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:764d7dd583a505726a0dc2fc66f44418b2069c78
Arguments:
--api-key ei_061b4aaff418017c1e11b1dc69f41037a17ef5f31452986bf85eda5367b046e9 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:764d7dd583a505726a0dc2fc66f44418b2069c78 \
--api-key ei_061b4aaff418017c1e11b1dc69f41037a17ef5f31452986bf85eda5367b046e9 \
--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:8a43e586d7562a857942b94f9999610b63b91318
Arguments:
--api-key ei_061b4aaff418017c1e11b1dc69f41037a17ef5f31452986bf85eda5367b046e9 --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:8a43e586d7562a857942b94f9999610b63b91318 \
--api-key ei_061b4aaff418017c1e11b1dc69f41037a17ef5f31452986bf85eda5367b046e9 \
--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:877f696473bf4822f1a508052e5bb8fe8a238299
Arguments:
--api-key ei_061b4aaff418017c1e11b1dc69f41037a17ef5f31452986bf85eda5367b046e9 --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:877f696473bf4822f1a508052e5bb8fe8a238299 \
--api-key ei_061b4aaff418017c1e11b1dc69f41037a17ef5f31452986bf85eda5367b046e9 \
--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:cbc1c24aa4144795322a66809c51cc0770612276
Arguments:
--api-key ei_061b4aaff418017c1e11b1dc69f41037a17ef5f31452986bf85eda5367b046e9 --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:cbc1c24aa4144795322a66809c51cc0770612276 \
--api-key ei_061b4aaff418017c1e11b1dc69f41037a17ef5f31452986bf85eda5367b046e9 \
--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.
