The AIY Vision Kit is a $45 add-on board that attaches to a Raspberry Pi Zero with a Pi 2 camera. The board includes a Vision Processing Unit (VPU) chip that runs Tensor Flow image processing graphs super efficiently. The kit comes with a bunch of examples out of the box, but to actually see what the camera see’s you need to plug the HDMI into a monitor. That’s not very useful when you want to put your battery powered kit in a remote location. And while it is nice that the rig does not require any Internet connectivity, that misses out on a lot of the fun applications.
Vision Bonnet
The Bonnet is just a small Pi Hat that attaches to the Pi Zero GPIO header. As one of the Googlers on the project was nice enough to explain, the Vision Bonnet reads directly from the Pi Camera via the standard Pi camera flex cable that passes through it. This means your other process have full access to the Pi Camera while it is running your code. It also means it does not use use any of the Pi’s resources other than what is needed for control signaling and the overhead to transfer the TensorFlow graph (more on that below), which is good because any kind of image processing can quickly exceed the Pi Zero’s single-core 1GHz ARM. Note that you do need something to initialize the camera since the Bonnet is just passively listening and can’t turn it on.But that’s not all – the bonnet itself also has its own Micro Controller Unit (MCU) that helps to offload the Kit’s push button with RGB LED and Piezo buzzer while leaving room for an extra 4 GPIO headers, a button, and some onboard LEDs.
The main feature of the board is an Intel® Movidius™ Myriad 2 MA2450 vision processing unit (VPU) chip. This is the magic that does all the vision processing heavy lifting . The VPU has hardware acceleration that runs neural network graphs at low power.
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