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:1cda7d17a0f86e8eebc8b7c21447dc572bd08c82
Arguments:
--api-key ei_e593efafb236a8586d159bfd15355f5b7e06c7b9911638812f61a1da331aa96b --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:1cda7d17a0f86e8eebc8b7c21447dc572bd08c82 \
--api-key ei_e593efafb236a8586d159bfd15355f5b7e06c7b9911638812f61a1da331aa96b \
--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:bf04f3bfde31b63fa611d35ae148b340d34e6824
Arguments:
--api-key ei_e593efafb236a8586d159bfd15355f5b7e06c7b9911638812f61a1da331aa96b --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:bf04f3bfde31b63fa611d35ae148b340d34e6824 \
--api-key ei_e593efafb236a8586d159bfd15355f5b7e06c7b9911638812f61a1da331aa96b \
--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:b845bd798db8ba19aa182e8d12a75a4c0a41b36b
Arguments:
--api-key ei_e593efafb236a8586d159bfd15355f5b7e06c7b9911638812f61a1da331aa96b --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:b845bd798db8ba19aa182e8d12a75a4c0a41b36b \
--api-key ei_e593efafb236a8586d159bfd15355f5b7e06c7b9911638812f61a1da331aa96b \
--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-6-0:9343e4489066be39b2470d89d1890584a9c4aa2c
Arguments:
--api-key ei_e593efafb236a8586d159bfd15355f5b7e06c7b9911638812f61a1da331aa96b --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-6-0:9343e4489066be39b2470d89d1890584a9c4aa2c \
--api-key ei_e593efafb236a8586d159bfd15355f5b7e06c7b9911638812f61a1da331aa96b \
--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.
