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:17837ffeb47de872efd47245bdc8bb80bfd6be35
Arguments:
--api-key ei_4782f540bbb1b8b7455b3dd4176e807829fbcea4a4cefaae6e3de5632eefbeaf --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:17837ffeb47de872efd47245bdc8bb80bfd6be35 \
--api-key ei_4782f540bbb1b8b7455b3dd4176e807829fbcea4a4cefaae6e3de5632eefbeaf \
--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:29a2854c935bcc1ea42caa17697e5381b2806a91
Arguments:
--api-key ei_4782f540bbb1b8b7455b3dd4176e807829fbcea4a4cefaae6e3de5632eefbeaf --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:29a2854c935bcc1ea42caa17697e5381b2806a91 \
--api-key ei_4782f540bbb1b8b7455b3dd4176e807829fbcea4a4cefaae6e3de5632eefbeaf \
--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:b5ff125b7cee06084dbb42d08b85fbe6a83453ce
Arguments:
--api-key ei_4782f540bbb1b8b7455b3dd4176e807829fbcea4a4cefaae6e3de5632eefbeaf --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:b5ff125b7cee06084dbb42d08b85fbe6a83453ce \
--api-key ei_4782f540bbb1b8b7455b3dd4176e807829fbcea4a4cefaae6e3de5632eefbeaf \
--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-6-0:95361799242485af99baff5699faf2243daead76
Arguments:
--api-key ei_4782f540bbb1b8b7455b3dd4176e807829fbcea4a4cefaae6e3de5632eefbeaf --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-6-0:95361799242485af99baff5699faf2243daead76 \
--api-key ei_4782f540bbb1b8b7455b3dd4176e807829fbcea4a4cefaae6e3de5632eefbeaf \
--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.
