Deploy to any Linux-based development board
Edge Impulse for Linux lets you run your models on any Linux-based development board,
with SDKs for Node.js, Python, Go and C++ to integrate your models quickly into
your application.
- Install the Edge Impulse Linux CLI
- Run
edge-impulse-linux-runner (run with --clean to switch projects)
Run your model as a Docker container
To run your model as a container with an HTTP interface, use:
Container:
public.ecr.aws/g7a8t7v6/inference-container:3fb08736838adf4bf8aecbfe5c9c161ffa5b77c0
Arguments:
--api-key ei_0c92a2e113c6e54038f25074cb8408b1519ed567a520d687654c18ecff6c9e79 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:3fb08736838adf4bf8aecbfe5c9c161ffa5b77c0 \
--api-key ei_0c92a2e113c6e54038f25074cb8408b1519ed567a520d687654c18ecff6c9e79 \
--run-http-server 1337
This automatically builds and downloads the latest model (incl. hardware optimizations), and runs an HTTP endpoint at
http://localhost:1337 with instructions.
Read the docs for information,
like bundling in your model inside the container and selecting extra hardware optimizations.
Run your model as a Docker container
To run your model as a container with an HTTP interface on NVIDIA Jetson's GPUs (JetPack 4.6.x), use:
Container:
public.ecr.aws/g7a8t7v6/inference-container-jetson:e8573c35248c7f6e96b5c6c735b863069ce061dc
Arguments:
--api-key ei_0c92a2e113c6e54038f25074cb8408b1519ed567a520d687654c18ecff6c9e79 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it --runtime=nvidia --gpus all \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container-jetson:e8573c35248c7f6e96b5c6c735b863069ce061dc \
--api-key ei_0c92a2e113c6e54038f25074cb8408b1519ed567a520d687654c18ecff6c9e79 \
--run-http-server 1337
This automatically builds and downloads the latest model (incl. hardware optimizations), and runs an HTTP endpoint at
http://localhost:1337 with instructions.
Read the docs for information,
like bundling in your model inside the container and selecting extra hardware optimizations.
Run your model as a Docker container
To run your model as a container with an HTTP interface on NVIDIA Jetson Orin's GPUs (JetPack 5.1.x), use:
Container:
public.ecr.aws/g7a8t7v6/inference-container-jetson-orin:3eb6076442d9d6f0ced0933b10a75588deb95982
Arguments:
--api-key ei_0c92a2e113c6e54038f25074cb8408b1519ed567a520d687654c18ecff6c9e79 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it --runtime=nvidia --gpus all \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container-jetson-orin:3eb6076442d9d6f0ced0933b10a75588deb95982 \
--api-key ei_0c92a2e113c6e54038f25074cb8408b1519ed567a520d687654c18ecff6c9e79 \
--run-http-server 1337
This automatically builds and downloads the latest model (incl. hardware optimizations), and runs an HTTP endpoint at
http://localhost:1337 with instructions.
Read the docs for information,
like bundling in your model inside the container and selecting extra hardware optimizations.
Run your model as a Docker container
To run your model as a container with an HTTP interface on NVIDIA Jetson Orin's GPUs (JetPack 6.0), use:
Container:
public.ecr.aws/g7a8t7v6/inference-container-jetson-orin-6-0:f602f62311460044a6da346fde777e93123ef48e
Arguments:
--api-key ei_0c92a2e113c6e54038f25074cb8408b1519ed567a520d687654c18ecff6c9e79 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it --runtime=nvidia --gpus all \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container-jetson-orin-6-0:f602f62311460044a6da346fde777e93123ef48e \
--api-key ei_0c92a2e113c6e54038f25074cb8408b1519ed567a520d687654c18ecff6c9e79 \
--run-http-server 1337
This automatically builds and downloads the latest model (incl. hardware optimizations), and runs an HTTP endpoint at
http://localhost:1337 with instructions.
Read the docs for information,
like bundling in your model inside the container and selecting extra hardware optimizations.
