This machine learning project aimed at assessing public service officers' friendliness in real-time. Using models like MobileNet and SVM, it detects emotions such as happiness or anger from facial expressions. With datasets like KDEF and RAF-DB, this tool offers an efficient way to evaluate service quality through facial recognition.
active 2024-09-22 → 2024-09-25 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 4 days from 2024-09-22 to 2024-09-25. Pushes: 12 total, peak 8 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| steveee27 | 12 | 12 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
No issue or PR events — this repo's activity is pushes only.
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.