Seeking Some Special Roadtesters for the UltraZed-EV

The FPGA and its carrier board are pretty amazing, but I suspect that unless anyone has already experience with the technology, it may require quite a bit of effort to learn how to properly use it.

Not just Zynq experience, but extensive video processing on Zynq experience. I've some road test experience with Zynq and dabbled in the video side with the Zybo Z7, but definitely couldn't do this board justice. I suspect finding anyone to adequately road test this will be very tricky.

Looks like an interesting board.  I'd like to design a real-time PIV system someday, but no time right now.

So many projects........

Scott

I love the project. I tear up not having the experience to undertake such a project.

I have designed FMC daughter cards for Xilinx boards, and would enjoy embracing this opportunity to road test the UltraZed-EV.

Impressive, but unfortunately I have other priorities at the moment.

I think, I would be interested in something like this too...

As previous experience, I have these:

• Stereo Vision and LiDAR Powered Donkey Car - hardware accelerated stereo vision implemented on an Ultra96 board (based on Xilinx UltraScale+ ZU3EG)
• PYNQ-Z2 Dev Board: Python Productivity for Zynq - Review - road test of the PYNQ-Z2 board (based on a Zynq-7000 series SoC)

As a Road Test project, probably I would try some object detection using hardware accelerated BNN-s (Binary Neural Networks). The video input / outputs could either HDMI or network video streams (RTSP).

I would be interested in testing this board.It looks feature packed.

I would port PYNQ to this board if it's not already. I ported PYNQ to the ZC702:

Porting PYQN to ZC702

I have posted a couple of  similar projects:without AI.

FPGA camera lane detection with ZYNQ ZC702

https://www.hackster.io/dhq/fpga-camera-edge-detection-02dce2

Ideally I would use two video feeds to  implement an image captioning neural network (CNN+ LSTM). I see the carrier has HDMI in which is great.

I have an idea on how to do this on a SOC but I will probably need to use PYNQ  framework to speed up development.

This will make testing IP cores quite straightforward since I one would have to use Python to talk to them.

Then I would implement a video mixer with multiple cameras. Will use HLS  IP's in order to meet the free cores requirements.

The MIPI-CSI core is quite expensive. Word on the vine is that Xilinx plans to release it for free in the future Vivado versions.

so I would use either an HDMi video source, a USB camera which will necessitate Petalinux or use a custom FMC solution with multiple cameras.

.

As for AI I think one can either run the DPU V3 .One other option is to compile and use YoloV3 for object localization running on the PS

1. I am interested in road testing this board since I can provide a very unique and comprehensive review on this board, the reason being that I am working on thermal and hyperspectral imaging. Most of the other reviewers will never deviate from visible imaging due to its very different handling approaches and algorithms.
2. My project has been supported by various industries and companies, who want my research and application to reach a conclusive end. Hence, I can submit a detailed, comprehensive and extensive road test, which will have an on-site demonstration in real-world environments.
3. My research, if successful will significantly impact agriculture in India and even worldwide. I am looking to create a huge dataset, using various thermal cameras (AMG, MLX, FLIR, etc) and use CV/ML/AI and even NN (I am experimenting with various architectures and methods to get the best result) and then train the model on a portable SoM specifically meant for video processing. I have tried various devices and systems already, like the Jetson Nano but they are falling quite short of meeting my requirements in the budget I want to deliver the product at.
4. My project will also contain a UAV drone, which is currently being designed and will make proper use of video capture and processing features of this board. External pieces are COTS and will have optimum VCU utilization.

As far as my background is concerned, I have just recently joined the roadtest community, bagged my first road test as soon as I joined a few days back... My team has represented my country Internationally, in the AAS Cansat competition, sponsored by NASA securing a worldwide ranking of 34 last year. I have won National hackathons and competitions. Apart from all this, I have bagged hardware on hackster.io multiple times for my different ideas. I can provide any evidence/ photos for these projects and competitions if needed.

Hi Dishant,

I don't want to detract from your application, but I had a question:

For thermal imaging, and OpenCV, isn't even a low-end processor adequate? I've used a Flir chip with a BeagleBone Black (it is almost a decade old tech) and that was fast enough to run OpenCV performing some operations, at the maximum frames-per-sec I could pull out of the chip. The other parts you refer to (Panasonic, Melexis) wouldn't begin to warm up first-gen Pi. Using a combined FPGA+processor is quite different..

1. I have tried various devices and systems already, like the Jetson Nano but they are falling quite short of meeting my requirements in the budget I want to deliver the product at.

You do know the price difference between the Jetson Nano and this Xilinx part, right?