This project implements a body part recognition system using machine learning techniques. It processes DICOM images, converts them to PNG format, and utilizes SVM and KNN classifiers to identify various body parts from the images. The system is structured to load training and testing datasets, preprocess images, and evaluate model accuracy.
active 2025-01-02 → 2025-01-02 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2025-01-02 to 2025-01-02. Pushes: 4 total, peak 4 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: 1 total, peak 1 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 |
|---|---|---|---|---|
| amWRit | 4 | 4 | 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 — 1 stars here means stars gained during the window, not the repo's star count.