What if you're formatting your own SD cards for Raspberry Pi, and need control over the partition layout, filesystem, etc. Surely there are some best practices that this tool embodies, which one can follow to achieve the same level of robustness and performance?
They decided to use the silicon space for other things. The Pi5 CPU is powerful enough to decode most h264 streams in software. The Pi5 has an h265 hardware decoder.
You need active cooling if you want to extract all the performance out of it. The standard cooling kits sold by Raspberry Pi are neat and cheap though, so not a problem in my experience. They have two options: A case with a fan on top, and a small heatsink + fan combo. The fans run at variable speed, so generally pretty quiet.
It's interesting that the standard "K" (number of elements with a shared scale) is 32. That seems to imply that the neural network will somehow learn to group weights at those 32-element boundaries.
Does anybody understand how that works? I mean, what is the mechanism that naturally causes the model to group weight scales into those K-element clusters?
"Modulation can be turned off on alternate scans to identify velocity using unmodulated carrier frequency shift. This allows range and velocity to be found with just one radar set."
Yes, you must disable CPU frequency scaling in your BIOS if you're doing this kind of work (i.e. building cryptographic primitives that don't leak information via timing).
TL;DR:
The December 5th experiment was about proving to ourselves and our adversaries that we still understand how to build and validate nuclear weapons, despite the ban on testing.
Yes, this would definitely work, so long as the two cameras have sufficient overlap. If you were to use OpenCV's stitching code, then you could run the first few phases of that on your initial photo pair, which determine the camera angles, and then save those angles.
Then, for every video frame, you could skip the photo angle computation, and just run the imagine stitching logic. The stitching_detail code is very readable, and quite easy to hack for experimentation.
I'm convinced after the work I did on panoramas that one shouldn't need to involve user input. Maybe for very strange situations... but generally it shouldn't be necessary. This is especially true if you have access to the IMU on a phone, which helps constrain the potential angles of each of your images.
If your images are just a random bag of jpegs that came in from the cold, then it's harder for sure.