3 ms·

I have no problem imagining a security camera application needing to monitor quite a few video channels.

• andy_ppp 4y ago
  /camera/state/g
• h2odragon 4y ago
  Certainly. I'm suspecting that doing much of anything with all 96 channels would really need more RAM, for most users.
  • scottlamb 4y ago
    On the inference accelerator? IIUC, the RAM is just to hold the model and whatever state it needs during a particular inference operation. I'm not an expert on ML but AFAIK 16 GiB is plenty. I suppose it'd also need to hold onto reference frames for the video decoding, but at 1080p with e.g. YUV420 (12 bits per pixel), you can hold a lot of those in 16 GiB. edit: e.g., 4 references for each of the 96 streams would take ~1 GiB. Even on the host, 16 GiB is fine for say an NVR. They don't need to keep a lot of state in RAM (or for that matter to do a lot of on-CPU computation either). I can run an 8-stream NVR on a Raspberry Pi 2 without on-NVR analytics. That's about its limit because the network and disk are on the same USB2 bus, but there's spare CPU and RAM.
• phkahler 4y ago
  >> I have no problem imagining a security camera application needing to monitor quite a few video channels. As a joke I sometimes tell people the automatic flushing toilets in public bathrooms work by having a little camera monitored by someone in a 3rd world country who remotely flushes as needed, while monitoring a whole lot of video feeds. They usually don't buy it, but will often acknowledge that our world is uncomfortably close to having stuff like become reality.