Hardware

My experience

I tested many different hardware for different computer vision applications in area of IoT and Robotics

How to upgrade Raspberry Pi 4 EEPROM boot recovery; Released 2020-09-14; to install and boot from USB 3 (SSD)

Raspberry pi 3
Raspberry pi 4
Intel® Neural Compute Stick 2
- Intel® Distribution of OpenVINO™ Toolkit
- I attached to Raspberry pi 4 by USB 3 and work very well for many deep learning models
Google Coral
- I attached to Raspberry pi 4 by USB 3 and work very well for TensorFlow models
- Why TensorFlow lite on Edge: Lightweight, low-latency, Privacy, improved power consumption, efficient model ready to used
NVIDIA Jetson Nano
- I test Multi-Class Multi-Object Multi-Camera Tracking (MCMOMCT) under heavy workloads can perform up to 30 minutes
NVIDIA JETSON AGX XAVIER
- The best hardware
- I attended in may conferences and summits in area of Hardware for deep learning such as:
  - - - AI Hardware Europe Summit (July 2020)
      - The Edge AI & Brain Inspired Computing (November 2020)
      - Apache TVM And Deep Learning Compilation Conference (December 2020)
      - RISC-V Summit (December 2020)
OpenCV AI Kit

I worked with many different cameras such as:

camera calibration is important
Quantum efficiency [%] (spectral response)
Sensor size [inches or mm] and pixel size [micro meter]
Dynamic Range [dB]
Image noise and signal to noise ratio (SNR), PSNR, SSIM, : greater SNR yields better contrast and clarity, as well as improved low light performance
inter face, cable length in m, bandwidth max in MB/s , multi camera, cable costs, real time, plug and play
- - firewire, 4.5 , 64, *, *, **, **
  - gige, 100, 100, **, **, *, *
  - usb, 8, 350, *, *, **, **
  - link, 10, 850, -, -, **, -
  - usb-c, 10, 40 GB,,,,
distortions, scaling factors, quality is important, calculate minimum sensor resolution *, determine your sensor size, focal length,
- - sensor resolution= image resolution = 2 * ( field of view (FOV) / smallest feature )
some online tools: baslerweb.com, edmundoptics.com, flir.com
to sum up
- use USB-C camera. it will help you in the future upgrades in hardware and easy to use with less issues
- find your best trade-off between WD and FOV
- sometimes you cannot have everything in life!
- your lens aperture (f/#) is your friend, use it!
- a larger DOF requires a larger f/#
- lens performance curves are the ultimate documentation to read when selecting a lens
- understanding them properly requires good knowledge in optics, but it totally worth it.