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:0fa6b537767dda3dedb7e25103a7cc99b44de205
Arguments:
--api-key ei_f931c14dd5f556fba046eb70edb8f16f91dcf6bea77f5720ac829eaf7c31d081 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:0fa6b537767dda3dedb7e25103a7cc99b44de205 \
--api-key ei_f931c14dd5f556fba046eb70edb8f16f91dcf6bea77f5720ac829eaf7c31d081 \
--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:146f2646a08da24609b460a2451ff8293d46702c
Arguments:
--api-key ei_f931c14dd5f556fba046eb70edb8f16f91dcf6bea77f5720ac829eaf7c31d081 --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:146f2646a08da24609b460a2451ff8293d46702c \
--api-key ei_f931c14dd5f556fba046eb70edb8f16f91dcf6bea77f5720ac829eaf7c31d081 \
--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:4eca4a4d5e84c8be4bef2ddf1f53f0ad454a3d29
Arguments:
--api-key ei_f931c14dd5f556fba046eb70edb8f16f91dcf6bea77f5720ac829eaf7c31d081 --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:4eca4a4d5e84c8be4bef2ddf1f53f0ad454a3d29 \
--api-key ei_f931c14dd5f556fba046eb70edb8f16f91dcf6bea77f5720ac829eaf7c31d081 \
--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-6-0:1dfc978de07b79a368cd167b8af443130343c218
Arguments:
--api-key ei_f931c14dd5f556fba046eb70edb8f16f91dcf6bea77f5720ac829eaf7c31d081 --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-6-0:1dfc978de07b79a368cd167b8af443130343c218 \
--api-key ei_f931c14dd5f556fba046eb70edb8f16f91dcf6bea77f5720ac829eaf7c31d081 \
--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.
