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:92d57efaea5f6f8147b3747c5a8ca827c534fde1
Arguments:
--api-key ei_a39602d5948d24dc1c1fe5ac02b7061d4f11e13739556ce150557d12ebecefb1 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:92d57efaea5f6f8147b3747c5a8ca827c534fde1 \
--api-key ei_a39602d5948d24dc1c1fe5ac02b7061d4f11e13739556ce150557d12ebecefb1 \
--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:42d52c449d4c1667496c4b6ac041d7b24cc88594
Arguments:
--api-key ei_a39602d5948d24dc1c1fe5ac02b7061d4f11e13739556ce150557d12ebecefb1 --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:42d52c449d4c1667496c4b6ac041d7b24cc88594 \
--api-key ei_a39602d5948d24dc1c1fe5ac02b7061d4f11e13739556ce150557d12ebecefb1 \
--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:18ac7fb19395952b7f7aa08bafa174854ca9ae28
Arguments:
--api-key ei_a39602d5948d24dc1c1fe5ac02b7061d4f11e13739556ce150557d12ebecefb1 --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:18ac7fb19395952b7f7aa08bafa174854ca9ae28 \
--api-key ei_a39602d5948d24dc1c1fe5ac02b7061d4f11e13739556ce150557d12ebecefb1 \
--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:a5941bbe9d543d5b5e579fae1ceac5dc97980b01
Arguments:
--api-key ei_a39602d5948d24dc1c1fe5ac02b7061d4f11e13739556ce150557d12ebecefb1 --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:a5941bbe9d543d5b5e579fae1ceac5dc97980b01 \
--api-key ei_a39602d5948d24dc1c1fe5ac02b7061d4f11e13739556ce150557d12ebecefb1 \
--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.
