4 ms·

You might want to investigate the Movidius Neural Compute stick (which you can use with a RPi), or the Nvidia Jetson Nano, which has a lot more oomph.

8fingerlouie 6y ago
I use the Movidius NCS and it's pretty much the optimal solution for light OpenCV work. It draws very little power, but as the Pi itself is powered by USB, don't expect to run much else off of USB on it. I use it in the exact same scenario, a Raspberry Pi (Zero W) with a camera with motion detection and notifications on movement, my implementation may be specific though. Each of my Raspberry Pi cameras runs motion (https://motion-project.github.io/index.html https://motion-project.github.io/index.html), and recorded files are stored on a NFS share. Each camera has it's own directory within this share (or rather each camera has it's own share within a parent directory), and the server then runs a python script that monitors for changed/added files, and runs object detection on the newly created/changed files. If a person is detected in the file, it then proceeds to create a "screenshot" of the frame with the most/largest bounding box, and sends a notification through Pushover.net including the screenshot with bounding box. There implementation is not quite as simple as described here, i.e. i use a "notification service" listening on MQTT for sending pushover notifications, but the gist of it is described above. Edit: I should probably clarify that my cameras are based on Raspberry Pi Zero W. They have enough power to run motion at 720p - at around 30fps. Not great, but good enough for most applications. I've since migrated most to Unifi Protect instead. A little higher hardware cost, a lot better quality :)
- dekhn 6y ago
  I played with the Movidius stick for a bit but it didn't seem like Intel was committed to Movidius tech in the long term. So I'm curious what the "next" thing will be.
  - 8fingerlouie 6y ago
    They were/are committed enough to put out a second version, and I guess these things are still pretty much a niche market, I mean they specifically target embedded applications. I think the next thing, which is already happening, is embedded “AI” processors on SOCs. Apple is doing it with their A12 processors, and it’s probably only a question of time before you can purchase “general purpose” ARM chips with “AI” capabilities.

8fingerlouie 6y ago

I use the Movidius NCS and it's pretty much the optimal solution for light OpenCV work. It draws very little power, but as the Pi itself is powered by USB, don't expect to run much else off of USB on it. I use it in the exact same scenario, a Raspberry Pi (Zero W) with a camera with motion detection and notifications on movement, my implementation may be specific though. Each of my Raspberry Pi cameras runs motion (https://motion-project.github.io/index.html https://motion-project.github.io/index.html), and recorded files are stored on a NFS share. Each camera has it's own directory within this share (or rather each camera has it's own share within a parent directory), and the server then runs a python script that monitors for changed/added files, and runs object detection on the newly created/changed files. If a person is detected in the file, it then proceeds to create a "screenshot" of the frame with the most/largest bounding box, and sends a notification through Pushover.net including the screenshot with bounding box. There implementation is not quite as simple as described here, i.e. i use a "notification service" listening on MQTT for sending pushover notifications, but the gist of it is described above. Edit: I should probably clarify that my cameras are based on Raspberry Pi Zero W. They have enough power to run motion at 720p - at around 30fps. Not great, but good enough for most applications. I've since migrated most to Unifi Protect instead. A little higher hardware cost, a lot better quality :)

dekhn 6y ago
I played with the Movidius stick for a bit but it didn't seem like Intel was committed to Movidius tech in the long term. So I'm curious what the "next" thing will be.
- 8fingerlouie 6y ago
  They were/are committed enough to put out a second version, and I guess these things are still pretty much a niche market, I mean they specifically target embedded applications. I think the next thing, which is already happening, is embedded “AI” processors on SOCs. Apple is doing it with their A12 processors, and it’s probably only a question of time before you can purchase “general purpose” ARM chips with “AI” capabilities.