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:b53227679668fb3b91312021e4c44e8d6f48c229
Arguments:
--api-key ei_3ecfd311cfb2404cd28e3362ef547c2f351cf7cf50cef8d587cebcecc9a68d4f --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:b53227679668fb3b91312021e4c44e8d6f48c229 \
--api-key ei_3ecfd311cfb2404cd28e3362ef547c2f351cf7cf50cef8d587cebcecc9a68d4f \
--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:fdf7ec69449e049b3baa68a94710a799ba23e242
Arguments:
--api-key ei_3ecfd311cfb2404cd28e3362ef547c2f351cf7cf50cef8d587cebcecc9a68d4f --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:fdf7ec69449e049b3baa68a94710a799ba23e242 \
--api-key ei_3ecfd311cfb2404cd28e3362ef547c2f351cf7cf50cef8d587cebcecc9a68d4f \
--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:8cc6bef0a7d18c4e04290964b37f734abbf6185c
Arguments:
--api-key ei_3ecfd311cfb2404cd28e3362ef547c2f351cf7cf50cef8d587cebcecc9a68d4f --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:8cc6bef0a7d18c4e04290964b37f734abbf6185c \
--api-key ei_3ecfd311cfb2404cd28e3362ef547c2f351cf7cf50cef8d587cebcecc9a68d4f \
--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:d746931e07a8d3e345ac3a1b1ca61980d60b7085
Arguments:
--api-key ei_3ecfd311cfb2404cd28e3362ef547c2f351cf7cf50cef8d587cebcecc9a68d4f --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:d746931e07a8d3e345ac3a1b1ca61980d60b7085 \
--api-key ei_3ecfd311cfb2404cd28e3362ef547c2f351cf7cf50cef8d587cebcecc9a68d4f \
--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.
