|
|
|
@@ -15,15 +15,15 @@ Follow the [Sedna installation document](/docs/setup/install.md) to install Sedn |
|
|
|
|
|
|
|
#### Prepare Images |
|
|
|
This example uses the following images: |
|
|
|
- Training worker: docker.io/luosiqi/sedna-robo:v0.1.2 |
|
|
|
- Evaluation worker: docker.io/luosiqi/sedna-robo:v0.1.2 |
|
|
|
- Inference worker: docker.io/luosiqi/sedna-robo:v0.1.2 |
|
|
|
- Training worker: kubeedge/sedna-example-lifelong-learning-cityscapes-segmentation:v0.6.0 |
|
|
|
- Evaluation worker: kubeedge/sedna-example-lifelong-learning-cityscapes-segmentation:v0.6.0 |
|
|
|
- Inference worker: kubeedge/sedna-example-lifelong-learning-cityscapes-segmentation:v0.6.0 |
|
|
|
|
|
|
|
These images are generated by the script [build_images.sh](/examples/build_image.sh). |
|
|
|
|
|
|
|
Users can also generate customized images for different workers and config them in yaml which will be presented in the following steps. |
|
|
|
|
|
|
|
#### Configure user nodes. |
|
|
|
#### Prepare user nodes |
|
|
|
``` |
|
|
|
WORKER_NODE=sedna-mini-control-plane |
|
|
|
|
|
|
|
@@ -58,8 +58,8 @@ unzip test_data.zip |
|
|
|
After finishing the above preparations, execute the following commands to config. |
|
|
|
``` |
|
|
|
local_prefix=/data |
|
|
|
cloud_image=docker.io/luosiqi/sedna-robo:v0.1.2 |
|
|
|
edge_image=docker.io/luosiqi/sedna-robo:v0.1.2 |
|
|
|
cloud_image=kubeedge/sedna-example-lifelong-learning-cityscapes-segmentation:v0.6.0 |
|
|
|
edge_image=kubeedge/sedna-example-lifelong-learning-cityscapes-segmentation:v0.6.0 |
|
|
|
data_url=$local_prefix/segmentation_data/data.txt |
|
|
|
OUTPUT=$local_prefix/lifelonglearningjob/output |
|
|
|
job_name=robo-demo |
|
|
|
|
SiqiLuo
2 years ago