There are the two models used in Low-light Dataset Project.
The results of the dataset project are uploaded on the AI-Hub
Each folder describe their code, pretrained model and results.
The final low-light result dataset consists of 2 million images.
Train : Valid : Test = 8 : 1 : 1
Object Detection part used Scale-Aware Trident Networks for Object Detection paper.
The original code is from TridentNet detectron2 Github
Instance Segmentation part used PointRend: Image Segmentation as Rendering paper.
The original code is from PointRend detectron2 Github
This code is implemented with Python 3.6 (Anaconda)
Python == 3.6
CUDA >= 11.1
torch == 1.11.0
opencv-python
scikit-image
detectron2