Hi, Xiaoyang! I'm trying to reimplement your awesome work.

In 'Getting Started', you mentioned 'Generate the data infos by running the following command:'

python -m liga.datasets.kitti.kitti_dataset create_kitti_infos
python -m liga.datasets.kitti.kitti_dataset create_gt_database_only

Unfortunately, these are only 'lidar_kitti_dataset' and 'stereo_kitti_dataset' in './liga/datasets/kitti/'. I successfully created kitti_infos and gt_database by running python -m liga.datasets.kitti.lidar_kitti_dataset create_kitti_infos and python -m liga.datasets.kitti.lidar_kitti_dataset create_gt_database_only.

However, I don't know how to create kitti_infos for the stereo detector. When I ran python -m liga.datasets.kitti.stereo_kitti_dataset create_kitti_infos, I found that I can't get the .pkl files (kitti_infos) because there is no 'create_kitti_infos()' and 'create_gt_database_only' in stereo_kitti_dataset create_kitti_infos.py.

More directly, if I want to train the whole LIGA-Stereo instead of just the modified SECOND, should I first create kitti_infos for the Stereo detector and then run ./scripts/dist_train.sh ${NUM_GPUS} 'exp_name' ./configs/stereo/kitti_models/liga.3d-and-bev.yaml?

Look forward to your answer!

Hi, thanks for your great work! I have a question about the coordinate system.

I notice that in the stereo_kitti_dataset.py file， there is the introduction of a pseudo-lidar coordinate system.

https://github.com/xy-guo/LIGA-Stereo/blob/aee3731a24a0ab1667e633e520cc89be2f135272/liga/datasets/kitti/stereo_kitti_dataset.py#L366

I would like to know why this function is not rect_to_lidar, but rect_to_lidar_pseudo? Is there any difference in labelling between double and single purpose?

Thanks for your great work~

When I run the following commands: python -m liga.datasets.kitti.kitti_dataset create_kitti_infos python -m liga.datasets.kitti.kitti_dataset create_gt_database_only

An error comes to me: No module named liga.datasets.kitti.kitti_dataset

I find that there are only stereo_kitti_dataset.py and lidar_kitti_dataset.py in the path: liga/datasets/kitti/ Any suggestions would be deeply appreciated! Thanks again.

Hi Xiaoyang! Thanks for your great work. In the Introduction of LIGA-Stereo, you mentioned

'Comparing with traditional knowledge distillation for recognition tasks, we did not take the final erroneous classification and regression predictions from the LiDAR model as “soft” targets, which we found benefits little for training stereo detection networks.'

Could you please elaborate on your implementation process and experimental results?

Hello,

Thanks a lot for your wonderful work. I followed the instructions to install mmdet and mmcv. It returned the errors that "cannot import name 'MultiScaleDeformableAttention' from 'mmcv.cnn.bricks.transformer'". It seems that this module is not defined in mmcv.cnn.

I tried other versions, no one can match all the requires of the test repository. Could you please share the versions of mmcv and mmdet that you used in your project.

Thanks in advance. Hoping to hear from you soon.

Best.

Hi！Thanks for sharing your awesome code. But I have some problem when i running this code... My error massages:

data/kitti/training/image_2/001773.png
data/kitti/training/image_2/001816.png
data/kitti/training/image_2/002829.png
data/kitti/training/image_3/001773.png
data/kitti/training/image_3/001816.png
data/kitti/training/image_3/002829.png
{'NAME': 'filter_truncated', 'AREA_RATIO_THRESH': None, 'AREA_2D_RATIO_THRESH': None, 'GT_TRUNCATED_THRESH': 0.98}
filter truncated ratio: null 3d boxes [[ 2.99       -3.87       -0.66499996  4.43        1.84        1.75
  -0.2907964 ]] flipped False image idx 890 frame_id 001773 

/home/users/gaoshiyu01/anaconda3/envs/liga5/lib/python3.7/site-packages/torch/optim/lr_scheduler.py:123: UserWarning: Detected call of `lr_scheduler.step()` before `optimizer.step()`. In PyTorch 1.1.0 and later, you should call them in the opposite order: `optimizer.step()` before `lr_scheduler.step()`.  Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate
  "https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate", UserWarning)
/home/users/gaoshiyu01/anaconda3/envs/liga5/lib/python3.7/site-packages/torch/optim/lr_scheduler.py:143: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
  warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)
data/kitti/training/image_2/004052.png
data/kitti/training/image_3/004052.png
Traceback (most recent call last):
  File "/home/users/gaoshiyu01/anaconda3/envs/liga5/lib/python3.7/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/home/users/gaoshiyu01/anaconda3/envs/liga5/lib/python3.7/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/home/users/gaoshiyu01/anaconda3/envs/liga5/lib/python3.7/site-packages/torch/distributed/launch.py", line 261, in <module>
    main()
  File "/home/users/gaoshiyu01/anaconda3/envs/liga5/lib/python3.7/site-packages/torch/distributed/launch.py", line 257, in main
    cmd=cmd)
subprocess.CalledProcessError: Command '['/home/users/gaoshiyu01/anaconda3/envs/liga5/bin/python', '-u', 'tools/train.py', '--local_rank=1', '--launcher', 'pytorch', '--fix_random_seed', '--sync_bn', '--save_to_file', '--cfg_file', './configs/stereo/kitti_models/liga.3d-and-bev.yaml', '--exp_name', 'test1']' died with <Signals.SIGSEGV: 11>.

Seems like a common bug caused by mmdet, so i followed the instruction from: mmdet bug report and checked my running/compiling libraries with nvcc, but everything seems alright, i still have no idea how to fix it, could you please provide more info, thanks a lot :)

My environment:

• nvcc --version: 10.1
• nvidia-smi: 10.2
• Cudatoolkit: 10.1
• python: 3.7.13
• pytorch: 1.6.0
• spconv : 1.2.1
• mmcv-full: 1.2.1
• mmdet: 2.6.0
• mmpycocotools : 12.0.3

</details>

Hello, Thanks for your excellent work !

I have several problem about distributed training

When i try to "CUDA_VISIBLE_DEVICE=0 python3 tools/train.py --cfg_file ${cfg} --batch_size 1" and "CUDA_VISIBLE_DEVICE=0 ./scripts/dist_train.sh 1 exp cfg_path", it is worked. but when i try to "python3 tools/train.py --cfg_file ${cfg} --batch_size 1" or "CUDA_VISIBLE_DEVICE=0,1,2,3 python3 tools/train.py --cfg_file ${cfg} --batch_size 1" or "CUDA_VISIBLE_DEVICE=0,1,2,3 ./scripts/dist_train.sh 4 exp cfg_path", That are not worked. How can i modify about the code for distributed training?

Hello Xiaoyang,

Thanks a lot for your great contribution! I am facing a problem when I run the following command:

python -m liga.datasets.kitti.kitti_dataset create_kitti_infos python -m liga.datasets.kitti.kitti_dataset create_gt_database_only

First I didn't find "kitti_dataset" in the ~/liga/dataset/kitti/kitti_dataset, but I have lidar_kitti_dataset.py and stereo_kitti_dataset.py instead. Then I run this command "python -m liga.datasets.kitti.kitti_dataset create_kitti_infos", it returned the error: "AttributeError: module 'matplotlib.cbook' has no attribute '_rename_parameter'. "

Any ideas and suggestions will be helpful.

Thanks in advance.

First, thank you for your great work and code.

I saw in your code that you force the batch_size_per_gpu = 1. What's the reason for this config? If I want to train a larger batch size on a single GPU, which parts should I modify?

Look forward to your answer. Thanks.

Thanks to your sharing,but when i first run following codes in my docker containers './scripts/dist_train.sh 1 dev configs/stereo/kitti_models/liga.yaml' or './scripts/dist_test_ckpt.sh 1 ./configs/stereo/kitti_models/liga.yaml ./ckpt/pretrained_liga.pth' nothing to show! If I cancle this processing by ctrl+c, run it again that will show '''bash Traceback (most recent call last): File "tools/train.py", line 211, in main() File "tools/train.py", line 73, in main args.tcp_port, args.local_rank, backend='nccl' File "/root/LIGA-Stereo-master/liga/utils/common_utils.py", line 181, in init_dist_pytorch world_size=num_gpus File "/root/miniconda3/envs/liga/lib/python3.7/site-packages/torch/distributed/distributed_c10d.py", line 422, in init_process_group store, rank, world_size = next(rendezvous_iterator) File "/root/miniconda3/envs/liga/lib/python3.7/site-packages/torch/distributed/rendezvous.py", line 126, in _tcp_rendezvous_handler store = TCPStore(result.hostname, result.port, world_size, start_daemon, timeout) RuntimeError: Address already in use Traceback (most recent call last): File "/root/miniconda3/envs/liga/lib/python3.7/runpy.py", line 193, in _run_module_as_main "main", mod_spec) File "/root/miniconda3/envs/liga/lib/python3.7/runpy.py", line 85, in _run_code exec(code, run_globals) File "/root/miniconda3/envs/liga/lib/python3.7/site-packages/torch/distributed/launch.py", line 261, in main() File "/root/miniconda3/envs/liga/lib/python3.7/site-packages/torch/distributed/launch.py", line 257, in main cmd=cmd) subprocess.CalledProcessError: Command '['/root/miniconda3/envs/liga/bin/python', '-u', 'tools/train.py', '--local_rank=0', '--launcher', 'pytorch', '--fix_random_seed', '--sync_bn', '--save_to_file', '--cfg_file', 'configs/stereo/kitti_models/liga.yaml', '--exp_name', 'dev']' returned non-zero exit status 1. ''' How should I solve it?