I need to choose hardware for an OpenCV project that I am working on currently. Space is limited hence I cannot use a full blown computer. The project specs are listed below:

  1. Using two USB 3.0 high speed Basler cameras running at 300 fps each (300 megs/sec each.) The video shot is between 1 to 1.5 seconds at a time.
  2. I am using the LBP (local binary patterns) OpenCV library to detect objects in the video.
  3. The video processing should be real-time or as close to real-time as possible - a lag of up to 2 seconds between the video end and result extraction is acceptable.
  4. The cameras are used for two different tasks, obtaining the angle of an object moving in parallel to a camera and its proximity to the cameras - hence the need for stereoscopic vision.
  5. To minimize the data quantity, basler offers me the ability to skip frames, which I have done. My project works if I only use every 4th frame. Hence I only need to process 225 frames at most. More optimization is possible by cutting the duration of the video to below 1 second.
  6. The hardware needs to support Linux - my OS of choice
  7. Ideally I would like the OS loaded from an SD card
  8. The hardware needs to have 2 USB 3.0 slots
  9. HDMI or VGA output is needed.
  10. The hardware should not be any bigger than 8" x 8" x 3"
  11. Internet via (RJ-45)
  12. Price should be around $500 - $1000
  13. Memory - ideally at least 4GB
  14. CUDA hardware acceleration or similar would be very nice
  15. Power - no restriction - city grid
  16. Needs to interface with a SSD drive as well

So far I have looked at an Intel NUC and a Nvidia JetsonTX2. Any other suggestions are greatly appreciated.

  • Hard to estimate the neccessary CPU/GPU performance without knowing the actual algorithm load. Do you know whether the OpenCV libraries you use have CUDA oder OpenCL implementations? RK3288-based systems like the wiki.radxa.com/Rock2 should meet your requirements, for example. – Philippos May 7 '19 at 13:43

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