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:56d993738a1160ec707ed487879c384f29e71a37
Arguments:
--api-key ei_217483b3747daf7b8ec4c8bc85c527a6b22fa79e65aecdf8aa27deb2e3189786 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:56d993738a1160ec707ed487879c384f29e71a37 \
--api-key ei_217483b3747daf7b8ec4c8bc85c527a6b22fa79e65aecdf8aa27deb2e3189786 \
--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:c699e478fdd69a4bce74c2eb3876f44d5b5716a0
Arguments:
--api-key ei_217483b3747daf7b8ec4c8bc85c527a6b22fa79e65aecdf8aa27deb2e3189786 --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:c699e478fdd69a4bce74c2eb3876f44d5b5716a0 \
--api-key ei_217483b3747daf7b8ec4c8bc85c527a6b22fa79e65aecdf8aa27deb2e3189786 \
--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:4e7ee6616bf6b03f6fe164e46015f49776b1a8e8
Arguments:
--api-key ei_217483b3747daf7b8ec4c8bc85c527a6b22fa79e65aecdf8aa27deb2e3189786 --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:4e7ee6616bf6b03f6fe164e46015f49776b1a8e8 \
--api-key ei_217483b3747daf7b8ec4c8bc85c527a6b22fa79e65aecdf8aa27deb2e3189786 \
--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:a2a59a643b16fe7ef14a66ae7aa641fa41e52bad
Arguments:
--api-key ei_217483b3747daf7b8ec4c8bc85c527a6b22fa79e65aecdf8aa27deb2e3189786 --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:a2a59a643b16fe7ef14a66ae7aa641fa41e52bad \
--api-key ei_217483b3747daf7b8ec4c8bc85c527a6b22fa79e65aecdf8aa27deb2e3189786 \
--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.
