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:106574ce36ef4d453528315cedaf930a7b32e3be
Arguments:
--api-key ei_3d5f812072c79069e2d3669e356eaee28373b15b1310554187c3975dcb19a7a3 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:106574ce36ef4d453528315cedaf930a7b32e3be \
--api-key ei_3d5f812072c79069e2d3669e356eaee28373b15b1310554187c3975dcb19a7a3 \
--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:82f0d132abc331a05ce7003242ef85fec24ba5cc
Arguments:
--api-key ei_3d5f812072c79069e2d3669e356eaee28373b15b1310554187c3975dcb19a7a3 --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:82f0d132abc331a05ce7003242ef85fec24ba5cc \
--api-key ei_3d5f812072c79069e2d3669e356eaee28373b15b1310554187c3975dcb19a7a3 \
--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:aedc76ee4d5dedfc25d3c162142f8f2de2d1a460
Arguments:
--api-key ei_3d5f812072c79069e2d3669e356eaee28373b15b1310554187c3975dcb19a7a3 --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:aedc76ee4d5dedfc25d3c162142f8f2de2d1a460 \
--api-key ei_3d5f812072c79069e2d3669e356eaee28373b15b1310554187c3975dcb19a7a3 \
--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:d7f289dedf5ebb57c411674a183fefa5ee3984b4
Arguments:
--api-key ei_3d5f812072c79069e2d3669e356eaee28373b15b1310554187c3975dcb19a7a3 --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:d7f289dedf5ebb57c411674a183fefa5ee3984b4 \
--api-key ei_3d5f812072c79069e2d3669e356eaee28373b15b1310554187c3975dcb19a7a3 \
--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.
