Evaluation results of the pre-trained model
Opened this issue · 1 comments
Sharpiless commented
When I run:
python evaluate.py --model raft-RFKtest.pth --dataset kitti
I get the results:
100%|█████████████████████████████████████████████████████████████████████████████████| 200/200 [01:00<00:00, 3.29it/s]
Validation KITTI: 2.479175, 8.867946
Shouldn't it be 2.31 8.65?
Env:
NVIDIA GeForce RTX 3090, torch 1.9.0+cu111
Timer-x commented
The results may be related to the environment, We conducted all experiments on 2080ti.
Here , we evaluate our pretrained model on NVIDIA GeForce RTX 3090:
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:25<00:00, 7.84it/s]
Validation KITTI: 2.317163, 8.810199
pip list:
Package Version Editable project location
------------------------ ------------ ---------------------------------------------
absl-py 1.3.0
addict 2.4.0
argon2-cffi 21.3.0
argon2-cffi-bindings 21.2.0
asttokens 2.0.5
attrs 21.4.0
backcall 0.2.0
black 22.1.0
bleach 4.1.0
cachetools 5.0.0
certifi 2021.10.8
cffi 1.15.0
charset-normalizer 2.1.1
click 8.0.4
cycler 0.11.0
debugpy 1.5.1
decorator 5.1.1
defusedxml 0.7.1
descartes 1.1.0
efficientnet-pytorch 0.7.1
entrypoints 0.4
executing 0.8.2
filelock 3.8.0
fire 0.4.0
flake8 5.0.4
fonttools 4.29.1
GeometricKernelAttention 1.0
google-auth 2.14.1
google-auth-oauthlib 0.4.6
grpcio 1.50.0
huggingface-hub 0.10.1
idna 3.4
imageio 2.22.4
importlib-metadata 5.0.0
importlib-resources 5.4.0
ipdb 0.13.9
ipykernel 6.9.1
ipython 8.0.1
ipython-genutils 0.2.0
ipywidgets 7.6.5
jedi 0.18.1
Jinja2 3.0.3
joblib 1.1.0
jsonschema 4.4.0
jupyter 1.0.0
jupyter-client 7.1.2
jupyter-console 6.4.0
jupyter-core 4.9.2
jupyterlab-pygments 0.1.2
jupyterlab-widgets 1.0.2
kiwisolver 1.3.2
llvmlite 0.31.0
lyft-dataset-sdk 0.0.8
Markdown 3.4.1
MarkupSafe 2.1.1
matplotlib 3.5.1
matplotlib-inline 0.1.3
mistune 0.8.4
mypy-extensions 0.4.3
nbclient 0.5.11
nbconvert 6.4.2
nbformat 5.1.3
nest-asyncio 1.5.4
networkx 2.2
notebook 6.4.8
numba 0.48.0
numpy 1.23.4
nuscenes-devkit 1.1.9
opencv-python 4.5.5.62
packaging 21.3
pandas 1.5.1
pandocfilters 1.5.0
parso 0.8.3
pathspec 0.9.0
pexpect 4.8.0
pickleshare 0.7.5
Pillow 9.0.1
pip 22.2.2
platformdirs 2.5.1
plotly 5.11.0
plyfile 0.7.4
prettytable 3.5.0
prometheus-client 0.13.1
prompt-toolkit 3.0.28
protobuf 3.19.4
ptyprocess 0.7.0
pure-eval 0.2.2
pyasn1-modules 0.3.0rc1
pycocotools 2.0.4
pycparser 2.21
Pygments 2.11.2
pyparsing 3.0.7
pyquaternion 0.9.9
pyrsistent 0.18.1
pytest 7.2.0
python-dateutil 2.8.2
pytz 2022.6
PyWavelets 1.4.1
PyYAML 6.0
pyzmq 22.3.0
qtconsole 5.2.2
QtPy 2.0.1
requests 2.28.1
requests-oauthlib 1.3.1
rsa 4.9
scikit-image 0.19.3
scikit-learn 1.0.2
scipy 1.8.0
Send2Trash 1.8.0
setuptools 65.5.0
Shapely 1.8.1.post1
six 1.16.0
stack-data 0.2.0
tenacity 8.1.0
tensorboard 2.11.0
tensorboard-data-server 0.6.1
tensorboard-plugin-wit 1.8.1
tensorboardX 2.4.1
termcolor 1.1.0
terminado 0.13.1
terminaltables 3.1.10
testpath 0.5.0
threadpoolctl 3.1.0
tifffile 2022.10.10
timm 0.6.11
toml 0.10.2
tomli 2.0.1
torch 1.9.1+cu111
torch-scatter 2.0.9
torchaudio 0.9.1
torchvision 0.10.1+cu111
tornado 6.1
tqdm 4.62.3
traitlets 5.1.1
trimesh 2.35.39
typing_extensions 4.1.1
urllib3 1.26.12
wcwidth 0.2.5
webencodings 0.5.1
Werkzeug 2.2.2
wheel 0.37.1
widgetsnbextension 3.5.2
yapf 0.32.0
zipp 3.7.0