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Douglas Adams said we'd have robots to watch TV for us. That seems to be the designed use case for this. 16gb RAM / 96 video channels ... I haven't done any o

Douglas Adams said we'd have robots to watch TV for us. That seems to be the designed use case for this. 16gb RAM / 96 video channels ... I haven't done any of that work but it feels like they expect that "96" not to be fully used in practice.

inetsee 4y ago
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.
deleted 4y ago
[deleted]
hhh 4y ago
I have models in production that currently monitor ~400 cameras with an addition of 2-3 cameras/month. If it were cheap enough, it would be useful for our use case (Quality Control). We generally pull from cameras roughly 6400 pixels per region of interest, of which one instance may have 4-30 RoIs across N cameras.
- 71a54xd 4y ago
  Curious where I could learn more about models like this / potentially see some open code outlining tooling / infra required as well?
  - hhh 4y ago
    Not sure about open information about the models, but from tooling/infra we are running k8s w/ in-house API for image acquisition. Features are defined as x,y coordinates denoting center of a feature, with a pixel count denoting size of rectangle in each direction from center.

inetsee 4y ago

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.

deleted 4y ago

[deleted]

hhh 4y ago

I have models in production that currently monitor ~400 cameras with an addition of 2-3 cameras/month. If it were cheap enough, it would be useful for our use case (Quality Control). We generally pull from cameras roughly 6400 pixels per region of interest, of which one instance may have 4-30 RoIs across N cameras.

71a54xd 4y ago
Curious where I could learn more about models like this / potentially see some open code outlining tooling / infra required as well?
- hhh 4y ago
  Not sure about open information about the models, but from tooling/infra we are running k8s w/ in-house API for image acquisition. Features are defined as x,y coordinates denoting center of a feature, with a pixel count denoting size of rectangle in each direction from center.