TAO Object Detection

Object Detection using TAO DSSD

This notebook shows an example usecase of DSSD object detection using Train Adapt Optimize (TAO) Launcher. In this notebook, you will learn how to leverage the simplicity and convenience of TAO to:

• Take a pretrained resnet18 model and train a ResNet-18 DSSD model on the KITTI dataset
• Prune the trained DSSD model
• Retrain the pruned model to recover lost accuracy
• Export the pruned model
• Quantize the pruned model using QAT
• Run Inference on the trained model

  About Quick Deploy

  The quick deploy feature automatically sets up the Vertex AI instance with an optimal configuration, preloads the dependencies, runs the software from NGC without any need to set up the infrastructure.

  Get Started with Training

  To help you get started, we have created a sample Jupyter Notebook that can be easily deployed on Vertex AI using NGC’s quick deploy feature. This feature automatically sets up the Vertex AI instance with an optimal configuration, preloads the dependencies, runs the software from NGC without any need to set up the infrastructure.

Simply click on the button that reads “Deploy to Vertex AI” and follow the instructions.