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:d7552a554935a12eff0a72f7b1cfc7705f6e766c
Arguments:
--api-key ei_ff5b83e7a1560c628fb8024e23b2c59462f804b745bc86d52d1318721e77ab00 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:d7552a554935a12eff0a72f7b1cfc7705f6e766c \
--api-key ei_ff5b83e7a1560c628fb8024e23b2c59462f804b745bc86d52d1318721e77ab00 \
--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:87df3db405f763d76ecae38d34ba8d910440004d
Arguments:
--api-key ei_ff5b83e7a1560c628fb8024e23b2c59462f804b745bc86d52d1318721e77ab00 --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:87df3db405f763d76ecae38d34ba8d910440004d \
--api-key ei_ff5b83e7a1560c628fb8024e23b2c59462f804b745bc86d52d1318721e77ab00 \
--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:b3418a096f446d7f82e11e3f49e28933ba6373b5
Arguments:
--api-key ei_ff5b83e7a1560c628fb8024e23b2c59462f804b745bc86d52d1318721e77ab00 --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:b3418a096f446d7f82e11e3f49e28933ba6373b5 \
--api-key ei_ff5b83e7a1560c628fb8024e23b2c59462f804b745bc86d52d1318721e77ab00 \
--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-6-0:2bc781ba27b83c37f446b1f4ee45642e3c69bf8e
Arguments:
--api-key ei_ff5b83e7a1560c628fb8024e23b2c59462f804b745bc86d52d1318721e77ab00 --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-6-0:2bc781ba27b83c37f446b1f4ee45642e3c69bf8e \
--api-key ei_ff5b83e7a1560c628fb8024e23b2c59462f804b745bc86d52d1318721e77ab00 \
--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.
