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:8b53cfe6423634ce80de11f0ed3bdcd51206a5fd
Arguments:
--api-key ei_437e15d980c4af2c7875d07b976b8395c405e0517172f32181f843daeb4c7436 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:8b53cfe6423634ce80de11f0ed3bdcd51206a5fd \
--api-key ei_437e15d980c4af2c7875d07b976b8395c405e0517172f32181f843daeb4c7436 \
--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:9e5bdb3e0065b53a7ed532e833ff2c2df852d73a
Arguments:
--api-key ei_437e15d980c4af2c7875d07b976b8395c405e0517172f32181f843daeb4c7436 --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:9e5bdb3e0065b53a7ed532e833ff2c2df852d73a \
--api-key ei_437e15d980c4af2c7875d07b976b8395c405e0517172f32181f843daeb4c7436 \
--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:0d0bbbfdceb20a331825e9a453f3e7eb5952067c
Arguments:
--api-key ei_437e15d980c4af2c7875d07b976b8395c405e0517172f32181f843daeb4c7436 --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:0d0bbbfdceb20a331825e9a453f3e7eb5952067c \
--api-key ei_437e15d980c4af2c7875d07b976b8395c405e0517172f32181f843daeb4c7436 \
--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:c822db8f8b81888e9ae8a7bd236e7323e02acd91
Arguments:
--api-key ei_437e15d980c4af2c7875d07b976b8395c405e0517172f32181f843daeb4c7436 --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:c822db8f8b81888e9ae8a7bd236e7323e02acd91 \
--api-key ei_437e15d980c4af2c7875d07b976b8395c405e0517172f32181f843daeb4c7436 \
--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.
