vehicle-cv-adas AmoabaKelvin · COMPLETED
The project can achieve FCWS, LDWS, and LKAS functions solely using only visual sensors. using YOLOv5 / YOLOv5-lite / YOLOv6 / YOLOv7 / YOLOv8 / YOLOv9 / EfficientDet and Ultra-Fast-Lane-Detection-v2 .
github.com/AmoabaKelvin/vehicle-cv-adas · ★ 0 · Forks 0 · Size 23.2 MB
SUMMARY
Technologies 6
Scored 6
Observed 6
Practices 6
Evidence 7
Skips 0
COVERAGE
Analyzed 71 files · 72 commits · 0 API calls
TECHNOLOGIES & DEPTH
Markdown LANGUAGE Depth 70
1 files · PRODUCTION
JSON LANGUAGE Depth 70
1 files · PRODUCTION
Python LANGUAGE Depth 70
47 files · PRODUCTION
pip BUILD_TOOL Depth 80
1 files · CONFIGURATION
NumPy LIBRARY Depth 81
23 files · PRODUCTION
TypeScript LANGUAGE Depth 58
1 files · PRODUCTION
PRACTICES
documentation · observedautomated_tests · absentcontinuous_integration · absentcontainerization · absentlinting · absentformatting · absent
ACTIVITY & OWNERSHIP
First commit 2023-01-10
Last commit 2024-10-02
Active months 14
Commits 72