Comments (17)
dendenxu
commented on August 20, 2024
Hi @GuaGod , looks like the model has already been successfully loaded since the log you highlighted should be printed after model loading.
The segmentation fault is most likely OpenGL-related so I might need your assistance on checking out your environment:
- If on Linux, could you try running
glxgearsand check whether the window is displayed correctly - Try running
evc-gui, which should open a black window for you with some controls, and check whether that works - Check OpenGl version by
glxinfo -Bto see if any error is shown and check PyOpenGL installation, which should be of version 3.1.7 as of today. If we're on 3.1.0, update usingpip install -U pyopengl
from 4k4d.
GuaGod
commented on August 20, 2024
- The window is displayed correctly after
glxgears.
- An error occured after
evc-gui
from 4k4d.
dendenxu
commented on August 20, 2024
That's strange ๐ถโ๐ซ๏ธ . Your OpenGL setup looks fine.
Could you try whether the off-screen rendering works?
evc -t test -c configs/projects/realtime4dv/rendering/4k4d_sport1.yaml,configs/specs/eval.yamlAnother thing to try is to disable the compatibiliy profile window hint by commenting these two lines here:
from 4k4d.
YongmoonPark
commented on August 20, 2024
Hello, and thank you for your excellent work.
In my situation, off-screen rendering works fine, but I encounter an error when attempting rendering with a GUI. I followed your suggestion to comment out two lines, but I am still experiencing issues running in GUI mode.
Here are the details of my environment:
OS: Ubuntu 22.04 LTS
GPU: NVIDIA GeForce RTX 3090
Driver Version: 545.23.08
CUDA Version: 11.8"
Package Version Editable project location
------------------------- ------------------ ------------------------------------------
absl-py 2.0.0
addict 2.4.0
ansi2html 1.9.1
antlr4-python3-runtime 4.9.3
anyio 4.2.0
argon2-cffi 23.1.0
argon2-cffi-bindings 21.2.0
arrow 1.3.0
asttokens 2.4.1
async-lru 2.0.4
attrs 23.2.0
autopep8 2.0.4
Babel 2.14.0
beautifulsoup4 4.12.2
black 23.12.1
bleach 6.1.0
blessed 1.20.0
blinker 1.7.0
cachetools 5.3.2
calmsize 0.1.3
certifi 2022.12.7
cffi 1.16.0
charset-normalizer 2.1.1
chumpy 0.70
clang-format 17.0.6
click 8.1.7
cloudpickle 3.0.0
cmake 3.25.0
comm 0.2.1
commentjson 0.9.0
ConfigArgParse 1.7
contourpy 1.2.0
cuda-python 12.3.0
cycler 0.12.1
dash 2.14.2
dash-core-components 2.0.0
dash-html-components 2.0.0
dash-table 5.0.0
debugpy 1.8.0
decorator 5.1.1
defusedxml 0.7.1
detectron2 0.6 /media/ym/linux-data/_src/_ref/detectron2
diff-gauss 1.0.5
docstring-parser 0.15
dotmap 1.3.30
easyvolcap 0.0.0 /media/ym/linux-data/_src/_test/EasyVolcap
einops 0.7.0
et-xmlfile 1.1.0
exceptiongroup 1.2.0
executing 2.0.1
fast-autocomplete 0.9.0
fastjsonschema 2.19.1
filelock 3.9.0
Flask 3.0.0
flatbuffers 23.5.26
fonttools 4.47.0
fqdn 1.5.1
func-timeout 4.3.5
fvcore 0.1.5.post20221221
glfw 2.6.4
google-auth 2.26.1
google-auth-oauthlib 1.2.0
gpustat 1.2.dev19+gf4cd639
grpcio 1.60.0
h5py 3.10.0
human-body-prior 2.2.2.0
hydra-core 1.3.2
idna 3.4
imageio 2.33.1
imgui-bundle 1.2.1
importlib-metadata 7.0.1
iopath 0.1.9
ipdb 0.13.13
ipykernel 6.28.0
ipython 8.20.0
ipywidgets 8.1.1
isoduration 20.11.0
itsdangerous 2.1.2
jedi 0.19.1
Jinja2 3.1.2
joblib 1.3.2
json5 0.9.14
jsonpointer 2.4
jsonschema 4.20.0
jsonschema-specifications 2023.12.1
jupyter 1.0.0
jupyter_client 8.6.0
jupyter-console 6.6.3
jupyter_core 5.7.1
jupyter-events 0.9.0
jupyter-lsp 2.2.1
jupyter_server 2.12.3
jupyter_server_terminals 0.5.1
jupyterlab 4.0.10
jupyterlab_pygments 0.3.0
jupyterlab_server 2.25.2
jupyterlab-widgets 3.0.9
kiwisolver 1.4.5
kornia 0.7.1
lark-parser 0.7.8
lazy_loader 0.3
lit 15.0.7
lpips 0.1.4
Markdown 3.5.2
markdown-it-py 3.0.0
MarkupSafe 2.1.3
matplotlib 3.8.2
matplotlib-inline 0.1.6
mdurl 0.1.2
mediapipe 0.10.9
memory-tempfile 2.2.3
mistune 3.0.2
mpmath 1.3.0
msgpack 1.0.7
munch 4.0.0
mypy-extensions 1.0.0
nbclient 0.9.0
nbconvert 7.14.0
nbformat 5.9.2
nest-asyncio 1.5.8
networkx 3.0
ninja 1.11.1.1
notebook 7.0.6
notebook_shim 0.2.3
numpy 1.24.1
nvdiffrast 0.3.1 /media/ym/linux-data/_src/_ref/nvdiffrast
nvidia-ml-py 12.535.133
oauthlib 3.2.2
omegaconf 2.3.0
open3d 0.18.0
opencv-contrib-python 4.9.0.80
opencv-python 4.9.0.80
openpyxl 3.1.2
overrides 7.4.0
packaging 23.2
pandas 2.1.4
pandocfilters 1.5.0
parso 0.8.3
pathspec 0.12.1
pdbr 0.8.8
pexpect 4.9.0
Pillow 9.5.0
pip 23.3.1
platformdirs 4.1.0
plotly 5.18.0
plyfile 1.0.3
portalocker 2.8.2
prometheus-client 0.19.0
prompt-toolkit 3.0.43
protobuf 3.20.3
psutil 5.9.7
ptyprocess 0.7.0
pure-eval 0.2.2
pyasn1 0.5.1
pyasn1-modules 0.3.0
pycocotools 2.0.7
pycodestyle 2.11.1
pycparser 2.21
pyglfw 0.2.2
PyGLM 2.7.1
Pygments 2.17.2
PyMCubes 0.1.4
pymeshlab 2023.12
pyntcloud 0.3.1
PyOpenGL 3.1.7
pyparsing 3.1.1
pyperclip 1.8.2
pyquaternion 0.9.9
python-dateutil 2.8.2
python-json-logger 2.0.7
pytorch-memlab 0.3.0
pytorch-msssim 1.0.0
pytorch3d 0.7.5 /media/ym/linux-data/_src/_ref/pytorch3d
PyTurboJPEG 1.7.3
pytz 2023.3.post1
PyYAML 6.0.1
pyzmq 25.1.2
qtconsole 5.5.1
QtPy 2.4.1
referencing 0.32.1
requests 2.31.0
requests-oauthlib 1.3.1
retrying 1.3.4
rfc3339-validator 0.1.4
rfc3986-validator 0.1.1
rich 13.7.0
rpds-py 0.16.2
rsa 4.9
ruamel.yaml 0.18.5
ruamel.yaml.clib 0.2.8
scikit-image 0.22.0
scikit-learn 1.3.2
scipy 1.11.4
Send2Trash 1.8.2
setuptools 68.2.2
shtab 1.6.5
simple-knn 0.0.0
six 1.16.0
smplx 0.1.28
sniffio 1.3.0
sounddevice 0.4.6
soupsieve 2.5
stack-data 0.6.3
sympy 1.12
tabulate 0.9.0
tenacity 8.2.3
tensorboard 2.15.1
tensorboard-data-server 0.7.2
tensorboardX 2.6.2.2
termcolor 2.4.0
terminado 0.18.0
threadpoolctl 3.2.0
tifffile 2023.12.9
timg 1.1.6
tinycss2 1.2.1
tinycudann 1.6
tomli 2.0.1
torch 2.0.1+cu118
torch-scatter 2.1.2
torch-tb-profiler 0.4.3
torchaudio 2.0.2+cu118
torchdiffeq 0.2.3
torchmcubes 0.1.0
torchvision 0.15.2+cu118
tornado 6.4
tqdm 4.66.1
traitlets 5.14.1
trimesh 4.0.8
triton 2.0.0
types-python-dateutil 2.8.19.20240106
typing_extensions 4.4.0
tyro 0.6.3
tzdata 2023.4
ujson 5.9.0
uri-template 1.3.0
urllib3 1.26.13
wcwidth 0.2.13
webcolors 1.13
webencodings 0.5.1
websocket-client 1.7.0
Werkzeug 3.0.1
wheel 0.41.2
widgetsnbextension 4.0.9
xatlas 0.0.8
yacs 0.1.8
yapf 0.40.2
zipp 3.17.0
from 4k4d.
dendenxu
commented on August 20, 2024
Hi @YongmoonPark thanks for trying out our code! Does the command also throw a segmentation fault in your case?
from 4k4d.
dendenxu
commented on August 20, 2024
Hey guys @GuaGod @YongmoonPark , could you try replacing the evc command with python -q -X faulthandler easyvolcap/scripts/main.py to let the program print more useful information for the segmentation fault?
For example, try running python -q -X faulthandler easyvolcap/scripts/main.py -t gui -c configs/specs/gui.yaml.
from 4k4d.
YongmoonPark
commented on August 20, 2024
Thank you, @dendenxu, for your prompt and kind response.
In my case, off-screen rendering works fine, but when I attempt rendering with a GUI, I encounter the same error. I tried following your instructions to comment out two lines, but I'm still facing an error when running in GUI mode. Here is the error message I received:
When executing the command:
python -q -X faulthandler easyvolcap/scripts/main.py -t gui -c configs/specs/gui.yaml
I encountered the following error:
2024-01-15 09:32:27.317839 __main__ -> preflight: Starting experiment: base, command: gui main.py:80
2024-01-15 09:32:27.318702 easyvolcap.utils.console_utils -> inner: Runtime exception: 'batch_size' console_utils.py:341
AttributeError: 'batch_size'
*** 'batch_size'
> /media/ym/linux-data/_src/_test/EasyVolcap/easyvolcap/utils/base_utils.py(101)__getitem__()
whole error message
(easyvolcap) ym@ym-linux:.../_test/EasyVolcap$ python -q -X faulthandler easyvolcap/scripts/main.py -t gui -c configs/specs/gui.yaml.
2024-01-15 09:32:27.317839 __main__ -> preflight: Starting experiment: base, command: gui main.py:80
2024-01-15 09:32:27.318702 easyvolcap.utils.console_utils -> inner: Runtime exception: 'batch_size' console_utils.py:341
โญโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ Traceback (most recent call last) โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฎ
โ /media/ym/linux-data/_src/_test/EasyVolcap/easyvolcap/utils/base_utils.py:99 in __getitem__ โ
โ โ
โ โฑ 99 โ โ โ return dict.__getitem__(self, key) โ
โฐโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฏ
KeyError: 'batch_size'
During handling of the above exception, another exception occurred:
โญโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ Traceback (most recent call last) โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฎ
โ /media/ym/linux-data/_src/_test/EasyVolcap/easyvolcap/utils/console_utils.py:338 in inner โ
โ โ
โ โฑ 338 โ โ โ return func(*args, **kwargs) โ
โ โ
โ /media/ym/linux-data/_src/_test/EasyVolcap/easyvolcap/engine/registry.py:56 in inner โ
โ โ
โ โฑ 56 โ โ return call_from_cfg(func, cfg) โ
โ โ
โ /media/ym/linux-data/_src/_test/EasyVolcap/easyvolcap/engine/registry.py:47 in call_from_cfg โ
โ โ
โ โฑ 47 โ return func(**call_args) โ
โ โ
โ /media/ym/linux-data/_src/_test/EasyVolcap/easyvolcap/scripts/main.py:158 in test โ
โ โ
โ โฑ 158 โ val_dataloader: "VolumetricVideoDataloader" = DATALOADERS.build(val_dataloader_cfg) # reuse the validataion โ
โ โ
โ /media/ym/linux-data/_src/_test/EasyVolcap/easyvolcap/engine/registry.py:300 in build โ
โ โ
โ โฑ 300 โ โ return self.build_func(*args, **kwargs, registry=self) โ
โ โ
โ /media/ym/linux-data/_src/_test/EasyVolcap/easyvolcap/engine/registry.py:131 in build_from_cfg โ
โ โ
โ โฑ 131 โ return call_from_cfg(obj_cls, args) โ
โ โ
โ /media/ym/linux-data/_src/_test/EasyVolcap/easyvolcap/engine/registry.py:47 in call_from_cfg โ
โ โ
โ โฑ 47 โ return func(**call_args) โ
โ โ
โ /media/ym/linux-data/_src/_test/EasyVolcap/easyvolcap/dataloaders/volumetric_video_dataloader.py:93 in __init__ โ
โ โ
โ โฑ 93 โ โ if batch_sampler_cfg.batch_size == -1: batch_sampler_cfg.batch_size = len(dataset) โ
โ โ
โ /media/ym/linux-data/_src/_test/EasyVolcap/easyvolcap/utils/base_utils.py:101 in __getitem__ โ
โ โ
โ โฑ 101 โ โ โ raise AttributeError(e) โ
โฐโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฏ
AttributeError: 'batch_size'
*** 'batch_size'
> /media/ym/linux-data/_src/_test/EasyVolcap/easyvolcap/utils/base_utils.py(101)__getitem__()
99 return dict.__getitem__(self, key)
100 except KeyError as e:
--> 101 raise AttributeError(e)
102 # MARK: Might encounter exception in newer version of pytorch
103 # Traceback (most recent call last):
(Pdbr)
[1]+ Stopped python -q -X faulthandler easyvolcap/scripts/main.py -t gui -c configs/specs/gui.yaml.
The process stopped with the error: AttributeError: 'batch_size'.
Any guidance you could provide would be greatly appreciated.
from 4k4d.
dendenxu
commented on August 20, 2024
Thanks for the feedback @YongmoonPark ! I could not reproduce the batch_size error on my end. That error usually means we are in the wrong directory or could not find the config file the user specified (yes I need to make the errors more human readable immediately :] ). Are you on the latest commit?
from 4k4d.
YongmoonPark
commented on August 20, 2024
Thank you for your prompt response, @dendenxu . I am indeed using the latest commit. I'll take your advice and recheck everything, including reinstalling my environment, to ensure
from 4k4d.
dendenxu
commented on August 20, 2024
@YongmoonPark Ah, no need for reintalling the environment. But you could try reinstalling 4K4D itself by executing pip install -e . inside the directory.
from 4k4d.
dendenxu
commented on August 20, 2024
Could you check whether this file configs/specs/gui.yaml exists in your working directory?
The first line of log should be like this, where the experiment name is changed to gui instead of base:
2024-01-15 09:36:28.746102 __main__ -> preflight: Starting experiment: gui, command: guifrom 4k4d.
YongmoonPark
commented on August 20, 2024
I have verified the location of configs/specs/gui.yaml. However, I still encounter the following error when executing:
2024-01-15 11:42:30.025936 __main__ -> preflight: Starting experiment: base, command: gui main.py:80
2024-01-15 11:42:30.026796 easyvolcap.utils.console_utils -> inner: Runtime exception: 'batch_size'
It seems that the issue might be occurring because the configs/specs/gui.yaml file is not being read and executed properly.
Thank you. Your advice has been helpful in narrowing down the cause of the problem.
from 4k4d.
dendenxu
commented on August 20, 2024
Glad to know that we're making progress. The next reasonable step seems to be putting a breakpoint here and examine the content of args.config and os.getcwd(). To add a breakpoint, simply add the line breakpoint()
from 4k4d.
Related Issues (16)
- Nice Work! HOT 1
- Are there any plans to release missing files? HOT 2
- CUDA out of memory HOT 2
- About real-time rendering HOT 1
- Is there any plan to add the training code? HOT 2
- Error in opengl HOT 3
- How to convert CamPose.inf to extri.yml? HOT 1
- Test view HOT 3
- ๅคๅพทๅคๅพท
- About the release time of the code HOT 4
- How long does it take to train a model HOT 7
- Can it render poses that have never appeared before? HOT 2
- Licensing HOT 4
- easyvolcap.utils.console_utils -> inner: Runtime exception: 'SuperChargedR4DV is not in the samplers registry' HOT 8
- Bad results than expected. HOT 10
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. ๐๐๐
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google โค๏ธ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from 4k4d.