classtree
Classtree is a hierarchical classifier for images or text.
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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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (9.8%) to scientific vocabulary
Keywords
Repository
Classtree is a hierarchical classifier for images or text.
Basic Info
- Host: GitHub
- Owner: aiml-au
- License: other
- Language: Python
- Default Branch: main
- Homepage: https://aiml.shop/products/classtree.html
- Size: 112 KB
Statistics
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
- Releases: 0
Topics
Metadata Files
README.md
Classtree
Classtree is a hierarchical classifier for images or text.
shell
pip install classtree
The fastest way to use Classtree is to call the CLI on a folder of images or text files.
shell
train_data/
|- animals/
|- mammals/
|- marsupials/
|- koala/
|- image001.jpg
|- image002.jpg
|- ...
|- ...
|- reptiles/
|- ...
|- ...
|- ...
shell
classtree train images --model animals --dir train_data/animals
or
shell
classtree train text --model animals --dir train_data/animals
And then use your model with the predict command.
```shell classtree predict --model animals new_data/image304.jpg
birds/raptors/eagle ```
Pre-trained Models
You can download a pre-trained model using the download command.
shell
classtree download --model dbpedia
Or download a pre-prepared dataset.
shell
classtree download --text dbpedia
If you want to fine-tune an existing model, you can use the --from flag during training with any downloaded model.
shell
classtree train text --model animals --from dbpedia --dir train_data/animals
Available Models
| Task | Name | Size | Dataset | Notes | |----------------------|--------------------|------|------------------------|----------------------------------------------| | Text Classification | dbpedia | M | dbpedia | |
Available Datasets
| Type | Name | Dataset | Notes | |-------|--------------------|------------------------------------------------------------------------------------|----------------------------------------------| | Image | inaturalist21-mini | iNaturalist 2021 (Mini) | Non-commercial research/educational use only | | Text | dbpedia | DBPedia | CC0: Public Domain |
Evaluation
You can test your model on a hold-out dataset using the test command.
shell
classtree test --model animals --dir=test_data/animals
Licensing
Classtree is available for non-commercial internal research use by academic institutions or not-for-profit organisations only, free of charge. Please, see the license for further details. To the extent permitted by applicable law, your use is at your own risk and our liability is limited. Interested in a commercial license? For commercial queries, please email aimlshop@adelaide.edu.au with subject line “Classtree Commercial License”.
This is an AIML Shop project.
Owner
- Name: Australian Institute for Machine Learning
- Login: aiml-au
- Kind: organization
- Location: Australia
- Repositories: 1
- Profile: https://github.com/aiml-au
Citation (CITATION.cff)
cff-version: "1.2.0"
title: "Classtree"
message: "If you use this software, please cite both the article from preferred-citation and the software itself."
authors:
- family-names: Valmadre
given-names: Jack
- name: AIML
preferred-citation:
authors:
- family-names: Valmadre
given-names: Jack
title: "Hierarchical classification at multiple operating points"
type: inproceedings
year: 2022
booktitle: "Advances in Neural Information Processing Systems"
volume: 35
start: 18034
end: 18045
publisher: "Curran Associates, Inc."
url: "https://proceedings.neurips.cc/paper_files/paper/2022/file/727855c31df8821fd18d41c23daebf10-Paper-Conference.pdf"
editors:
- name: "S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh"
GitHub Events
Total
- Watch event: 2
Last Year
- Watch event: 2
Dependencies
- actions/checkout v2 composite
- actions/download-artifact v2 composite
- actions/setup-python v2 composite
- actions/upload-artifact v2 composite
- Pillow *
- fsspec *
- gcsfs *
- matplotlib *
- numpy *
- torch *
- torchtext *
- torchvision *
- tqdm *
- Flake8-pyproject *
- bandit *
- black *
- flake8 *
- mypy *
- pre-commit *