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:87049ffdac97814578a8eb90610fb89620f843bd
Arguments:
--api-key ei_32002302e48a0da7f1ac74f918b364e8d5b6c9f24e2272d39b5079de643300a8 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:87049ffdac97814578a8eb90610fb89620f843bd \
--api-key ei_32002302e48a0da7f1ac74f918b364e8d5b6c9f24e2272d39b5079de643300a8 \
--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:05926a492f8a440915266ea774513f4d7f7d69ad
Arguments:
--api-key ei_32002302e48a0da7f1ac74f918b364e8d5b6c9f24e2272d39b5079de643300a8 --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:05926a492f8a440915266ea774513f4d7f7d69ad \
--api-key ei_32002302e48a0da7f1ac74f918b364e8d5b6c9f24e2272d39b5079de643300a8 \
--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:1324212e2a5b32e59e31f3b959c45757960640d5
Arguments:
--api-key ei_32002302e48a0da7f1ac74f918b364e8d5b6c9f24e2272d39b5079de643300a8 --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:1324212e2a5b32e59e31f3b959c45757960640d5 \
--api-key ei_32002302e48a0da7f1ac74f918b364e8d5b6c9f24e2272d39b5079de643300a8 \
--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:bb88b238be0bfbefadf3a517000ba2b2c80e185a
Arguments:
--api-key ei_32002302e48a0da7f1ac74f918b364e8d5b6c9f24e2272d39b5079de643300a8 --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:bb88b238be0bfbefadf3a517000ba2b2c80e185a \
--api-key ei_32002302e48a0da7f1ac74f918b364e8d5b6c9f24e2272d39b5079de643300a8 \
--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.
