Skip to content
/ FoHIS Public
forked from noahzn/FoHIS

Towards Simulating Foggy and Hazy Images and Evaluating their Authenticity

License

Notifications You must be signed in to change notification settings

LTTM/FoHIS

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

25 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

🌫️ FoHIS: Simulating Foggy and Hazy Images

🛠️ Instructions

Set your custom parameters in parameters.py, then use the function fog to generate foggy images. Inputs:

  • 🖼️ rgb path: Path to the input image
  • 🗺️ depth path: Path to the depth image
  • 💾 out path: Path to the output image
  • 💡 luminance reduction factor: Optional, controls how much the luminance is reduced (default: 0)
  • 🎨 saturation reduction factor: Optional, controls how much the saturation is reduced (default: 0)
  • 🌈 apply color scheme: Optional, if True applies a premade color scheme that enhances the fog effect (default: False)
  • 🌫️ min-depth: Optional, sets the minimum depth for the fog effect (default: 1)

To run as standalone code, use:

python fog.py --rgb <path> [--depth <path> [--out <path>] [--reduce-lum <value>] [--reduce-sat <value>] [--color-scheme] [--min-depth <value>]

🙏 Acknowledgements

This repository is a fork of the one made by Ning Zhang, Lin Zhang, and Zaixi Cheng for their paper Towards Simulating Foggy and Hazy Images and Evaluating their Authenticity. The original repository can be found here.

This specific fork was created by:

About

Towards Simulating Foggy and Hazy Images and Evaluating their Authenticity

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%