Hacker News Reader

Comment by brittohalloran | Hacker News Reader

The one new looking item is the VisionBonnet (with a low power Intel Movidius chip [1]). I've been pounding away on a low power / low cost NN vision device and now in the last two days we got Amazon DeepLens and this Google AIY Vision kit. Exciting and frustrating at the same time.

[1] https://www.movidius.com/solutions/vision-processing-unit

View on HN

I'll go with exciting. I'm looking at doing some computer vision (at least background segmentation for motion detection) as part of a security camera NVR project. I was eyeing the Hexagon DSP 680 included in the newest Qualcomm SoCs but couldn't find a cheap SBC that included it. At first glance, the VisionBonnet seems to do similar things as part of a $45 kit. As a bonus, they say it's supported by TensorFlow. That will be helpful if I ever actually get into machine learning...

On second glance, I think it's a pretty different device than the Hexagon DSP 680 I mentioned.

For one thing, this board in particular apparently has a direct connection to the camera. I'm not sure if you can do anything but live video from the directly-connected camera (in my case, I want prerecorded video / video from IP cameras). Maybe it can but it's not immediately obvious anyway.

The $75 "Movidius Neural Compute Stick" uses the same chip and does everything via USB so that's more promising. But it's a binary-only API that's totally focused on neural networks (and only available for Ubuntu/x86_64 and Raspbian/arm7). In contrast, I believe you can easily send Hexagon arbitrary code. Its assembly format is documented and upstream llvm appears to support it. So if I want to do background subtraction via more old-school approaches, the Hexagon is probably useful where the Movidius stuff is not. And I have yet to learn anything about neural networks so that's a significant factor for me at least.

Really neat hardware but I wish it were more open.

If I was going to do some embedded image processing I would choose a Tegra. You can get a Shield TV for not too much money, and although I haven't done it myself it looks pretty hackable with both Android and Ubuntu (and if you don't want to hack it you can just buy the devkit). CUDA is a decent toolkit and of course NVIDIA's support for neural networks is by far better than anyone else's.

Reply on news.ycombinator.com