Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (10.7%) to scientific vocabulary
Repository
训练脚本
Basic Info
- Host: GitHub
- Owner: anxingle
- License: apache-2.0
- Language: Python
- Default Branch: master
- Size: 3.54 MB
Statistics
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
这是 别人家(openmmlab)的框架库 ，拿来自己训模型。特此说明！
English | 中文readME说明
Installation
Below are quick steps for installation:
shell
conda create -n open-mmlab python=3.8 pytorch==1.10.1 torchvision==0.11.2 cudatoolkit=11.3 -c pytorch -y
conda activate open-mmlab
pip install openmim
git clone https://github.com/open-mmlab/mmpretrain.git
cd mmpretrain
mim install -e .
Please refer to installation documentation for more detailed installation and dataset preparation.
For multi-modality models support, please install the extra dependencies by:
shell
mim install -e ".[multimodal]"
Acknowledgement
MMPreTrain is an open source project that is contributed by researchers and engineers from various colleges and companies. We appreciate all the contributors who implement their methods or add new features, as well as users who give valuable feedbacks. We wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and supporting their own academic research.
Citation
If you find this project useful in your research, please consider cite:
BibTeX
@misc{2023mmpretrain,
title={OpenMMLab's Pre-training Toolbox and Benchmark},
author={MMPreTrain Contributors},
howpublished = {\url{https://github.com/open-mmlab/mmpretrain}},
year={2023}
}
License
This project is released under the Apache 2.0 license.
Owner
- Name: 安兴乐-siler
- Login: anxingle
- Kind: user
- Location: 北京
- Company: Infervision
- Website: http://anxingle.github.io
- Twitter: anxingle_Christ
- Repositories: 48
- Profile: https://github.com/anxingle
Master of Computer Science, Institute of Automation of Chinese Academy of Sciences
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." title: "OpenMMLab's Pre-training Toolbox and Benchmark" authors: - name: "MMPreTrain Contributors" version: 0.15.0 date-released: 2023-04-06 repository-code: "https://github.com/open-mmlab/mmpretrain" license: Apache-2.0
GitHub Events
Total
- Watch event: 1
- Push event: 18
- Create event: 2
Last Year
- Watch event: 1
- Push event: 18
- Create event: 2
Issues and Pull Requests
Last synced: 7 months ago
Dependencies
- actions/checkout v3 composite
- actions/setup-python v4 composite
- actions/checkout v3 composite
- actions/setup-python v4 composite
- codecov/codecov-action v1.0.14 composite
- actions/checkout v3 composite
- actions/setup-python v4 composite
- actions/checkout v3 composite
- actions/setup-python v4 composite
- pytorch/pytorch ${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel build
- pytorch/pytorch ${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel build
- pytorch/torchserve latest-gpu build
- docutils ==0.18.1
- modelindex *
- myst-parser *
- pytorch_sphinx_theme *
- sphinx ==6.1.3
- sphinx-copybutton *
- sphinx-notfound-page *
- sphinx-tabs *
- sphinxcontrib-jquery *
- tabulate *
- mmcv >=2.0.0,<2.4.0
- mmengine >=0.8.3,<1.0.0
- pycocotools *
- transformers >=4.28.0
- albumentations >=0.3.2
- grad-cam >=1.3.7,<1.5.0
- requests *
- scikit-learn *
- mmcv-lite >=2.0.0rc4
- mmengine *
- pycocotools *
- torch *
- torchvision *
- transformers *
- einops *
- importlib-metadata *
- mat4py *
- matplotlib *
- modelindex *
- numpy *
- rich *
- coverage * test
- interrogate * test
- pytest * test