Rock 5 with Ubuntu 22.04 OS image
Installation.
- Get a 16 GB (minimal) SD card holding the image.
- Download the
Rock5_Ubuntu22.img.xzimage (3.6 GByte) from our Sync site. - Flash the image on the SD card with the Imager or balenaEtcher.
- Insert the SD card in your Rock 5 and enjoy.
- Username: 5ubuntu22
- no password
Model performance benchmark(FPS)
All models, with C++ examples, can be found on the SD image.
| demo | model_name | inputs_shape | dtype | Rock 5 |
|---|---|---|---|---|
| yolov5 | yolov5s_relu | [1, 3, 640, 640] | INT8 | 50.0 |
| yolov5n | [1, 3, 640, 640] | INT8 | 58.8 | |
| yolov5s | [1, 3, 640, 640] | INT8 | 37.7 | |
| yolov5m | [1, 3, 640, 640] | INT8 | 16.2 | |
| yolov6 | yolov6n | [1, 3, 640, 640] | INT8 | 63.0 |
| yolov6s | [1, 3, 640, 640] | INT8 | 29.5 | |
| yolov6m | [1, 3, 640, 640] | INT8 | 15.4 | |
| yolov7 | yolov7-tiny | [1, 3, 640, 640] | INT8 | 53.4 |
| yolov7 | [1, 3, 640, 640] | INT8 | 9.4 | |
| yolov8 | yolov8n | [1, 3, 640, 640] | INT8 | 53.1 |
| yolov8s | [1, 3, 640, 640] | INT8 | 28.5 | |
| yolov8m | [1, 3, 640, 640] | INT8 | 12.1 | |
| yolox | yolox_s | [1, 3, 640, 640] | INT8 | 30.0 |
| yolox_m | [1, 3, 640, 640] | INT8 | 12.9 | |
| ppyoloe | ppyoloe_s | [1, 3, 640, 640] | INT8 | 28.8 |
| ppyoloe_m | [1, 3, 640, 640] | INT8 | 13.1 | |
| yolov5_seg | yolov5n-seg | [1, 3, 640, 640] | INT8 | 9.4 |
| yolov5s-seg | [1, 3, 640, 640] | INT8 | 7.8 | |
| yolov5m-seg | [1, 3, 640, 640] | INT8 | 6.1 | |
| yolov8_seg | yolov8n-seg | [1, 3, 640, 640] | INT8 | 8.9 |
| yolov8s-seg | [1, 3, 640, 640] | INT8 | 7.3 | |
| yolov8m-seg | [1, 3, 640, 640] | INT8 | 4.5 | |
| ppseg | ppseg_lite_1024x512 | [1, 3, 512, 512] | INT8 | 27.5 |
| RetinaFace | RetinaFace_mobile320 | [1, 3, 320, 320] | INT8 | 243.6 |
| RetinaFace_resnet50_320 | [1, 3, 320, 320] | INT8 | 43.4 | |
| PPOCR-Det | ppocrv4_det | [1, 3, 480, 480] | INT8 | 31.5 |
| PPOCR-Rec | ppocrv4_rec | [1, 3, 48, 320] | FP16 | 35.7 |
- Due to the pixel-wise filling and drawing, segmentation models are relatively slow
Tips.
- If you need extra space delete the opencv and the opencv_contrib folder from the SD card. They are no longer needed since all libraries are stored in the /usr/ directory.
- Use a tool like GParted
sudo apt-get install gpartedto expand the image to larger SD cards. We recommend a minimum of 64 GB. Deep learning requires a lot of space.
Pre-installed frameworks.
- OpenCV 4.8.0
- ncnn 20240410
- NPU rknpu2 1.5.2
- NPU model zoo 2.0.0
- NPU model zoo models 2.0.0
Thanks.
A more than special thanks to Stuart Naylor, who, ever so kindly, provided us with the Rock Pi 5 for free.
And Joshua Riek for all the hard work on the Ubuntu OS.
