Closed lmh0501 closed 1 year ago
感谢提问!我没有遇到这个问题,你可以检查一下numpy和numba的版本是否正确,我们使用的是numpy 1.20.0, numba 0.48.0
是一样的。我现在是用nuscenes中的mini数据集,会跟这个有关系嘛?
你可以尝试一下把numpy版本降低到1.19.5
好像不大行,我试了numpy和numba的不同版本,不同情况的报错,只有你给的这个版本能运行到上面这一步然后也是会报错
好像不大行,我试了numpy和numba的不同版本,不同情况的报错,只有你给的这个版本能运行到上面这一步,然后也是会报错
我用的单张3090显卡,定位到报错的那行,然后把最后的dtype=np.bool改成dtype=np.int64,代码就能跑起来了,但是构建GT Database这步运行得特别慢,我看了一下大概需要七个小时,这还是mini数据集,是不是不大对啊?
我们在完整数据集上确实是需要六七个小时,但是mini数据集我不太确定,你们可以确认一下是不是确实只构建了mini数据集,还是其实是在构建完整数据集。
同样的问题。
Create GT Database of NuScenesDataset
[ ] 0/28130, elapsed: 0s, ETA:Traceback (most recent call last):
File "tools/create_data.py", line 225, in <module>
max_sweeps=args.max_sweeps)
File "tools/create_data.py", line 67, in nuscenes_data_prep
f'{out_dir}/{info_prefix}_infos_train.pkl')
File "/home/palmdong/mmfusion/SparseFusion/tools/data_converter/create_gt_database.py", line 254, in create_groundtruth_database
point_indices = box_np_ops.points_in_rbbox(points, gt_boxes_3d)
File "/home/palmdong/mmfusion/SparseFusion/mmdet3d/core/bbox/box_np_ops.py", line 433, in points_in_rbbox
indices = points_in_convex_polygon_3d_jit(points[:, :3], surfaces)
File "/home/palmdong/mmfusion/SparseFusion/mmdet3d/core/bbox/box_np_ops.py", line 763, in points_in_convex_polygon_3d_jit
normal_vec, d, num_surfaces)
TypeError: expected dtype object, got 'numpy.dtype[bool_]'
我的版本:
(sparsefusion) palmdong@473370ef5807:~/mmfusion/SparseFusion$ pip list
Package Version Editable project location
----------------------------- ----------- ------------------------------------
absl-py 2.1.0
addict 2.4.0
anyio 3.7.1
argon2-cffi 23.1.0
argon2-cffi-bindings 21.2.0
attrs 23.2.0
backcall 0.2.0
beautifulsoup4 4.12.3
black 23.3.0
bleach 6.0.0
cachetools 5.3.3
ccimport 0.4.2
certifi 2022.12.7
cffi 1.15.1
charset-normalizer 3.3.2
click 8.1.7
comm 0.1.4
cumm-cu117 0.4.11
cycler 0.11.0
Cython 0.29.33
debugpy 1.7.0
decorator 5.1.1
defusedxml 0.7.1
descartes 1.1.0
entrypoints 0.4
exceptiongroup 1.2.1
fastjsonschema 2.19.1
fire 0.6.0
flake8 3.9.2
fonttools 4.38.0
google-auth 2.29.0
google-auth-oauthlib 0.4.6
grpcio 1.62.2
idna 3.7
imageio 2.31.2
importlib-metadata 6.7.0
importlib-resources 5.12.0
iniconfig 2.0.0
ipykernel 6.16.2
ipython 7.34.0
ipython-genutils 0.2.0
ipywidgets 8.1.3
jedi 0.19.1
Jinja2 3.1.4
joblib 1.3.2
jsonschema 4.17.3
jupyter 1.0.0
jupyter_client 7.4.9
jupyter-console 6.6.3
jupyter_core 4.12.0
jupyter-server 1.24.0
jupyterlab-pygments 0.2.2
jupyterlab_widgets 3.0.11
kiwisolver 1.4.5
lark 1.1.9
llvmlite 0.31.0
lyft-dataset-sdk 0.0.8
Markdown 3.4.4
MarkupSafe 2.1.5
matplotlib 3.5.2
matplotlib-inline 0.1.6
mccabe 0.6.1
mistune 3.0.2
mmcv-full 1.2.7
mmdet 2.10.0
mmdet3d 0.11.0 /home/palmdong/mmfusion/SparseFusion
mmpycocotools 12.0.3
MultiScaleDeformableAttention 1.0
mypy-extensions 1.0.0
nbclassic 1.1.0
nbclient 0.7.4
nbconvert 7.6.0
nbformat 5.8.0
nest-asyncio 1.6.0
networkx 2.2
ninja 1.11.1.1
notebook 6.5.7
notebook_shim 0.2.4
numba 0.48.0
numpy 1.20.0
nuscenes-devkit 1.1.10
oauthlib 3.2.2
opencv-python-headless 4.9.0.80
packaging 24.0
pandas 1.3.5
pandocfilters 1.5.1
parso 0.8.4
pathspec 0.11.2
pccm 0.4.11
pexpect 4.9.0
pickleshare 0.7.5
Pillow 9.5.0
pip 22.3.1
pkgutil_resolve_name 1.3.10
platformdirs 4.0.0
plotly 5.18.0
pluggy 1.2.0
plyfile 0.9
portalocker 2.7.0
prometheus-client 0.17.1
prompt_toolkit 3.0.45
protobuf 3.20.3
psutil 5.9.8
ptyprocess 0.7.0
pyasn1 0.5.1
pyasn1-modules 0.3.0
pybind11 2.12.0
pycocotools 2.0.7
pycodestyle 2.7.0
pycparser 2.21
pyflakes 2.3.1
Pygments 2.17.2
pyparsing 3.1.2
pyquaternion 0.9.9
pyrsistent 0.19.3
pytest 7.4.4
python-dateutil 2.9.0.post0
pytz 2024.1
PyWavelets 1.3.0
PyYAML 6.0.1
pyzmq 26.0.3
qtconsole 5.4.4
QtPy 2.4.1
requests 2.31.0
requests-oauthlib 2.0.0
rsa 4.9
scikit-image 0.19.3
scikit-learn 1.0.2
scipy 1.7.3
Send2Trash 1.8.3
setuptools 65.6.3
Shapely 1.8.5
six 1.16.0
sniffio 1.3.1
soupsieve 2.4.1
spconv-cu117 2.3.3
tenacity 8.2.3
tensorboard 2.11.2
tensorboard-data-server 0.6.1
tensorboard-plugin-wit 1.8.1
termcolor 2.3.0
terminado 0.17.1
terminaltables 3.1.10
threadpoolctl 3.1.0
tifffile 2021.11.2
tinycss2 1.2.1
tomli 2.0.1
torch 1.7.1+cu110
torchaudio 0.7.2
torchvision 0.8.2+cu110
tornado 6.2
tqdm 4.66.4
traitlets 5.9.0
trimesh 2.35.39
typed-ast 1.5.5
typing_extensions 4.7.1
urllib3 2.0.7
wcwidth 0.2.13
webencodings 0.5.1
websocket-client 1.6.1
Werkzeug 2.2.3
wheel 0.38.4
widgetsnbextension 4.0.11
yapf 0.40.2
zipp 3.15.0
当尝试按mmdet3d的QA降numpy版本时报错numpy与pycocotools的版本不匹配。
Traceback (most recent call last):
File "tools/create_data.py", line 5, in
解决了,降版本+需要重新编译mmpycocotools:
pip uninstall numpy; pip install numpy==1.20.0 #需要在mmpycocotools前面装。 pip uninstall mmpycocotools pycocotools; pip install mmpycocotools==12.0.3 --no-cache-dir
想问一嘴为何用numpy==1.20.0,有什么讲究么?
你好,想问一下,运行python tools/create_data.py nuscenes --root-path ./data/nuscenes --out-dir ./data/nuscenes --extra-tag nuscenes时出现这个问题该怎么解决呢?