


According to this post: https://robotics.stackexchange.com/questions/21401/how-to-make-two-frames-relative-to-each-other

R_lidar_camera = R_camera_vehicle.T.dot(R_lidar_vehicle) should be 
R_lidar_camera = R_lidar_vehicle.T.dot(R_camera_vehicle)

Also the difference in translation is: translation_carla(np.array([[lidar_transform.location.x],[lidar_transform.location.y],[lidar_transform.location.z]])-np.array([[camera_transform.location.x],[camera_transform.location.y],[camera_transform.location.z]])))

Should it not be camera - lidar ?

I have noticed that if I change fps_simu to fps_simu=10 instead of 1000. Simulation runs faster, but I am not sure how it influence data generation and will it influence the final output which is supposed to be KITTI like. Do you have any suggestions on how I should approach this? Thanks

hi, i want to download dataset form https://npm3d.fr/kitti-carla , but the speed is too slow，the download failed soon, Is there any solution to this problem?

The current version of KITTI 3D dataset has the points clouds in .bin format, and I noticed that the code saves in .ply. Am I missing something?

Thanks for sharing the code!

Hello @jedeschaud ,

How are these fixed transforms are determined ?
As I understand the (0,0,0) of a car is fixed to be the middle of the rear axle

 # Set sensors transformation from KITTI
            lidar_transform = carla.Transform(carla.Location(x=0, y=0, z=1.80), carla.Rotation(pitch=0, yaw=180, roll=0))
            cam0_transform = carla.Transform(carla.Location(x=0.30, y=0, z=1.70), carla.Rotation(pitch=0, yaw=0, roll=0))
            cam1_transform = carla.Transform(carla.Location(x=0.30, y=0.50, z=1.70), carla.Rotation(pitch=0, yaw=0, roll=0))


Atleast from the KITTI sensor setup diagram I cant seem to figure out how atleast the Location is decided from a CARLA left hand rule perspective..

Since the KITTI-CARLA is an (almost) exact simulation of the KITTI, can I reuse the calib.txt file in data_odometry_calib.zip file ?

The contents of the calib.txt file in each of the sequences is as follows:

P0: 7.188560000000e+02 0.000000000000e+00 6.071928000000e+02 0.000000000000e+00 0.000000000000e+00 7.188560000000e+02 1.852157000000e+02 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 1.000000000000e+00 0.000000000000e+00
P1: 7.188560000000e+02 0.000000000000e+00 6.071928000000e+02 -3.861448000000e+02 0.000000000000e+00 7.188560000000e+02 1.852157000000e+02 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 1.000000000000e+00 0.000000000000e+00
P2: 7.188560000000e+02 0.000000000000e+00 6.071928000000e+02 4.538225000000e+01 0.000000000000e+00 7.188560000000e+02 1.852157000000e+02 -1.130887000000e-01 0.000000000000e+00 0.000000000000e+00 1.000000000000e+00 3.779761000000e-03
P3: 7.188560000000e+02 0.000000000000e+00 6.071928000000e+02 -3.372877000000e+02 0.000000000000e+00 7.188560000000e+02 1.852157000000e+02 2.369057000000e+00 0.000000000000e+00 0.000000000000e+00 1.000000000000e+00 4.915215000000e-03
Tr: 4.276802385584e-04 -9.999672484946e-01 -8.084491683471e-03 -1.198459927713e-02 -7.210626507497e-03 8.081198471645e-03 -9.999413164504e-01 -5.403984729748e-02 9.999738645903e-01 4.859485810390e-04 -7.206933692422e-03 -2.921968648686e-01

Hello @jedeschaud I have found that the labels are ot present in the given synthetic dataset. I am working on synthetic to realistic point cloud data conversion. Please help on this

I changed number of frames from 5000 to 50 and when loading the second map the program seg faults

Export : KITTI_Dataset_CARLA_v0.9.12/Carla/Maps/Town01/generated/images_depth/0049_20.png
Export : KITTI_Dataset_CARLA_v0.9.12/Carla/Maps/Town01/generated/images_depth/0049_21.png
Export : KITTI_Dataset_CARLA_v0.9.12/Carla/Maps/Town01/generated/frames/frame_0049.ply
Export : KITTI_Dataset_CARLA_v0.9.12/Carla/Maps/Town01/generated/poses_lidar.ply
Stop record
Destroying 50 vehicles
Destroying 32 walkers
Destroying KITTI
Elapsed time : 71.06980013847351

Map Town02
Segmentation fault (core dumped)

Anyone seen this problem before ?

It seems to work only one town at a time.

python KITTI_data_generator.py
Map Town02
Created Actor(id=135, type=vehicle.tesla.model3)
Number of spawn points : 101

..

Stop record
Destroying 50 vehicles
Destroying 33 walkers
Destroying KITTI
Elapsed time : 65.43478298187256

Map Town03
Segmentation fault (core dumped)

python KITTI_data_generator.py

Map Town01
Created Actor(id=1669, type=vehicle.tesla.model3)
('Number of spawn points : ', 255)
Spawned 1 vehicles and 1 walkers
Waiting for KITTI to stop ...
KITTI stopped
('Elapsed total time : ', 35.62052607536316)
Traceback (most recent call last):
File "KITTI_data_generator.py", line 177, in
main()
File "KITTI_data_generator.py", line 86, in main
gen.screenshot(KITTI, world, actor_list, folder_output, carla.Transform(carla.Location(x=0.0, y=0, z=2.0), carla.Rotation(pitch=0, yaw=0, roll=0)))
File "/home/libing/source/simulator/kitti_carla_simulator/generator_KITTI.py", line 297, in screenshot
RGB.set_attributes(world.get_blueprint_library())
TypeError: unbound method set_attributes() must be called with RGB instance as first argument (got BlueprintLibrary instance instead)

Can anyone say what the benefit of having the LIDAR point backwards ?
lidar_transform = carla.Transform(carla.Location(x=0, y=0, z=1.80), carla.Rotation(pitch=0, yaw=180, roll=0))

Also the lidar to camera translation makes difference of lidar to camera

T_lidar_camera = R_camera_vehicle.T.dot(translation_carla(np.array([[lidar_transform.location.x],[lidar_transform.location.y],[lidar_transform.location.z]])-np.array([[camera_transform.location.x],[camera_transform.location.y],[camera_transform.location.z]])))

Should it not be the other way around ?
@jedeschaud, Could you give some hints on this ?

Also the sensors are not synchronized:

Camera data timestamp:  3.4262565394164994
Export: KITTI_Dataset_CARLA_v0.9.12/Carla/Maps/Town07/generated/image_2/000000.pngSaving lidar pointcloud at timestamp  3.525256544118747
Export: KITTI_Dataset_CARLA_v0.9.12/Carla/Maps/Town07/generated/velodyne/000000.bin

KITTI paper:

1. Height of LIDAR: 1.73m
2. Height of Cameras: 1.65m
3. Distance between the stereo cameras is 0.54m

But in the scripts :

1. Height of LIDAR to be: 1.80m
   "The LiDAR is attached to the vehicle body with a global
   translation of (X = 0.0m, Y = 0.0m, Z = 1.80m)"

2. Height of cameras to be: 1.70m

3. Distance between the stereo cameras to be: 0.50m
   "Cameras are attached to the vehicle body with a global translation of (X = 0.30m, Y = 0.0m, Z = 1.70m)
   for camera 0 and (X = 0.30m, Y = 0.50m, Z = 1.70m) for
   camera 1"

Are these ok for a working code ? Or does usage of CARLA have something to do with this ?

When I run the data generation code, after one map there are always errors ERROR: Invalid session: no stream available with id, do you know how to solve it? It seems that it is because the sensors are not deleted totally.