zhangyp15 / occformer Goto Github PK

Have you ever try origin bev_encoder of bevdepth, how about it's performance?

Hi, thank you for sharing your work.
However, when I use
python tools/create_data.py nuscenes --root-path ./data/nuscenes --out-dir ./data --version v1.0 --canbus ./data
to generate the info, some thing goes wrong like:
ImportError: /home/guixingtai/anaconda3/envs/occformer/lib/python3.7/site-packages/mmdet3d-0.17.1-py3.7-linux-x86_64.egg/mmdet3d/ops/furthest_point_sample/furthest_point_sample_ext.cpython-37m-x86_64-linux-gnu.so: undefined symbol: _Z39furthest_point_sampling_kernel_launcheriiiPKfPfPiP11CUstream_st

can you help me?
thanks

Hi, Thank you for your sharing the great code.
When I run the script bash tools/dist_train.sh projects/configs/occformer_nusc/occformer_nusc_panoptic_r50_256x704_my.py 2,
I met the error . How can I generate the *_panoptic.npz.

Congratulations on the amazing work.

I am curious about the efficiency of the method. Could you shed some light on the inference time and the memory requirement?

Hello,

I would like to seek clarification regarding the training data used for the reported results on the SemanticKITTI test. Specifically, I would like to know whether the results were obtained by training solely on the "train" subset or by combining both the "train" and "val" subsets.

Thanks for your assistance in providing this information.

Congratulations on creating such an excellent and solid work!

However, I'm wondering about the results achieved without the query-based Transformer decoder, or in other words, the isolated impact of the Transformer Occupancy Decoder.
Given that the Dual-path Transformer Encoder guides the Voxel Features with the BEV feature, it seems that the voxel features should already possess sufficient fine-grained features for SSC.
Additionally, the absence of instance-level annotations could possibly reduce the impact of the Transformer Decoder and one-to-one matching.

I would appreciate any insights you may have on this matter.

Thanks for your great work, I'm a little confused as to why the truck's iou for the validation set is an astonishing 25.53, but the test set is only 1.6.

Hi,
Thank you for sharing the great work.
I want to generate the nuscenes_infos_temporal_trainval.pkl in the code.
Can you help me?

Hi,
When I run the script python projects/mmdet3d_plugin/visualize/visualize_nusc_video.py $YOUR_SAVE_PATH $YOUR_VISUALIZE_SAVE_PATH,I met the error below.

Traceback (most recent call last):
  File "projects/mmdet3d_plugin/visualize/visualize_nusc_video.py", line 8, in <module>
    from visualize_nusc_release import draw_nusc_occupancy
ModuleNotFoundError: No module named 'visualize_nusc_release'

I cannot find and import the visualize_nusc_release module.

When I try to execute the code after installing PyQT5 using pip install PyQT5 the following error occurs.

QObject::moveToThread: Current thread (0xd4bcc0) is not the object's thread (0x1416720).
Cannot move to target thread (0xd4bcc0)

qt.qpa.plugin: Could not load the Qt platform plugin "xcb" in "/home/limlab/anaconda3/envs/occformer/lib/python3.7/site-packages/cv2/qt/plugins" even though it was found.
This application failed to start because no Qt platform plugin could be initialized. Reinstalling the application may fix this problem.

Available platform plugins are: xcb, eglfs, linuxfb, minimal, minimalegl, offscreen, vnc, wayland-egl, wayland, wayland-xcomposite-egl, wayland-xcomposite-glx, webgl.


Aborted (core dumped)

please help me

Hi,
When I ran the scrript python projects/mmdet3d_plugin/tools/validate_lidarseg_submission.py --result-path $YOUR_SAVE_PATH --dataroot data/nuscenes --zip-out ., I met the error below.

  File "/rockywin.wang/occ_net/OccFormer/projects/mmdet3d_plugin/tools/validate_lidarseg_submission_my.py", line 158, in <module>
    zip_out=zip_out_)
  File "/rockywin.wang/occ_net/OccFormer/projects/mmdet3d_plugin/tools/validate_lidarseg_submission_my.py", line 35, in validate_submission
    mapper = LidarsegClassMapper(nusc)
  File "/opt/conda/lib/python3.7/site-packages/nuscenes/eval/lidarseg/utils.py", line 140, in __init__
    self.fine_idx_2_coarse_idx_mapping = self.get_fine_idx_2_coarse_idx()
  File "/opt/conda/lib/python3.7/site-packages/nuscenes/eval/lidarseg/utils.py", line 241, in get_fine_idx_2_coarse_idx
    for fine_name, fine_idx in self.nusc.lidarseg_name2idx_mapping.items():
AttributeError: 'NuScenes' object has no attribute 'lidarseg_name2idx_mapping'

The below is my data structure.

Hi,
Thank you for sharing the great work!
I want to visualize the occupancy label like the demo.
But I don't know how to do it.
Can you help me?

What is the data_velodyne under the SemanticKITTI folder? How can I get this?

Hi,
Thank you for sharing the great work!
When I run the scipt bash tools/dist_test.sh projects/configs/occformer_nusc/occformer_nusc_r50_256x704.py /rockywin.wang/occ_net/OccFormer/occformer_nusc_r50.pth 4 --pred-save /rockywin.wang/occ_net/OccFormer/01_pred_dir
I met the error below.
The version of MMCV is 1.4.0.

te/attempt_3/0/error.json
Traceback (most recent call last):
  File "tools/test.py", line 19, in <module>
    from projects.mmdet3d_plugin.datasets.builder import build_dataloader
  File "/rockywin.wang/occ_net/OccFormer/projects/mmdet3d_plugin/__init__.py", line 1, in <module>
    from .occformer import *
  File "/rockywin.wang/occ_net/OccFormer/projects/mmdet3d_plugin/occformer/__init__.py", line 5, in <module>
    from .mask2former import *
  File "/rockywin.wang/occ_net/OccFormer/projects/mmdet3d_plugin/occformer/mask2former/__init__.py", line 2, in <module>
    from .assigners import *
  File "/rockywin.wang/occ_net/OccFormer/projects/mmdet3d_plugin/occformer/mask2former/assigners/__init__.py", line 1, in <module>
    from .mask_hungarian_assigner import MaskHungarianAssigner
  File "/rockywin.wang/occ_net/OccFormer/projects/mmdet3d_plugin/occformer/mask2former/assigners/mask_hungarian_assigner.py", line 12, in <module>
    class MaskHungarianAssigner(BaseAssigner):
  File "/opt/conda/lib/python3.7/site-packages/mmcv/utils/registry.py", line 312, in _register
    module_class=cls, module_name=name, force=force)
  File "/opt/conda/lib/python3.7/site-packages/mmcv/utils/registry.py", line 246, in _register_module
    raise KeyError(f'{name} is already registered '
KeyError: 'MaskHungarianAssigner is already registered in bbox_assigner'
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 172562) of binary: /opt/conda/bin/python
ERROR:torch.distributed.elastic.agent.server.local_elastic_agent:[default] Worker group failed

When I try to run test.py with one GPU, the terminal reports Expected dtype object, got 'numpy.dtype[uint8] in Line 107 of projects/mmdet3d_plugin/datasets/pipelines/loading_nusc_occ.py. But i have checked Line122-123, nb.jit('u1[:,:,:](u1[:,:,:],i8[:,:])', nopython=True, cache=True, parallel=False) and the datatype matches the processed_label and label_voxel_pair. Can you help me solve this issue? Thx!

i wanna to visualize one photo with mask ,but i don't know how to generate the fov_mask.(the photo is come from the Semantic kitti)
where provide the method among the source code of Occformer?
Please,I have a terrible time on this problem

I need to generate the kind of picture with vision shadow

Hi there, I was wondering whether the Mask2FormerOccHead can be adapted to use a simple per-voxel loss such as CE (or Geo-Scal loss from MonoScene). I find that using mask and cls paradigm in Mask2Former is kinda difficult to apply known loss function in voxel space. Can you think of a way to adapt this in your code? Thank you

Hi there, it's a great work.
I'd like to know if there is any impact, such as slow training or inference speed, etc, for only using the "CPU version of multi-scale deformable attention".