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:8ff0a60f98a3446f1f38e387def80493aa00925f
Arguments:
--api-key ei_fc2cff995bca76653f443cc16fbdccc937f5c1e0e05d3063931ff29233da845f --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:8ff0a60f98a3446f1f38e387def80493aa00925f \
--api-key ei_fc2cff995bca76653f443cc16fbdccc937f5c1e0e05d3063931ff29233da845f \
--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:af2b6a2650e7990e2cb600f93d36ab193bbda8bd
Arguments:
--api-key ei_fc2cff995bca76653f443cc16fbdccc937f5c1e0e05d3063931ff29233da845f --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:af2b6a2650e7990e2cb600f93d36ab193bbda8bd \
--api-key ei_fc2cff995bca76653f443cc16fbdccc937f5c1e0e05d3063931ff29233da845f \
--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:dd269e8947b3a192ddd027cffa09db296306a825
Arguments:
--api-key ei_fc2cff995bca76653f443cc16fbdccc937f5c1e0e05d3063931ff29233da845f --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:dd269e8947b3a192ddd027cffa09db296306a825 \
--api-key ei_fc2cff995bca76653f443cc16fbdccc937f5c1e0e05d3063931ff29233da845f \
--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-6-0:4c40e442d1623133e8b77d424383f9e52640fdb8
Arguments:
--api-key ei_fc2cff995bca76653f443cc16fbdccc937f5c1e0e05d3063931ff29233da845f --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-6-0:4c40e442d1623133e8b77d424383f9e52640fdb8 \
--api-key ei_fc2cff995bca76653f443cc16fbdccc937f5c1e0e05d3063931ff29233da845f \
--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.
