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# Contributing to Awesome Computational Primatology
Thank you for your interest in contributing! This document explains how to add papers and improve the project.
## 🚀 Quick Start
### Preview Your Changes Locally
```bash
# 1. Fork and clone the repository
git clone https://github.com/YOUR-USERNAME/awesome-computational-primatology.git
cd awesome-computational-primatology
# 2. Make your changes to README.md
# 3. Preview the website (auto-generates index.html and opens browser)
python scripts/dev-preview.py
# 4. Commit BOTH README.md and index.html, then create a pull request
```
**Important:** Always commit `index.html` along with your `README.md` changes. The CI will fail if they're out of sync.
### Automatic PR Previews
When you submit a PR, our automation will:
- ✅ Generate a preview website with your changes
- ✅ Post a comment with the preview link
- ✅ Validate table formatting and links
- ✅ Check that `index.html` is in sync with `README.md`
### 1. Branch Protocol
- Fork the repository
- Create a branch with format: `add-paper/YYYY-AuthorName` (e.g., `add-paper/2024-Smith`)
- For multiple papers or other changes: `update/brief-description`
- Add your paper in the correct section following the format below
- Verify all links are working
### 2. Pull Request Process
1. Create a draft PR first
2. Use title format: "Add: YYYY AuthorName paper" or "Update: brief description"
3. Fill out the PR template
4. Mark as ready for review when complete
### 3. Review Process
- Maintainers will review within 1-2 weeks
- Automated checks will verify table formatting and links
- Reviews focus on:
- Correct formatting
- Working links
- Appropriate categorization
- Complete information
### Eligibility Criteria
- Papers must be at the intersection of deep learning and non-human primatology
- Published from 2012 onwards (around AlexNet era)
- Must provide novel approaches or applications in computational primatology
- Cross-species datasets including primates are acceptable
### Table Format
Add your paper to the appropriate table section using this format:
| Year | Paper | Topic | Animal | Model? | Data? | Image/Video Count |
Where:
- **Year**: Publication year
- **Paper**: `[Title](link)` or just Title if preprint
- **Topic**: Use abbreviations from Topic Legend (PD, BPE, FD, etc.)
- **Animal**: Specific primate species or "Cross-species"
- **Model?**:
- `[Yes](link)` if code + pretrained models available
- `[Code only](link)` if repository available but no pretrained models
- `[No](link)` if repository with information but no functional code
- "N/A" if neither available
- **Data?**:
- `[Yes](link)` if publicly available
- "Upon request" if available through contact
- "N/A" if not available
- **Image/Video Count**: Number or "N/A" if not applicable
### Topic Legend
Use these abbreviations for the Topic column:
- PD: Primate Detection
- BPE: Body Pose Estimation
- FD: Face Detection
- FLE: Facial Landmark Estimation
- FR: Face Recognition and/or Re-Identification
- FAC: Facial Action Coding / Units
- HD: Hand Detection
- HPE: Hand Pose Estimation
- BR: Behavior Recognition / Understanding / Modeling
- AM: Avatar / Mesh
- SI: Species Identification
- RL: Reinforcement Learning
- O: Other
## Verification Steps
Before submitting your PR:
1. Verify all links are accessible
2. Check table formatting matches existing entries
3. Ensure topic abbreviations are correct
4. Confirm model/data availability is accurately represented
5. Test any code repository links
## Questions or Issues?
- Open an issue for:
- Clarification on guidelines
- Suggesting improvements
- Reporting broken links
- Discussing paper categorization
- Expect response within 1 week
## Additional Resources
- [GitHub Fork & Pull Request Workflow](https://github.com/susam/gitpr)
- [Markdown Table Format](https://www.markdownguide.org/extended-syntax/#tables) |