Tiny Arm YOLO contains all of the packages necessary to run YOLO on a raspberry pi 3 b+.
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This container can be used to run YOLO on a Raspberry Pi as well as darknet-NNPACK, a version of Darknet that is optimized to be ran on a CPU.
YOLO classification takes roughly 30 seconds to complete on a Raspberry Pi, however, using NNPACK allows to cut this time down to under one second on a Raspberry Pi 3 B+.
This container has only been tested on a Raspberry Pi 3 B+. During the installation of darknet NNPACK, the CPU architecture must be specified. This could lead to issues with other versions of Raspberry Pis as they use different CPU architectures. I hypothesize that this would work on the Raspberry Pi 3 Model B as they both use Arm's Cortex A53 architecture.
I also predict that the non NNPACK YOLO implementation would work on any Raspberry Pi through this container as it is not dependent on CPU architecture.
Install Docker on the Raspberry Pi This tutorial was effective for me.
Run the Docker Image
Docker run -it -p 8080:8080 rollinsjw/tinyarmyolo:base /bin/bash
The -it flag is condenced from -i and -t. -i makes the container interactive and the -t flag allocates a pseudo-tty. The -p flag opens up port 8080 on the container and allows you to create a ssh tunnel to connect to a jupyter notebook running within the container.
cd darknet-nnpack
ls | grep weights
If the return is not blank, then you are in the correct directory.
./darknet detector test ./cfg/coco.data ./cfg/tiny-yolo.cfg yolov2-tiny.weights data/person.jpg
. Please pull the base tag to use.
Content type
Image
Digest
Size
743.2 MB
Last updated
almost 8 years ago
docker pull rollinsjw/tinyarmyolo:base