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CV / YOLO26

YOLO26-seg

YOLO26 segmentation HEFs run through HailoRT. The one2one CPU decoder produces instance masks and boxes for 80 COCO classes.

14 downloads
Size
6.0 MB
Memory
4GB+
Precision
Hailo HEF / HailoRT

Choose the device you're using, the set up guide and documentation will update accordingly.

Getting Started

Deploy
sudo docker run --rm \
  --name cm5-hailo-yolo26n-seg \
  --privileged \
  --net=host \
  -e PYTHONUNBUFFERED=1 \
  --device /dev/hailo0:/dev/hailo0 \
  -v /usr/lib/libhailort.so.5.1.1:/usr/lib/libhailort.so.5.1.1:ro \
  -v /usr/lib/libhailort.so:/usr/lib/libhailort.so:ro \
  ghcr.io/seeed-projects/recomputer-hailo10h-cv/yolo26n_seg:latest \
  python web_detection.py --model_path model/yolo26n_seg.hef --video_path video/test.mp4

Model Details

reComputer CM5 + Hailo-10H

YOLO26-seg on reComputer CM5 + Hailo-10H

YOLO26n/s/m-seg models run on Hailo-10H through HailoRT. The one2one CPU decode (DFL + top-k + prototype-mask assembly) produces instance masks and boxes for 80 COCO classes.

Model Info

VariantInputPackaged HEFContainer image
YOLO26n-seg640×640×3 RGB6.0 MByolo26n_seg
YOLO26s-seg640×640×3 RGB17.5 MByolo26s_seg
YOLO26m-seg640×640×3 RGB27.0 MiB (28.3 MB)yolo26m_seg

Hardware and Host Setup

ItemValue
BoardRaspberry Pi CM5
AcceleratorHailo-10H, /dev/hailo0
RuntimeHailoRT 5.1.1
OSRaspberry Pi OS Bookworm, aarch64
bash
sudo apt update
sudo apt install hailo-h10-all -y
sudo reboot

# After reboot
hailortcli fw-control identify
ls /dev/hailo0

Run With Demo Video

Select the command matching the model variant.

YOLO26n-seg

bash
sudo docker run --rm --privileged --net=host \
  --name cm5-hailo-yolo26n-seg \
  -e PYTHONUNBUFFERED=1 \
  --device /dev/hailo0:/dev/hailo0 \
  -v /usr/lib/libhailort.so.5.1.1:/usr/lib/libhailort.so.5.1.1:ro \
  -v /usr/lib/libhailort.so:/usr/lib/libhailort.so:ro \
  ghcr.io/seeed-projects/recomputer-hailo10h-cv/yolo26n_seg:latest \
  python web_detection.py --model_path model/yolo26n_seg.hef --video_path video/test.mp4

YOLO26s-seg

bash
sudo docker run --rm --privileged --net=host \
  --name cm5-hailo-yolo26s-seg \
  -e PYTHONUNBUFFERED=1 \
  --device /dev/hailo0:/dev/hailo0 \
  -v /usr/lib/libhailort.so.5.1.1:/usr/lib/libhailort.so.5.1.1:ro \
  -v /usr/lib/libhailort.so:/usr/lib/libhailort.so:ro \
  ghcr.io/seeed-projects/recomputer-hailo10h-cv/yolo26s_seg:latest \
  python web_detection.py --model_path model/yolo26s_seg.hef --video_path video/test.mp4

YOLO26m-seg

bash
sudo docker run --rm --privileged --net=host \
  --name cm5-hailo-yolo26m-seg \
  -e PYTHONUNBUFFERED=1 \
  --device /dev/hailo0:/dev/hailo0 \
  -v /usr/lib/libhailort.so.5.1.1:/usr/lib/libhailort.so.5.1.1:ro \
  -v /usr/lib/libhailort.so:/usr/lib/libhailort.so:ro \
  ghcr.io/seeed-projects/recomputer-hailo10h-cv/yolo26m_seg:latest \
  python web_detection.py --model_path model/yolo26m_seg.hef --video_path video/test.mp4

Open http://<Board_IP>:8000 for the Web preview. Use /api/video_feed for the MJPEG stream.

REST API

Each variant has its own endpoint:

VariantEndpoint
YOLO26n-segPOST /api/models/yolo26n_seg/predict
YOLO26s-segPOST /api/models/yolo26s_seg/predict
YOLO26m-segPOST /api/models/yolo26m_seg/predict

Example:

bash
curl -X POST "http://<Board_IP>:8000/api/models/yolo26n_seg/predict" \
  -F "file=@test.jpg"

The response contains predictions entries with box, confidence, and class_id fields.

Development

VariantSourceDockerfile
YOLO26n-segsrc/hailo10h_yolo26n_seg/docker/hailo10h/yolo26n_seg.dockerfile
YOLO26s-segsrc/hailo10h_yolo26s_seg/docker/hailo10h/yolo26s_seg.dockerfile
YOLO26m-segsrc/hailo10h_yolo26m_seg/docker/hailo10h/yolo26m_seg.dockerfile

Inputs and Outputs

Input: image (640x640 RGB). Output: instance masks, boxes, classes and confidences for 80 COCO classes.