diff --git a/docs/how-to-guides/training-machine-learning-models/training-models.md b/docs/how-to-guides/training-machine-learning-models/training-models.md index 51c9091918d..4b9d3e96747 100644 --- a/docs/how-to-guides/training-machine-learning-models/training-models.md +++ b/docs/how-to-guides/training-machine-learning-models/training-models.md @@ -28,10 +28,17 @@ an example dataset containing three distinct classes (green, yellow, red), which Detailed instructions for training the traffic light classifier model can be found **[here](https://github.com/autowarefoundation/autoware.universe/blob/main/perception/traffic_light_classifier/README.md)**. - +To train custom CenterPoint models and convert them into ONNX format for deployment in Autoware, please refer to the instructions provided in the README file included with the +**"lidar_centerpoint"** package. These instructions will provide a step-by-step guide for training CenterPoint model. -## Training CenterPoint 3D object detection model +In order to assist you with your training process, we have also included an example dataset in the Tier4 dataset format. +This dataset contains 600 lidar frames and covers 5 classes, including 6905 cars, 3951 pedestrians, 75 cyclists, 162 buses, and 326 trucks. +You can utilize this example dataset to facilitate your training efforts. + +Detailed instructions for training the CenterPoint model can be found **[here](https://github.com/autowarefoundation/autoware.universe/blob/main/perception/lidar_centerpoint/README.md)**.