ValueError: buffer size must be a multiple of element size

[DongmingMMM]

Prerequisite

• I have searched Issues and Discussions but cannot get the expected help.
• I have read the FAQ documentation but cannot get the expected help.
• The bug has not been fixed in the latest version (dev-1.x) or latest version (dev-1.0).

Task

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

Branch

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

Environment

sys.platform: darwin
Python: 3.9.20 (main, Oct 3 2024, 02:27:54) [Clang 14.0.6 ]
CUDA available: False
MUSA available: False
numpy_random_seed: 2147483648
GCC: Apple clang version 15.0.0 (clang-1500.3.9.4)
PyTorch: 1.11.0
PyTorch compiling details: PyTorch built with:

• GCC 4.2
• C++ Version: 201402
• clang 12.0.0
• Intel(R) oneAPI Math Kernel Library Version 2023.1-Product Build 20230303 for Intel(R) 64 architecture applications
• Intel(R) MKL-DNN v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e)
• LAPACK is enabled (usually provided by MKL)
• NNPACK is enabled
• CPU capability usage: AVX2
• Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CXX_COMPILER=/Applications/Xcode-12.0.1.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/clang++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -Wno-deprecated-declarations -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOCUPTI -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -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-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-range-loop-analysis -Wno-pass-failed -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -Wno-invalid-partial-specialization -Wno-typedef-redefinition -Wno-unknown-warning-option -Wno-unused-private-field -Wno-inconsistent-missing-override -Wno-aligned-allocation-unavailable -Wno-c++14-extensions -Wno-constexpr-not-const -Wno-missing-braces -Qunused-arguments -fcolor-diagnostics -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-unused-private-field -Wno-missing-braces -Wno-c++14-extensions -Wno-constexpr-not-const, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=0, USE_CUDNN=OFF, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=OFF, USE_NNPACK=ON, USE_OPENMP=OFF, USE_ROCM=OFF,

TorchVision: 0.12.0
OpenCV: 4.10.0
MMEngine: 0.10.4
MMDetection: 3.2.0
MMDetection3D: 1.4.0+fe25f7a
spconv2.0: False

Reproduces the problem - code sample

pcd_demo.py

Reproduces the problem - command or script

I encountered the same errors when I try to visualize kitti demo and my own config (alongwith custom kitti format dataset) on my iMac.
I ran the command:
python demo/pcd_demo.py output_kitti.pcd configs/pointpillars/pointpillars_hv_secfpn_8xb6-160e_kitti-3d-car.py checkpoints/hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class_20220301_150306-37dc2420.pth --show --device cpu

Reproduces the problem - error message

python demo/pcd_demo.py output_kitti.pcd configs/pointpillars/pointpillars_hv_secfpn_8xb6-160e_kitti-3d-car.py checkpoints/hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class_20220301_150306-37dc2420.pth --show --device cpu
12/09 21:47:51 - mmengine - WARNING - Display device not found. --show is forced to False
/Users/dongming/Documents/mmdetection3d/mmdet3d/models/dense_heads/anchor3d_head.py:94: UserWarning: dir_offset and dir_limit_offset will be depressed and be incorporated into box coder in the future
warnings.warn(
Loads checkpoint by local backend from path: checkpoints/hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class_20220301_150306-37dc2420.pth
The model and loaded state dict do not match exactly

size mismatch for bbox_head.conv_cls.weight: copying a param with shape torch.Size([18, 384, 1, 1]) from checkpoint, the shape in current model is torch.Size([2, 384, 1, 1]).
size mismatch for bbox_head.conv_cls.bias: copying a param with shape torch.Size([18]) from checkpoint, the shape in current model is torch.Size([2]).
size mismatch for bbox_head.conv_reg.weight: copying a param with shape torch.Size([42, 384, 1, 1]) from checkpoint, the shape in current model is torch.Size([14, 384, 1, 1]).
size mismatch for bbox_head.conv_reg.bias: copying a param with shape torch.Size([42]) from checkpoint, the shape in current model is torch.Size([14]).
size mismatch for bbox_head.conv_dir_cls.weight: copying a param with shape torch.Size([12, 384, 1, 1]) from checkpoint, the shape in current model is torch.Size([4, 384, 1, 1]).
size mismatch for bbox_head.conv_dir_cls.bias: copying a param with shape torch.Size([12]) from checkpoint, the shape in current model is torch.Size([4]).
12/09 21:47:51 - mmengine - WARNING - Failed to search registry with scope "mmdet3d" in the "function" registry tree. As a workaround, the current "function" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "mmdet3d" is a correct scope, or whether the registry is initialized.
/opt/anaconda3/envs/openmmlab/lib/python3.9/site-packages/mmengine/visualization/visualizer.py:196: UserWarning: Failed to add <class 'mmengine.visualization.vis_backend.LocalVisBackend'>, please provide the save_dir argument.
warnings.warn(f'Failed to add {vis_backend.class}, '
Inference ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Traceback (most recent call last):
File "/Users/dongming/Documents/mmdetection3d/demo/pcd_demo.py", line 93, in
main()
File "/Users/dongming/Documents/mmdetection3d/demo/pcd_demo.py", line 83, in main
inferencer(**call_args)
File "/Users/dongming/Documents/mmdetection3d/mmdet3d/apis/inferencers/base_3d_inferencer.py", line 210, in call
for data in (track(inputs, description='Inference')
File "/opt/anaconda3/envs/openmmlab/lib/python3.9/site-packages/rich/progress.py", line 168, in track
yield from progress.track(
File "/opt/anaconda3/envs/openmmlab/lib/python3.9/site-packages/rich/progress.py", line 1210, in track
for value in sequence:
File "/opt/anaconda3/envs/openmmlab/lib/python3.9/site-packages/mmengine/infer/infer.py", line 291, in preprocess
yield from map(self.collate_fn, chunked_data)
File "/opt/anaconda3/envs/openmmlab/lib/python3.9/site-packages/mmengine/infer/infer.py", line 588, in _get_chunk_data
processed_data = next(inputs_iter)
File "/opt/anaconda3/envs/openmmlab/lib/python3.9/site-packages/mmengine/dataset/base_dataset.py", line 60, in call
data = t(data)
File "/opt/anaconda3/envs/openmmlab/lib/python3.9/site-packages/mmcv/transforms/base.py", line 12, in call
return self.transform(results)
File "/Users/dongming/Documents/mmdetection3d/mmdet3d/datasets/transforms/loading.py", line 1145, in transform
return self.from_file(inputs)
File "/opt/anaconda3/envs/openmmlab/lib/python3.9/site-packages/mmcv/transforms/base.py", line 12, in call
return self.transform(results)
File "/Users/dongming/Documents/mmdetection3d/mmdet3d/datasets/transforms/loading.py", line 646, in transform
points = self._load_points(pts_file_path)
File "/Users/dongming/Documents/mmdetection3d/mmdet3d/datasets/transforms/loading.py", line 623, in _load_points
points = np.frombuffer(pts_bytes, dtype=np.float32)
ValueError: buffer size must be a multiple of element size

Additional information

I followed the instructions on https://mmdetection3d.readthedocs.io/en/latest/user_guides/inference.html.

The code said the the it should be a 'PCD_FILE' but the example below was a .bin file. I tried both formats. The .bin one would crash so I wrote code to convert .bin to .pcd:

import numpy as np
import open3d as o3d

file_path = 'data/TJ4DRadSet_4DRadar/training/velodyne_reduced/000004.bin'
points = np.fromfile(file_path, dtype=np.float32).reshape(-1, 8) # original ptc has 8 dims

pcd = o3d.geometry.PointCloud()

pcd.points = o3d.utility.Vector3dVector(points[:, :3])

output_pcd_path = 'output_full_dimensions.pcd'
with open(output_pcd_path, 'w') as f:

f.write(f"# .PCD v0.7 - Point Cloud Data file format\n")
f.write(f"VERSION 0.7\n")
f.write(f"FIELDS x y z {''.join([f'f{i} ' for i in range(3, points.shape[1])]).strip()}\n")
f.write(f"SIZE 4 4 4 {' '.join(['4'] * (points.shape[1] - 3))}\n")
f.write(f"TYPE F F F {' '.join(['F'] * (points.shape[1] - 3))}\n")
f.write(f"COUNT 1 1 1 {' '.join(['1'] * (points.shape[1] - 3))}\n")
f.write(f"WIDTH {points.shape[0]}\n")
f.write(f"HEIGHT 1\n")
f.write(f"VIEWPOINT 0 0 0 1 0 0 0\n")
f.write(f"POINTS {points.shape[0]}\n")
f.write(f"DATA ascii\n")

for point in points:
    f.write(" ".join(map(str, point)) + "\n")

Then I encountered the error stated above, whether using either kitti demo or my own config file.

[DongmingMMM]

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