Vision Tachometer

If you have any questions, please submit issues or email me: enpeicv@outlook.com, have fun with it!

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1.Demo

demo.mp4

2.Usage

• Clone the project

Python

• Create a python=3.8 environment with conda or venv.

• Install packages like opencv and numpy.

• Download 1.video_tachometer_demo.mp4 from media files.

• Move 1.video_tachometer_demo.mp4 to the media directory of the project.

• # video_path: filename for input video | camera index for stream
  # snap_path: reference snapshot
  # output_path: recorded video path
  
  # example
  python demo.py --video_path media/1.video_tachometer_demo.mp4 --snap_path media/snap.png --output_path result.mp4

• It will open three windows (raw video, matched, graph).

  

C++

The overall process is identical to Python's.

• Build and run:

• # build
  cmake -S . -B build
  cmake --build build
  
  # run 
  ./build/HelloWorld <video_file> <reference_image>

3.References

• High Speed Rotation Estimation with Dynamic Vision Sensors
• https://ieeexplore.ieee.org/document/8443343
• https://kar.kent.ac.uk/77844/1/1570319863_I2MTC2017_speed%20measurement_final.pdf
• https://www.mdpi.com/1424-8220/20/24/7314
• https://www.semanticscholar.org/reader/d5cc5ae8e75ef87ac8824ae13c7a4d3d11e92be8
• https://doi.org/10.1364/OE.24.013375
• https://linkinghub.elsevier.com/retrieve/pii/S088832701730537X