https://github.com/calebweinreb/video-embedding
Science Score: 36.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓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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✓Committers with academic emails
1 of 3 committers (33.3%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (9.4%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: calebweinreb
- Language: Jupyter Notebook
- Default Branch: main
- Size: 21.6 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
- Releases: 0
Metadata Files
README.md
Video clip embedding
The train.ipynb notebook contains code for training a 3D convnet using Barlow Twins. The goal is to embed short video clips of animal behavior in a semantically-meaningful latent space.
Development environment
Create a virtual environment using conda:
conda create -n video_embedding python=3.10
conda activate video_embedding
Install ipykernel to use the conda environment in Jupyter notebooks:
pip install ipykernel
python -m ipykernel install --user --name=video_embedding
When you want to use the conda environment in Jupyter notebooks, select the video_embedding kernel.
TODO:
Install necessary dependencies to run the full notebook. List all the dependencies you had to install in a file called
requirements.txtAdd comments/docstrings that explain the purpose of each function (or question marks if any you're not sure).
Create a minimal python package by adding an
__init__.pyfile and splitting the functions into separate files that cover different functionalities (e.g.io.pyfor video reading and writing,augmentation.pyfor augmentations,model.pyfor the model, etc.). The package should be importable from the notebook.Add formal docstrings to all the functions and classes. Use the Google style guide for docstrings. Refactor where necessary to make the code more readable.
Formalize the python package by adding a
setup.pyfile and versioning (Caleb will do this).Add functionality for animal tracking / cropping.
Create documentation, including installation instructions and a tutorial notebook.
Owner
- Name: Caleb Weinreb
- Login: calebweinreb
- Kind: user
- Repositories: 3
- Profile: https://github.com/calebweinreb
GitHub Events
Total
- Delete event: 2
- Issue comment event: 1
- Member event: 1
- Push event: 75
- Pull request event: 12
- Create event: 8
Last Year
- Delete event: 2
- Issue comment event: 1
- Member event: 1
- Push event: 75
- Pull request event: 12
- Create event: 8
Committers
Last synced: about 1 year ago
Top Committers
| Name | Commits | |
|---|---|---|
| Caleb Weinreb | c****w@g****m | 58 |
| MarieatouDaniels | m****s@g****m | 44 |
| Weinreb | c****4@c****u | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: about 1 year 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
Issue Authors
Pull Request Authors
- calebweinreb (5)
- MarieatouDaniels (3)