This repository is a machine learning library to deploy for Autoware to aim for "robotics MLOps".
AWML supports training with T4dataset format in addition to open datasets and deployment for Autoware.
In addition to ML model deployment, AWML supports active learning framework include auto labeling, semi-auto labeling, and data mining.
AWML can deploy following task for now.
- 2D detection for dynamic recognition
- 3D detection for dynamic recognition
- 2D fine detection for traffic light recognition
- 2D classification for traffic light recognition
AWML supports following environment.
- All tools are tested by Docker environment on Ubuntu 22.04LTS
- NVIDIA dependency: CUDA 12.1 + cuDNN 8
- Need > 530.xx.xx NVIDIA device driver
If you want to know about the design of AWML, you should read following pages.
- Docs for architecture of dataset pipeline
- Docs for architecture of ML model
- Docs for architecture of S3 storage
- Docs for AWML design
If you want to develop AWML, you should read following pages.
If you want to search the OSS tools around AWML, you should read following pages.
If you want to know about AWML, you should read following pages.
- Setting environment for AWML
- Training and evaluation
- Analyze for the dataset and the model
- Auto labeling
- Data mining
- ROS2
- Model for Autoware
- Model for ML tools
- Model for Autoware
- Model for Autoware
- Model for ML tools
- Model for ML tools
- (TBD) SegmentAnything
- Model for Autoware
- Model for ML tools