George-Hotz/yolov8_seg_tensorRT
在Jetson AGX Xavier上部署yolov8-seg检测分割模型（带自适应低光照补偿）
This project helps process live video streams or recorded video files for object detection and segmentation, even in challenging low-light conditions. It takes video input and produces a new video file with detected objects outlined by bounding boxes and precise segmentation masks. This is ideal for applications needing real-time visual analysis, such as security monitoring, quality control on a production line, or autonomous robotics.
No commits in the last 6 months.
Use this if you need to perform high-performance, real-time object detection and segmentation on video footage, especially in environments where lighting can be poor.
Not ideal if you primarily work with static images or do not require low-light compensation for your video analysis tasks.
Stars
50
Forks
2
Language
Cuda
License
—
Category
Last pushed
Feb 24, 2025
Commits (30d)
0
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