LEIP Recipes are delivered as part of the LEIP SDK and made available inside a Docker image. You will need to have Docker installed to continue with this guide. A container is provided with all the required dependencies for the SDK while running this image. For more information on Docker images and containers, refer to the Docker Overview.
We highly recommend you increase the amount of memory you have allocated to Docker from the default to at least 4GB of memory.
You will need to meet the following specifications for your development environment to follow this recipe:
Your host computer must:
Have support for Docker.
Have a Linux operating system. For Windows support, please contact Latent AI.
Have an Nvidia graphics processing unit (GPU). This recipe supports Maxwell through Turing class GPUs. Ampere support is pending.
Have at least 16GB of RAM to run the experiment “as-is.” Refer to the troubleshooting section on how to modify the experiment if the system has less RAM.
Your target device must:
Be a Jetson AGX Xavier (32G of RAM).
Have JetPack SDK version 4.6.1 installed.
Your detection dataset needs to be in a supported format to use the plug-in BYOD feature. We currently support data in the MS COCO format.
Pulling the Container
Before you begin, you will need your license key and to have been granted access to the Latent AI container registry in order to complete the SDK installation process.
The LEIP SDK is distributed in a Docker container. Please verify you have Docker version 1.19 or greater installed on you target host and have allocated at least 4GB of memory for Docker. While Latent AI provides several Docker variants of the SDK depending on your hardware target, the initial AGX recipe is only provided with the Cuda Optimized container.
Then, choose the container you would like to use for your development environment. There are multiple options depending on your use case. The latest version will always include the latest tag. However, if you need a specific version, the versions are available by replacing the variant’s latest tag with the version number string (for example, registry.latentai.io/leip-sdk/gpu-cuda10.2:2.4.1).
If you need access to the registry or your license key, please contact firstname.lastname@example.org for assistance.
Docker Hub Namespace
Optimized CUDA GPU Support
# Login to the Latent AI container registry # (for credentials, refer to the instructions that came with your license key) docker login registry.latentai.io # Pull one of the LEIP SDK Docker images from the registry docker pull $variant
Starting the Container
Once you have pulled the container, start it by using your LEIP license.
# Run the container using a valid LEIP license key # and setting the `--gpus all` directive as needed docker run -e LICENSE_KEY=$license-key --name leip -it --gpus all --ipc=host $variant # TIP: after you exit the container, if you want to return to this container state docker start leip; docker attach leip # use docker rm leip to remove it
Next, let’s take a quick look at the stages that make up a recipe.