node-deepstackai-trigger VS bi-aidetection

Step by step guide: https://github.com/danecreekphotography/node-deepstackai-trigger/wiki/Integrating-with-BlueIris

I do, using this Docker solution.

So I used this container to handle the deepstack integration. You can configure MQTT topics as handlers so that when the deepstack result is positive it triggers that topic. Basically just set NR up to listen for any events under the high level topic (so it can see every camera), parse the json data to perform whatever logic you want, and then if you want to trigger HD recording use a webrequest call blue iris like you normally would. Hopefully that makes some sense lol.

RPI4 using the latest CPU image for deepstack. Another way that I also like is using this project

I run Blue Iris with https://github.com/VorlonCD/bi-aidetection (getting very long since the last update, but still works great) and am very happy with it and am using DeepQuest AI's latest Windows release rather than Docker. I have 14 cameras going to a VM running it all with 24/7 low res recording and event triggered high res recording. I have MQTT reporting of events to Home Assistant for notifications and Blue Iris handles all the actual video pieces. The hardest part is finding decent RTSP cameras that don't re-stream from the cloud. I've got a mix of Amcrest, Reolink, and Unifi. The older Amcrest seem to work best, but the Unifi ones (once you get past the restream from the local UMD bit) are really good as well and provide a nice double layer for notification if I ever want it. I've been running this setup for just a little over 3 years now and the only real complaint I have is about the Reolink cameras. I have them working, but do not recommend them at all.

and this tool to gain ai detection https://ipcamtalk.com/threads/tool-tutorial-free-ai-person-detection-for-blue-iris.37330/

​ https://github.com/VorlonCD/bi-aidetection

1) https://github.com/gentlepumpkin/bi-aidetection 2) The fork: https://github.com/VorlonCD/bi-aidetection

This is a thread that discusses a technique for analyzing still images coming out of Blue Iris using DeepStack initially and later DeepQuestAI. Between those three links you should be able to get going.

The easiest way to think of it is a camera aimed at a driveway. You are probably interested in people and cars in a driveway. Since DeepStack doesn't know which part of the frame has motion, it will alert on a parked car in the frame even if something else triggered the motion. Dynamic masking will automatically apply an "ignore" mask on an object that has remained stationary for several frames and it will keep it ignored until it moves again. This allows you to enable alerts for cars and people, and only get alerted when a new car arrives in the driveway, or an existing parked car moves. This is the fork of AI_Tool that I use to accomplish this: https://github.com/VorlonCD/bi-aidetection/releases

I think what you are asking for came from this project: GitHub - VorlonCD/bi-aidetection: Alarm system for Blue Iris based on Artificial Intelligence.

@diymatt https://github.com/VorlonCD/bi-aidetection cool deepstack implementation for blue Iris