pytorch-cinic
Small utility package providing easy-install dataloader for https://github.com/BayesWatch/cinic-10#data-loading
Science Score: 77.0%
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
Found 3 DOI reference(s) in README -
✓Academic publication links
Links to: arxiv.org -
✓Committers with academic emails
1 of 1 committers (100.0%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (5.9%) to scientific vocabulary
Repository
Small utility package providing easy-install dataloader for https://github.com/BayesWatch/cinic-10#data-loading
Basic Info
- Host: GitHub
- Owner: igor-krawczuk
- License: mit
- Language: Python
- Default Branch: main
- Size: 11.7 KB
Statistics
- Stars: 2
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
A simple package packaging a pytorch dataloader for the CINIC10 dataset.
If you use it cite the original authors
@misc{https://doi.org/10.48550/arxiv.1810.03505,
doi = {10.48550/ARXIV.1810.03505},
url = {https://arxiv.org/abs/1810.03505},
author = {Darlow, Luke N. and Crowley, Elliot J. and Antoniou, Antreas and Storkey, Amos J.},
keywords = {Computer Vision and Pattern Recognition (cs.CV), Machine Learning (cs.LG), Machine Learning (stat.ML), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {CINIC-10 is not ImageNet or CIFAR-10},
publisher = {arXiv},
year = {2018},
copyright = {Creative Commons Attribution Share Alike 4.0 International}
}
and if you want to be nice, also this repo (although the code is borderline trivial so no hard feelings if not).
To use simply import
from pytorch_cinic.dataset import CINIC10
and then use like CIFAR10 (except that we use partition=train/valid/test instead of train=True/False)
Owner
- Name: Igor Krawczuk
- Login: igor-krawczuk
- Kind: user
- Location: Switzerland
- Website: https://krawczuk.eu
- Twitter: thegermanpole
- Repositories: 5
- Profile: https://github.com/igor-krawczuk
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you want to be nice, cite this repo, but more importantly, *cite the authors* - see the README"
authors:
- family-names: Krawczuk
given-names: Igor
orcid: https://orcid.org/0000-0002-5281-8926
title: "pytorch_cinic"
version: 0.0.1
date-released: 2022-09-01
GitHub Events
Total
- Watch event: 1
Last Year
- Watch event: 1
Committers
Last synced: almost 3 years ago
All Time
- Total Commits: 10
- Total Committers: 1
- Avg Commits per committer: 10.0
- Development Distribution Score (DDS): 0.0
Top Committers
| Name | Commits | |
|---|---|---|
| Igor Krawczuk | i****k@e****h | 10 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 0
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 0
- Total pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
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Packages
- Total packages: 1
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Total downloads:
- pypi 19 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 6
- Total maintainers: 1
pypi.org: pytorch-cinic
A small wrapper around the CINIC10 dataset https://datashare.ed.ac.uk/handle/10283/3192
- Homepage: https://github.com/igor-krawczuk/pytorch-cinic
- Documentation: https://pytorch-cinic.readthedocs.io/
- License: MIT License Copyright (c) 2022 Igor Krawczuk Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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Latest release: 0.0.6
published over 3 years ago