CV / DeepLab v3
DeepLab v3 MobileNet v2 wo dilation
Alternative DeepLab v3 MobileNet v2 HEF without dilation for the R20 HailoRT segmentation module.
Choose the device you're using, the set up guide and documentation will update accordingly.
Getting Started
sudo docker run --rm \
--name cm5-hailo-deeplab-v3-mobilenet-v2-wo-dilation \
--privileged \
--net=host \
-e PYTHONUNBUFFERED=1 \
--device /dev/hailo0:/dev/hailo0 \
-v /usr/lib/libhailort.so.4.23.0:/usr/lib/libhailort.so.4.23.0:ro \
-v /usr/lib/libhailort.so:/usr/lib/libhailort.so:ro \
ghcr.io/seeed-projects/recomputer-r20-cv/deeplab_v3_mobilenet_v2:latest \
python web_detection.py --model_path model/deeplab_v3_mobilenet_v2_wo_dilation.hef --video_path video/test.mp4REST API
Use the REST API to run inference. Copy the commands below.
curl -X POST "http://<R20_IP>:8000/api/models/deeplab/predict" \
-F "file=@test.jpg"import requests
resp = requests.post(
"http://<R20_IP>:8000/api/models/deeplab/predict",
files={"file": open("test.jpg", "rb")},
timeout=30,
)
print(resp.json())Model Details
DeepLab v3 MobileNet v2 on reComputer R Series (CM5 + Hailo)
DeepLab v3 MobileNet v2 semantic segmentation with HailoRT, live preview, and REST inference.
This page is adapted from rpi5_hailo8_deeplab_v3_mobilenet_v2/README.md in reComputer-R20-CV. It targets reComputer R Series (CM5 + Hailo) with a PCIe Hailo-8 accelerator.
Hardware and Host Setup
| Item | Value |
|---|---|
| Board | reComputer R Series with Raspberry Pi CM5 |
| Accelerator | Hailo-8 M.2 over PCIe, exposed as /dev/hailo0 |
| OS | Raspberry Pi OS Bookworm, aarch64 |
| Host driver | hailo-all apt package |
| Validated HailoRT | 4.23.x; host driver, firmware, native library, and Python wheel must share major.minor |
sudo apt update
sudo apt install hailo-all
sudo reboot
# After reboot
hailortcli fw-control identify
ls /dev/hailo0
# Docker
curl -fsSL https://get.docker.com -o get-docker.sh
sudo sh get-docker.sh --mirror Aliyun
sudo systemctl enable docker
sudo systemctl start dockerRun With Demo Video
sudo docker run --rm --privileged --net=host \
-e PYTHONUNBUFFERED=1 \
--device /dev/hailo0:/dev/hailo0 \
-v /usr/lib/libhailort.so.4.23.0:/usr/lib/libhailort.so.4.23.0:ro \
-v /usr/lib/libhailort.so:/usr/lib/libhailort.so:ro \
ghcr.io/seeed-projects/recomputer-r20-cv/deeplab_v3_mobilenet_v2:latest \
python web_detection.py --model_path model/deeplab_v3_mobilenet_v2.hef --video_path video/test.mp4Open http://<R20_IP>:8000 to view the web preview. The image includes the module source, demo video, HailoRT Python wheel, and HEF files listed below.
The libhailort.so bind mounts intentionally come from the host. If your firmware is not 4.23.0, replace both paths with the version reported by hailortcli fw-control identify; rebuild the image if the major.minor version differs.
USB Camera Mode
sudo docker run --rm --privileged --net=host \
-e PYTHONUNBUFFERED=1 \
--device /dev/hailo0:/dev/hailo0 \
--device /dev/video0:/dev/video0 \
-v /usr/lib/libhailort.so.4.23.0:/usr/lib/libhailort.so.4.23.0:ro \
-v /usr/lib/libhailort.so:/usr/lib/libhailort.so:ro \
ghcr.io/seeed-projects/recomputer-r20-cv/deeplab_v3_mobilenet_v2:latest \
python web_detection.py --model_path model/deeplab_v3_mobilenet_v2.hef --camera_id 0Switch HEF variants
Override the image default by passing a different --model_path:
sudo docker run --rm --privileged --net=host \
-e PYTHONUNBUFFERED=1 \
--device /dev/hailo0:/dev/hailo0 \
-v /usr/lib/libhailort.so.4.23.0:/usr/lib/libhailort.so.4.23.0:ro \
-v /usr/lib/libhailort.so:/usr/lib/libhailort.so:ro \
ghcr.io/seeed-projects/recomputer-r20-cv/deeplab_v3_mobilenet_v2:latest \
python web_detection.py --model_path model/deeplab_v3_mobilenet_v2_wo_dilation.hef --video_path video/test.mp4HEF Files
| HEF | Size | Notes |
|---|---|---|
deeplab_v3_mobilenet_v2.hef | 4.68 MB | Default DeepLab v3 model |
deeplab_v3_mobilenet_v2_wo_dilation.hef | 4.09 MB | No-dilation DeepLab v3 variant |
REST API
Prediction endpoint:
POST http://<R20_IP>:8000/api/models/deeplab/predictExample image request:
curl -X POST "http://<R20_IP>:8000/api/models/deeplab/predict" \
-F "file=@test.jpg"Common service endpoints:
| Endpoint | Method | Purpose |
|---|---|---|
/ | GET | Web preview UI |
/api/models/deeplab/predict | POST | Single-frame inference from uploaded image/video or current frame |
/api/video_feed | GET | MJPEG preview stream |
/api/config | GET / POST | Read or update runtime thresholds |
/api/video/upload | POST | Upload a video for offline analysis |
/api/video/analyze | POST | Start offline analysis |
/api/video/status | GET | Poll analysis progress |
/api/video/list | GET | List uploaded and processed videos |
/api/video/download/{filename} | GET | Download processed output |
Development Notes
- Source module:
src/rpi5_hailo8_deeplab_v3_mobilenet_v2/ - Dockerfile:
docker/hailo8/deeplab_v3_mobilenet_v2.dockerfile - Main service:
web_detection.pywraps HailoRT inference, post-processing, MJPEG preview, REST prediction, and offline video analysis. - When swapping in a custom HEF, keep the output layout compatible with the module post-processing code or update
post_process_hailo().
Inputs and Outputs
Input: image, video, or USB camera frame. Output: semantic mask or overlay and annotated MJPEG preview.