Hi all! i finally come around publishing a small side project i am running at my home for the last few years. This past month i have revamped it by rewriting the C++ backend and improving the web UI (single page HTML+CSS+AlpineJS) for a broader public.
LazyNVR is a different take on hosting webcams and centralizing access to them. Instead of working on the cameras feed, which is CPU/GPU heavy and doesn't scale much, it relies on cameras on-board capabilities to detect motion and upload recorded videos to your own server.
If you own IP cameras from brands like Dahua, Reolink and many others, you can leverage their on board motion detection capabilities and off-load your server computational power using LazyNVR.
I have some 15 cameras and tools like Frigate or MotionEye just kill my server CPU, but all my cameras can detect motions and automatically record a video and upload it to my server using different protocols (like FTP, sftp, and such). So LazyNVR was born.
The server is written in C++ and basically detect incoming videos, recode (without re-encoding) them to an MP4 web streammable format, and store them well sorted. It will also keep your incoming folders clean and purge stored videos when they are too old. The server will also fetch and refresh still live images from the cameras.
The client is a WEB GUI, actually a single HTML file with CSS and some AlpineJS, which will show the still live images and the list of all the recorded videos letting you download or view them directly.
I am running over 15 cameras from my RaspPi with basically 0% CPU overhead.
I have published LazyNVR on Codeberg (here https://codeberg.org/LazyNVR/lazynvr-sources) because well, i think it's better than GitHub. And there is also a pretty lazy web site on https://www.lazynvr.it/ (which mostly redirect to Codeberg).
Currently there are docker images for AMD64 and ARM64, but it's pretty easy to compile directly, with the provided instructions in the Codeberg Wiki.
Please, feel free to try it!
Mandatory AI disclaimer: i don't use AI for coding. Zero code (C++ or Javscript) has been written by or with AI support in this project. I have used AI extensively for the CSS stuff that i hate, but reviewed and mostly edited it anyway. I have also used AI for research and to write the dockerfile faster, since i am no docker expert. I have personally written the dockerfile anyway, and personally tested as well. The logo has been created with AI, probably it shows.
Sounds like this could pretty easily be run alongside Frigate for testing. I'll have to check it out!
Yes indeed if your camera have motion detection embedded, it will work.
I tested frigate but after two cameras or so my small server CPU was hammered. This solution works for my 15 cameras with almost zero CPU impact.
I assume frigate can do a much better motion detection and filtering tough.