LOLv2 Real — Low light images
Visual dataset specialized in the improvement of images taken in low light, intended for computer vision research.
Description
LoLv2 Real is an extended version of the famous LOL dataset, designed to evaluate and train algorithms for improving images captured in low light. It includes real and complex scenes to test the performance of the models in difficult conditions. This dataset is a recognized benchmark in the computer vision community.
What is this dataset for?
- Testing the robustness of image editing algorithms
- Train models for restoration or visual improvement (low-light enhancement)
- Establishing a standard benchmark for vision research
Can it be enriched or improved?
Yes. The dataset can be extended with images taken in other contexts (external, multilingual, in motion). Annotations such as light conditions or shooting metadata can also be added. Pre-trained models can be used to create an automatically annotated version (e.g. noise masks).
🔎 In summary
🧠 Recommended for
- Vision researchers
- Retouching algorithm developers
- Image processing students
🔧 Compatible tools
- OpenCV
- PyTorch
- TensorFlow
- FastAI
- ImageEnhance
💡 Tip
To maximize performance, use the original version of the dataset coupled with a perceptual loss (VGG) during training.
Frequently Asked Questions
Does the dataset contain pre/post-processing pairs?
Yes, each low-light image is accompanied by a corresponding version under normal conditions for comparison.
Is that enough to train a model from start to finish?
Yes, for lightweight models or pre-training. For deep networks, pre-training or data augmentation is recommended.
Can this dataset be used for commercial use?
Yes, the Apache 2.0 license allows free use, including commercial use, as long as the license conditions are met.
