backbonehub
Science Score: 54.0%
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
Links to: arxiv.org -
○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 (12.7%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: bear-coder-9527
- License: apache-2.0
- Language: Python
- Default Branch: main
- Size: 5.8 MB
Statistics
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Introduction
This project is for personal learning and use, based on MMPreTrain. It aims to track and reproduce the latest backbone models since MMPreTrain hasn’t released any new models for over a year.MMPreTrain is an open source pre-training toolbox based on PyTorch. It is a part of the OpenMMLab project.
The main branch works with PyTorch 1.8+.
What's new
🌟 (2024.12.5) Support StartNet Rewrite the Stars. - More details StartNet.
🌟 Support CAS-ViT. - More details CAS-ViT.
Installation
Below are quick steps for installation:
shell
conda create -n BackboneHub python=3.8 pytorch==1.10.1 torchvision==0.11.2 cudatoolkit=11.3 -c pytorch -y
conda activate BackboneHub
pip install openmim
git clone https://github.com/bear-coder-9527/BackboneHub.git
cd BackboneHub
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]"
User Guides
The basic usage is same as MMPreTrain for new users:
For more information, please refer to our documentation.
Model zoo
Results and models are available in the model zoo.
Acknowledgement
This project is based on MMPreTrain. Thanks for their public repository and excellent contributions!
Owner
- Login: bear-coder-9527
- Kind: user
- Repositories: 1
- Profile: https://github.com/bear-coder-9527
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: 12
- Create event: 3
Last Year
- Watch event: 1
- Push event: 12
- Create event: 3
Dependencies
- 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