This test uses the synthetic data generated in the previous test ("Pallet Jack" images in a logistics setting) to train a CV AI object detection model.

The AI development environment configurations are based on NVIDIA-Omniverse synthetic-data repository examples , which leverage the NVIDIA open-source Pre-Trained Tool Kit (TAO).

High-level training, validation, and real-world inference steps:

1. Convert synthetic data metadata records into a suitable format for an AI model.
   • Use an NVIDIA TAO detectnet-v2 container to convert KITTI to Tensorflow format.
   • Download a pre-trained CV AI model (ResNet-18 model).
2. Train the model on synthetic data.
3. Validate model on synthetic data.
4. Perform training and build validation model with synthetic data.

Results

The provided juypter notebook contains the code required to run training, validation, and inferencing.