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But let's be honest, everyone needs Home Assistant in their life

Very much so, but making the move to becoming open source. VorlonCD's fork of the original AI Tool is the one most of us use.

I'd say that's a bit too deep as you'd need SMTP authentication details, etc. If I wanted that info likely look to MQTT and Node Red.

My GPU is a low end 1030 Nvidia

Sounds complex. I did it GUI all the way...

I run Deepstack in an auto-restarting Docker container in WSL2. I do this using Task Scheduler as per the answer in this thread. I have nothing against VMs. I use them for running PiHole, Home Assistant, my NAS, my system monitor, etc. But why do it if you don't have to?

Sorry, just catching up after a few days away. [GIN] 2020/12/29 - 16:26:52 | 200 | 128.7103ms | 172.17.0.1 | POST /v1/vision/detection [GIN] 2020/12/29 - 16:26:56 | 200 | 144.0097ms | 172.17.0.1 | POST /v1/vision/detection [GIN] 2020/12/29 - 16:26:59 | 200 | 139.4709ms...

Though I have the JPEG at 100%

I have two GPU Deepstack instances running on ports 83 and 84. Seems to work fine.

Do you have the technical preview build of Docker? GPU support in Docker Desktop is a new feature not in the main release yet: https://www.docker.com/blog/wsl-2-gpu-support-is-here/

The 24/7 recording is in case the AI fails to notice something, as I want something recorded. And I don't want to dedicate disk space resources to storing 24/7 4k streams.

Odd question. For others running AITool as a server, do you stop the server in Task Manager before opening the AITool program to make changes, see the history, etc?

I did similar to start with. I have evolved now to having this per camera: Low res substream - 24/7 recording with no motion detection. High res main stream that records video when triggered by AITool. A second high res main stream that records JPEG resized to 1280x720 (and not video) on motion...

I have it working exactly like this. However I think you need to have a Windows Insider build to enable WSL to access the GPU as per here.

So the saving of the image into the folder from BI? Have you changed the time down from the default 1 minute in the jpeg options?

FYI, Docker now supports GPU in WSL 2: WSL 2 GPU Support is Here - Docker Blog

Using deepstack:Jetson in High with 640x480 I get 300ms. But I'm missing lots of genuine triggers as confidence is low.

@Mattias Fornander - I also offloaded my Deepstack to a Jetson when they released a version that finally worked on the platform! Thanks for the tip about MODE=High, I'd missed that.

Sorry if already mentioned, but possible interest for members here: DeepStack Release on Jetson Still a Beta, but works for me and takes a load of my ageing BI machine.

My bad. To use GPU at all from Docker you'll need to be using WSL with the Cuda build toolkit. I tried this but failed a while back. My current solution is that I'm running Proxmox with Docker on bare metal, with BI running in a Windows virtual machine. Unfortunately Proxmox doesn't like Nvidia...

@setchells curl -s -L https://nvidia.github.io/nvidia-container-runtime/gpgkey | sudo apt-key add - distribution=$(. /etc/os-release;echo $ID$VERSION_ID) curl -s -L https://nvidia.github.io/nvidia-container-runtime/$distribution/nvidia-container-runtime.list |\ sudo tee...

Damn it, that's my old post. I must try again in that case, as I never got it working...

Stupid question I apologize as possibly somewhere in the 115 pages. How to people get the MQTT "label (confidence)" pairs out of the @Chris Dodge fork (which is excellent) to use in Home Assistant and/or NodeRed? The sensor currently gets this to it: Person (80%),Car (96%),Car (41%),Truck...

Many thanks to GP for the original code, and CD for the awesome additions. All I need now is Deepstack to release a Jetson Nano version and I'm golden!

Issue 1 - I was using VISION-SCENE not VISION-DETECTION. Numpty.

FYI - My docker in WSL isn't the Docker Desktop version with WSL, it's the version of Docker in my Ubuntu install so I could get all the nvidia gubbins... I tested using the GPU on Docker with this: tim@WinServer:~$ docker run --gpus all nvcr.io/nvidia/k8s/cuda-sample:nbody nbody -gpu...

I'm running Deepstack as the latest docker version (deepquestai/deepstack:gpu) that doesn't require a key. The URL in a browser gives me the activated message: However, that's on a 127.20.9.x subnet, where the log was talking about 127.0.0.x subnets. Hmmm....

Or AI is programmed by a man, so inherently sexist? ;)

I think I'm getting there with this. Thanks to all the community hard work for creating guides and tools like this. I was maxing out my ancient CPU (i7 960 from back in the day) trying to run Deepstack, with image processing times being multiple seconds. Not workable. However, given the...