Hey Python people,
There was a thread about object detection quite a while back, but I haven't seen a mention of it since.
My situation is that, like many Indigo users, I have a Unifi Protect video setup and I'm not at all satisfied with its motion notifications. I experimented with Security Spy for person detection and that seemed to work OK but seems inelegant to me.
I started playing around with OpenCV, and it only took a couple evenings to get a useable Python service that watches an RTSP feed from Protect, runs it through YOLOv3-tiny, and logs when recognized objects are seen. It's taking around 75mS/frame without GPU on my laptop, and i'm recognizing at 1 frame per second. It wouldn't be unreasonable to run 5 cameras concurrently without further optimization, and I've ordered a Coral accelerator (https://coral.ai/products/accelerator/) to see how much impact that makes.
My question is: Is anybody else messing around with this sort of thing? Does anyone see value in making a new person-detector (cat-detector / toaster-detector / ...) plugin, or extending the existing security camera plugin?
I'm also looking for suggestions on a more surveillance-specific neural net that's reasonably performant. I'm not going to invest in training my own, but I'm guessing the Coco dataset isn't ideal for this application.
Any other thoughts, comments, ideas?
(FWIW, the installation wasn't that bad. I only needed NumPy and OpenCV-Python, and I might be able to factor out the NumPy requirement if I had to. The Yolo stuff is public domain, so I could bundle it with a hypothetical plugin)
Thanks