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:2a3b2676a1ddd46d5660cfdd25b4f63f78ed89db
Arguments:
--api-key ei_26aefe79ae6fb091232b7aa3c124ec0979b9551b28c16656d2881b37159852b6 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:2a3b2676a1ddd46d5660cfdd25b4f63f78ed89db \
--api-key ei_26aefe79ae6fb091232b7aa3c124ec0979b9551b28c16656d2881b37159852b6 \
--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:0b86e216b0055b86f9a128d9bec16f2322b4b36b
Arguments:
--api-key ei_26aefe79ae6fb091232b7aa3c124ec0979b9551b28c16656d2881b37159852b6 --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:0b86e216b0055b86f9a128d9bec16f2322b4b36b \
--api-key ei_26aefe79ae6fb091232b7aa3c124ec0979b9551b28c16656d2881b37159852b6 \
--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:e871897267c3595a7c6db7bd158b2a5ca478760d
Arguments:
--api-key ei_26aefe79ae6fb091232b7aa3c124ec0979b9551b28c16656d2881b37159852b6 --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:e871897267c3595a7c6db7bd158b2a5ca478760d \
--api-key ei_26aefe79ae6fb091232b7aa3c124ec0979b9551b28c16656d2881b37159852b6 \
--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:e919d6b6035d429c4d513eb18a62bdd20d008d43
Arguments:
--api-key ei_26aefe79ae6fb091232b7aa3c124ec0979b9551b28c16656d2881b37159852b6 --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:e919d6b6035d429c4d513eb18a62bdd20d008d43 \
--api-key ei_26aefe79ae6fb091232b7aa3c124ec0979b9551b28c16656d2881b37159852b6 \
--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.
