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:314ee8adca425158bf382e06159532ae974b5b44
Arguments:
--api-key ei_7d09b7c8adc1e384c67683995b1d9c59162efcfea1d567693fdc84cd5c7198e4 --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:314ee8adca425158bf382e06159532ae974b5b44 \
--api-key ei_7d09b7c8adc1e384c67683995b1d9c59162efcfea1d567693fdc84cd5c7198e4 \
--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:8979a1cfa8124f1ba740d8e5a368962b2f74185d
Arguments:
--api-key ei_7d09b7c8adc1e384c67683995b1d9c59162efcfea1d567693fdc84cd5c7198e4 --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:8979a1cfa8124f1ba740d8e5a368962b2f74185d \
--api-key ei_7d09b7c8adc1e384c67683995b1d9c59162efcfea1d567693fdc84cd5c7198e4 \
--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:7c7a4004f6f2dd1365135c875a7250bb9199ba4b
Arguments:
--api-key ei_7d09b7c8adc1e384c67683995b1d9c59162efcfea1d567693fdc84cd5c7198e4 --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:7c7a4004f6f2dd1365135c875a7250bb9199ba4b \
--api-key ei_7d09b7c8adc1e384c67683995b1d9c59162efcfea1d567693fdc84cd5c7198e4 \
--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-6-0:4399a0946b8cf4f261fc7c66a6a703b512ff2568
Arguments:
--api-key ei_7d09b7c8adc1e384c67683995b1d9c59162efcfea1d567693fdc84cd5c7198e4 --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-6-0:4399a0946b8cf4f261fc7c66a6a703b512ff2568 \
--api-key ei_7d09b7c8adc1e384c67683995b1d9c59162efcfea1d567693fdc84cd5c7198e4 \
--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.
