YOLOv11n on Raspberry Pi 5
github.com/kutekhoaisan/yolov11n_raspberrypi5- Category
- AI Tools
- Rank
- No. 2342Tools index
- Pricing
- Open Source
- Type
- TOOL
- Date
About
This is a C implementation of YOLOv11n object detection optimized with ARM NEON intrinsics for the Raspberry Pi 5, running the full 24-layer network in about 310 ms on a 768x576 test image, roughly 1.4x faster than the reference Python/Ultralytics implementation with identical detections. It ships as a single prebuilt library with no Python, PyTorch, or NumPy dependencies, giving instant startup and a low memory footprint for offline, embedded use.
Why it made the leaderboard
Lets embedded/edge developers run YOLOv11n object detection on a Raspberry Pi 5 without installing Python, PyTorch, or ultralytics, with faster inference and lower memory footprint than the reference implementation.
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