hezhangsprinter/ID-CGAN
Image De-raining Using a Conditional Generative Adversarial Network
This project helps improve the clarity of images taken in rainy conditions, making them more suitable for automated analysis. You input a single image containing rain, and it outputs a de-rained version that looks much clearer and performs better with computer vision tasks like object detection or classification. This is ideal for computer vision engineers or researchers working with outdoor imagery.
265 stars. No commits in the last 6 months.
Use this if you need to process images captured in the rain and want to remove raindrops or streaks to improve the performance of downstream computer vision algorithms.
Not ideal if you're looking for a general-purpose photo editor to enhance image quality beyond rain removal, or if you need to process video footage rather than single images.
Stars
265
Forks
57
Language
Lua
License
—
Category
Last pushed
Nov 20, 2022
Commits (30d)
0
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