[BUG] Potential BUG in visualization of function 'draw_camera_bbox3d_on_img'

Prerequisite

[X] I have searched Issues and Discussions but cannot get the expected help.
[X] I have read the FAQ documentation but cannot get the expected help.
[X] The bug has not been fixed in the latest version (dev) or latest version (1.x).

Task

I'm using the official example scripts/configs for the officially supported tasks/models/datasets.

Branch

master branch https://github.com/open-mmlab/mmdetection3d

Environment

fatal: not a git repository (or any parent up to mount point /home) Stopping at filesystem boundary (GIT_DISCOVERY_ACROSS_FILESYSTEM not set). sys.platform: linux Python: 3.8.16 (default, Mar 2 2023, 03:21:46) [GCC 11.2.0] CUDA available: True GPU 0,1,2,3,4,5,6,7: NVIDIA GeForce RTX 3090 CUDA_HOME: /usr/local/cuda-11.1 NVCC: Cuda compilation tools, release 11.1, V11.1.74 GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0 PyTorch: 1.9.0+cu111 PyTorch compiling details: PyTorch built with:

GCC 7.3
C++ Version: 201402
Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications
Intel(R) MKL-DNN v2.1.2 (Git Hash 98be7e8afa711dc9b66c8ff3504129cb82013cdb)
OpenMP 201511 (a.k.a. OpenMP 4.5)
NNPACK is enabled
CPU capability usage: AVX2
CUDA Runtime 11.1
NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86
CuDNN 8.0.5
Magma 2.5.2
Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.9.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON,

TorchVision: 0.10.0+cu111 OpenCV: 4.7.0 MMCV: 1.5.2 MMCV Compiler: GCC 7.3 MMCV CUDA Compiler: 11.1 MMDetection: 2.28.2 MMSegmentation: 0.30.0 MMDetection3D: 1.0.0rc6+ spconv2.0: False

Reproduces the problem - code sample

pred_lidar_ins_3dbbox = LiDARInstance3DBoxes(pred_bboxes) 

pred_bboxes_in_cam = Box3DMode.convert(
    box=pred_lidar_ins_3dbbox,
    src=Box3DMode.LIDAR,
    dst=Box3DMode.CAM,
    rt_mat=cam_extrinsics.T  # cam_extrinsics.T is lidar2cam
)

drawed_img = draw_camera_bbox3d_on_img(
    pred_bboxes_in_cam, img, cam_intrinsics, img_metas={}, color=(241, 101, 72), thickness=1
)

mmcv.imwrite(drawed_img, args.out_dir + '/nuscenes_showed_img_coor.png')

# cam_extrinsics.T is lidar2cam, cam_intrinsics is cam2img
drawed_img = draw_lidar_bbox3d_on_img(
    pred_lidar_ins_3dbbox, img, np.dot(cam_intrinsics, cam_extrinsics.T), {}, color=(241, 101, 72), thickness=1
)

mmcv.imwrite(drawed_img, args.out_dir + '/nuscenes_showed_lidar_coor.png')

Reproduces the problem - command or script

python dets_inference.py

Reproduces the problem - error message

when I visualize CameraInstance3DBoxes converted by function Box3DMode.convert from LiDARInstance3DBoxes, I get a wrong visualization

but when I directly visualize LiDARInstance3DBoxes, I get a correct visualization

then in order to find the bug, I change the code1 to code2

####### code1 ######## drawed_img = draw_camera_bbox3d_on_img( pred_bboxes_in_cam, img, cam_intrinsics, img_metas={}, color=(241, 101, 72), thickness=1 ) ####################

####### code2 ######## drawed_img = draw_camera_bbox3d_on_img( pred_lidar_ins_3dbbox, img, np.dot(cam_intrinsics, cam_extrinsics.T), img_metas={}, color=(241, 101, 72), thickness=1 ) ####################

in my opinion, the transform_matrix in code2 can directly transform the points from lidar coordinate into img coordinate, which is similar with the transformation in code1, and interestingly, I get a correct visualization too

so I think the BUG is in Box3DMode.convert or draw_camera_bbox3d_on_img, but I read the source code of Box3DMode.convert, the transformation in code is correct, so I think there are something wrong in draw_camera_bbox3d_on_img.

please help me solve this bug, thanks a lot!

Additional information

No response

open-mmlab / mmdetection3d