Jerry:
I have fine-tuned the Yolov3-tiny network to specialize solely in person detection using data from MS-COCO (the dataset used to train the pre-trained network) and the Caltech Pedestrian Dataset, which would hopefully increase the accuracy of the network for our use case. I verified that it performed better on the Caltech dataset compared to the pretrained network.
Since we’ve formally decided to support battery operations, I have also been researching into possible batteries for the system. At first I was considering USB power banks, and found that though this is possible, a large amount of equipment will be needed:
- USB power bank
- A way to convert the 5V USB output to a 12V 4.8mm x 2.1mm jack output
- A way to prevent the power bank from turning itself off under low current draw (!!)
- Courage to believe that the power bank won’t draw too much power while it’s being forced on
I breadboarded a circuit that kept one of my own power banks on, but later by chance I found a different battery that outputs 12V DC directly and is well-suited for powering low-powered things for a long time, so we decided to use that instead.
Next time, I will try to make the neural network run on the board.
Karthik:
I have been working on trying to interface with the GPIO pins on the Ultra96 Board. This will specifically become more useful as the parts we ordered start to come in. Therefore, because we don’t have all the parts, I am trying to interface with LEDs that are connected through the GPIO pins just as a proof of concept. To do this, I have been doing some installations of different board configuration files and been going through some Ultra96 startup guides to try and set up both Vivado and the Xilinx SDK on my laptop to use the GPIO pins. This has involved getting pin assignments from a third-party site. After that I started setting up both Vivado and the Xilinx SDK to use the proper pin assignments.
On top of this, I have been working with Nathan and Jerry to try and get an Archlinux system with the Deephi libraries that we needed for our project onto our board. Overall, I think we are pretty close to on schedule because after getting the OS on our board and the logitech webcam, we can now start to test the GPIO interfacing with the webcam.
Nathan:
I spent my week focusing on getting the Ultra96 functional with the Deephi demo IP. As the end result of this process involved pulling in Karthik and Jerry as well, I will detail it in more detail in the team section. Additionally, I worked on nailing down the specifics of our control and low power motion subsystem. The general system is as follows. We will use the Adafruit Feather Board platform (specifically their ARM M0+ based board, specialized for CircuitPython) to monitor the motion sensor with low power consumption. Upon detecting motion, it will send a signal over UART to the Ultra96 to wake it from deep sleep. This seems the lowest power way to economically monitor the device’s surroundings. The Feather Board will also control the servos and stepper motors of the control system, as Adafruit and the Arduino ecosystem have very robust software tools for precisely that purpose, and there is no effective power difference compared to using the Ultra96 itself, despite the latter’s greater complexity.
Also, I forgot to mention this in the last post, but I significantly improved the website before last week’s blog post, as some visitors may have noticed, and even included one-click links to our presentations (as opposed to embedding them in a post).
Team:
In addition to the contributions above, our team had an epic this Saturday to rival the Iliad. Nathan started by trying to get some Deephi demos working on the board. Nominally, this involved downloading a Xilinx board image and transferring over some test programs, a simple feat in theory. However, upon trying to boot that board image, nothing was happening. We tried reflashing the original Linux distribution, which works just fine, and also validated the flashing utility, but the Deephi boot image just wouldn’t work.
Eventually, we were able to track down a UART to USB tool, which we could use to debug the boot process instead of flying blind. However, what we saw was the following message, over and over again:
Xilinx Zynq MP First Stage Boot Loader Release 2018.2 Dec 10 2018 – 14:03:11 Reset Mode : System Reset Platform: Silicon (4.0), Running on A53-0 (64-bit) Processor, Device Name: XCZUG SD0 Boot Mode Non authenticated Bitstream download to start now PL Configuration done successfully
We tried various solutions, including booting from a USB (got nothing over debug) and even modifying the binary file, but nothing worked.
Eventually, however, we stumbled upon the true source of the problem. Apparently, the lab power supply can only provide 0.5A, which was just enough to boot into Linux, but was insufficient to power the boot process for the Deephi. However, by increasing the voltage, we were able to provide enough power to get to the desktop, but not enough to run the demos. We will receive a new power supply this week to fix this problem.
Edit 3/2: Corrected typo “logic” to “Linux”.