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)

  1. update Raspberry Pi 4 EEPROM boot recovery

  2. install Ubuntu 20 on SSD

  3. change the config.txt and add "program_usb_boot_mode=1" at the end of file

  4. remove and micro sd card and boot from ssd

Smart AI IoT, Robotic, 3D SLAM, AR, VR


I worked with many different hardware such as

  • 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


    • The best hardware

    • I attended in may conferences and summits in area of Hardware for deep learning such as:

  • OpenCV AI Kit


I worked with many different cameras such as:

  • Camera Module V1

  • Camera Module V2

  • Camera Module V2.1

  • multispectral camera

  • USB webcam

  • IP camera

  • high resolution camera > 8K

  • depth camera

  • stereo camera

What is important?

  • 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.

Scaled-YOLOv4:scaling model based on hardware