This is a simulator that generates foggy, rainy, smoky and cloudy image over a clear remote sensing image.
- Accelerate speed when processing large images.
- Improve continuity of generated fog.
Run pip install -r requirements.txt.
Just put the images into the folder data/raw.
Besides prepare images, you should also prepare labels corresponding to every image in YOLO format, and put them into the folder data/labels.
Use command python simulate.py --foggy --light --medium --heavy. Parameters light / medium / heavy control the thickness
of the fog. Note that you should at least use one parameter, or there will be no output. Output images will be in the folder
data/foggy.
This method is modified from FoHIS.
Use command Python simulate.py --rainy. Output images will be in the folder data/rainy.
Use command python simulate.py --smoky --light --medium --heavy. The usage of the last three parameters is same to
that in generating foggy images. Output images will be in the folder data/smoky.
Use command Python simulate.py --cloudy. Output images will be in the folder data/cloudy.
From left to right is original image, image with light fog, image with medium fog and image with heavy fog
respectively.
From left to right is original image, image with light rain and image with heavy rain respectively.
The heavy rain simulation is not included in the code because it's not quite real.
From left to right is original image, image with light smoke, image with medium smoke and image with heavy smoke
respectively.
From left to right is original image, image with clouds. We demonstrate two examples here.
If you found this repository useful, please consider citing this repository:
@misc{Runou2023,
author = {Runou Yang},
title = {AdverseWeatherSimulation},
year = {2023},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/RicardooYoung/AdverseWeatherSimulation}},
}