Open SMSajadi99 opened 1 year ago
I am working with mini data, now the problem is that it calls the error sweeps/LIDAR_TOP
twice
@SMSajadi99 We'll provide annotation files generated offline soon. You can try it first: nuscenes train split nuscenes val split nuscenes_mini train split nuscenes_mini val split
Thanks so much
@JingweiZhang12 Hi
Thank you very much for the data you sent.
But I want to start it on my system, on data mini. I will try to explain in detail so that we can fix the bug, thank you for your help.
nuscenes folder photo:
Installation libraries using Conda 23.1.0
and CUDA 11.7
:
Package | Version |
---|---|
absl-py | 1.4.0 |
addict | 2.4.0 |
anyio | 3.6.2 |
appdirs | 1.4.4 |
argon2-cffi | 21.3.0 |
argon2-cffi-bindings | 21.2.0 |
arrow | 1.2.3 |
asttokens | 2.2.1 |
attrs | 22.2.0 |
backcall | 0.2.0 |
beautifulsoup4 | 4.12.0 |
black | 23.3.0 |
bleach | 6.0.0 |
build | 0.7.0 |
cachetools | 5.3.0 |
ccimport | 0.4.2 |
certifi | 2022.12.7 |
cffi | 1.15.1 |
charset-normalizer | 3.1.0 |
click | 8.1.3 |
colorama | 0.4.6 |
comm | 0.1.3 |
ConfigArgParse | 1.5.3 |
contextlib2 | 21.6.0 |
contourpy | 1.0.7 |
cumm-cu117 | 0.4.8 |
cycler | 0.11.0 |
dash | 2.9.2 |
dash-core-components | 2.0.0 |
dash-html-components | 2.0.0 |
dash-table | 5.0.0 |
debugpy | 1.6.6 |
decorator | 5.1.1 |
defusedxml | 0.7.1 |
descartes | 1.1.0 |
docopt | 0.6.2 |
exceptiongroup | 1.1.1 |
executing | 1.2.0 |
fastjsonschema | 2.16.3 |
fire | 0.5.0 |
flake8 | 6.0.0 |
Flask | 2.2.3 |
flit_core | 3.8.0 |
fonttools | 4.39.3 |
fqdn | 1.5.1 |
google-auth | 2.17.1 |
google-auth-oauthlib | 1.0.0 |
grpcio | 1.53.0 |
h5py | 3.8.0 |
idna | 3.4 |
imageio | 2.27.0 |
importlib-metadata | 6.3.0 |
importlib-resources | 5.12.0 |
iniconfig | 2.0.0 |
inspect-it | 0.3.2 |
ipykernel | 6.22.0 |
ipython | 8.12.0 |
ipython-genutils | 0.2.0 |
ipywidgets | 8.0.6 |
isoduration | 20.11.0 |
itsdangerous | 2.1.2 |
itypes | 1.2.0 |
jedi | 0.18.2 |
Jinja2 | 3.1.2 |
joblib | 1.2.0 |
jsonpointer | 2.3 |
jsonschema | 4.17.3 |
jupyter | 1.0.0 |
jupyter_client | 8.1.0 |
jupyter-console | 6.6.3 |
jupyter_core | 5.3.0 |
jupyter-events | 0.6.3 |
jupyter_server | 2.5.0 |
jupyter_server_terminals | 0.4.4 |
jupyterlab-pygments | 0.2.2 |
jupyterlab-widgets | 3.0.7 |
kiwisolver | 1.4.4 |
lark | 1.1.5 |
lazy_loader | 0.2 |
llvmlite | 0.36.0 |
loguru | 0.6.0 |
lyft-dataset-sdk | 0.0.8 |
Markdown | 3.4.3 |
markdown-it-py | 2.2.0 |
MarkupSafe | 2.1.2 |
matplotlib | 3.5.2 |
matplotlib-inline | 0.1.6 |
mccabe | 0.7.0 |
mdurl | 0.1.2 |
mistune | 2.0.5 |
mkl-fft | 1.3.1 |
mkl-random | 1.2.2 |
mkl-service | 2.4.0 |
mmcv | 2.0.0 |
mmdet | 3.0.0 |
mmengine | 0.7.2 |
model-index | 0.1.11 |
mpi4py | 3.0.3 |
msgpack | 1.0.5 |
msgpack-numpy | 0.4.8 |
multimethod | 1.9.1 |
mypy-extensions | 1.0.0 |
nbclassic | 0.5.4 |
nbclient | 0.7.2 |
nbconvert | 7.2.10 |
nbformat | 5.7.0 |
nest-asyncio | 1.5.6 |
networkx | 3.1 |
ninja | 1.11.1 |
notebook | 6.5.3 |
notebook_shim | 0.2.2 |
numba | 0.53.0 |
numpy | 1.23.5 |
nuscenes-devkit | 1.1.10 |
oauthlib | 3.2.2 |
olefile | 0.46 |
open3d | 0.17.0 |
opencv-python | 4.7.0.72 |
openmim | 0.3.7 |
ordered-set | 4.1.0 |
packaging | 23.0 |
pandas | 2.0.0 |
pandocfilters | 1.5.0 |
parso | 0.8.3 |
pathlib | 1.0.1 |
pathspec | 0.11.1 |
pccm | 0.4.6 |
pep517 | 0.13.0 |
pickleshare | 0.7.5 |
Pillow | 9.5.0 |
pip | 23.0.1 |
pip-tools | 6.13.0 |
pkgutil_resolve_name | 1.3.10 |
platformdirs | 3.2.0 |
plotly | 5.14.1 |
pluggy | 1.0.0 |
portalocker | 2.7.0 |
prometheus-client | 0.16.0 |
prompt-toolkit | 3.0.38 |
protobuf | 4.22.1 |
psutil | 5.9.4 |
pure-eval | 0.2.2 |
pyasn1 | 0.4.8 |
pyasn1-modules | 0.2.8 |
pybind11 | 2.10.4 |
pycocotools | 2.0.6 |
pycodestyle | 2.10.0 |
pycparser | 2.21 |
pyflakes | 3.0.1 |
Pygments | 2.14.0 |
pyparsing | 3.0.9 |
pyquaternion | 0.9.9 |
pyrsistent | 0.19.3 |
pytest | 7.3.0 |
python-dateutil | 2.8.2 |
python-json-logger | 2.0.7 |
pytools | 2022.1.14 |
pytz | 2023.3 |
PyWavelets | 1.4.1 |
pywin32 | 306 |
pywinpty | 2.0.10 |
PyYAML | 6.0 |
pyzmq | 25.0.2 |
qtconsole | 5.4.2 |
QtPy | 2.3.1 |
regex | 2023.3.23 |
requests | 2.28.2 |
requests-oauthlib | 1.3.1 |
rfc3339-validator | 0.1.4 |
rfc3986-validator | 0.1.1 |
rich | 13.3.4 |
rsa | 4.9 |
scikit-image | 0.20.0 |
scikit-learn | 1.2.2 |
scipy | 1.9.1 |
Send2Trash | 1.8.0 |
setuptools | 65.6.3 |
Shapely | 1.8.5 |
six | 1.16.0 |
sniffio | 1.3.0 |
soupsieve | 2.4 |
spconv-cu117 | 2.3.6 |
stack-data | 0.6.2 |
tabulate | 0.9.0 |
tenacity | 8.2.2 |
tensorboard | 2.12.1 |
tensorboard-data-server | 0.7.0 |
tensorboard-plugin-wit | 1.8.1 |
tensorpack | 0.11 |
termcolor | 2.2.0 |
terminado | 0.17.1 |
terminaltables | 3.1.10 |
threadpoolctl | 3.1.0 |
tifffile | 2023.3.21 |
tinycss2 | 1.2.1 |
toml | 0.10.2 |
tomli | 2.0.1 |
torch | 1.10.1 |
torchaudio | 0.10.1 |
torchpack | 0.3.1 |
torchvision | 0.11.2 |
tornado | 6.2 |
tqdm | 4.65.0 |
traitlets | 5.9.0 |
trimesh | 2.35.39 |
typing | 3.7.4.3 |
typing_extensions | 4.4.0 |
tzdata | 2023.3 |
uri-template | 1.2.0 |
urllib3 | 1.26.15 |
wcwidth | 0.2.6 |
webcolors | 1.13 |
webencodings | 0.5.1 |
websocket-client | 1.5.1 |
Werkzeug | 2.2.3 |
wheel | 0.38.4 |
widgetsnbextension | 4.0.7 |
win32-setctime | 1.1.0 |
wincertstore | 0.2 |
yapf | 0.32.0 |
zipp | 3.15.0 |
Now the main folder is as follows:
Data folder:
Now I run the following code: Of course, I have to say two things
In line 252 of the python creat_data.py
file, I changed the version from v1.0
to v1.0-mini
.
I pulled out the creat_data file from the tools folder and put it in the mmdetection3d folder, because in the picture below it says that the file should be run in the tools folder, but in the file itself, it says to go to tools folder, which had this problem, in general, it ran fine with this. became.
Now the output is as follows:
Now I have to say two things:
path
it is referring to writes the phrase sweeps/LIDAR_TOP
twice, so it is clear that there is a problem.
Now, if possible, check this case, what should I do?
Fro the log, you could check the code of create_gt_databse. Maybe the path is repeated somewhere?
Hi again @JingweiZhang12
I did this, created two separate folders, and put the data in them.
The productions were done without problems, but this was the output:
Now the problem that has arisen is that there are 4 files like the files you gave, for me there are 3 of which are shared and the other 2 are different and I don't have mini data in the pkl files. I was looking at the creat_gt_database
python file and saw It produces exactly dbinfo
files, can you tell me the change that I have to make so that I can produce mini like you?
But I was looking at the python file nuscenes_converter
and we saw that it is somehow forming this mini section.
Thank you for helping me
Hi @JingweiZhang12 I typed the following code again with another method, but it didn't work like the files you sent me in the first question.
python create_data.py nuscenes --root-path ./data/nuscenes --version "v1.0-mini" --out-dir ./data/nuscenes --extra-tag nuscenes
what should i do
Hi @JingweiZhang12, can you help me ?
Hi, I have the same problem, have you solved it yet?
Hi @Lcl159 , not yet Working with Dataset Mini is very difficult
Hello, I received GitHub, I went to the folders according to your instructions, and its site is:
https://github.com/open-mmlab/mmdetection3d/blob/1.0/docs/en/datasets/nuscenes_det.md
The outputs are as follows:
But I encountered this error
can you help me