README.md

---
base_model:
- black-forest-labs/FLUX.2-klein-base-9B
datasets:
- ControlLight/Light100K
language:
- en
- zh
license: apache-2.0
library_name: diffusers
pipeline_tag: image-to-image
---

<h1>Original Repository: <a href="https://huggingface.co/ControlLight/ControlLight" target="_blank">ControlLight/ControlLight</a></h1>

<div align="center">

# ControlLight: Towards Controllable, Consistent, and Generalizable Low-Light Enhancement

[![arXiv](https://img.shields.io/badge/arXiv-2605.25569-b31b1b.svg)](https://arxiv.org/abs/2605.25569)
[![Project Page](https://img.shields.io/badge/Project-Page-blue)](https://yfyang007.github.io/ControlLight/)
[![GitHub Code](https://img.shields.io/badge/GitHub-Code-black)](https://github.com/yfyang007/ControlLight)
[![Light100K](https://img.shields.io/badge/Light100K-Dataset-green)](https://huggingface.co/datasets/ControlLight/Light100K)
[![Hugging Face](https://img.shields.io/badge/HuggingFace-Model-yellow)](https://huggingface.co/ControlLight/ControlLight)

</div>

ControlLight is presented in the paper **[ControlLight: Towards Controllable, Consistent, and Generalizable Low-Light Enhancement](https://huggingface.co/papers/2605.25569)**.

ControlLight is a controllable low-light enhancement model built on top of **FLUX.2 [klein] 9B**. It is trained as a LoRA for continuous illumination enhancement, enabling users to adjust enhancement strength with a controllable parameter `alpha`. The model is designed to enhance low-light images while preserving the original scene structure, visual content, and fine-grained details.

## 🔥🔥🔥 News!!

- **May 2026:** 👋 We release **ControlLight**, its model weights, inference and training code.
- **May 2026:** 👋 We release **Light100K**, a continuous low-light enhancement dataset for controllable illumination learning.

## ⚡️ Model Usage

### Installation

This project currently relies on the patched local `diffusers/` checkout from the ControlLight repository.

```bash
git clone https://github.com/yfyang007/ControlLight.git
cd ControlLight

conda create -n controlight python=3.12 -y
conda activate controlight

python -m pip install --upgrade pip
python -m pip install -e diffusers
python -m pip install -r requirements.txt
python -m pip install -e .
```

You can verify the environment with:

```bash
bash scripts/predict.sh --help
bash scripts/demo.sh --help
bash -lc 'source scripts/project_env.sh; python run.py --help >/dev/null'
```

### Inference with ControlLight

```bash
bash scripts/predict.sh predict-image \
  --input /path/to/input.jpg \
  --output /path/to/output.png \
  --model-path /path/to/FLUX.2-klein-base-9B \
  --lora-path /path/to/controllight.safetensors \
  --alpha 0.50 \
  --num-inference-steps 20 \
  --guidance-scale 1.0 \
  --seed 42 \
  --device cuda \
  --torch-dtype bfloat16
```

### CLI Quick Start

```bash
bash scripts/predict.sh predict-four \
  --input /path/to/images \
  --output /path/to/out_four \
  --model-path /path/to/FLUX.2-klein-base-9B \
  --lora-path /path/to/controllight.safetensors \
  --num-inference-steps 20 \
  --seed 42 \
  --device cuda \
  --torch-dtype bfloat16
```

### Recommended Inference Config

- **Device:** `cuda`
- **Torch dtype:** `bfloat16`
- **Inference steps:** `20`
- **Guidance scale:** `1.0`
- **Recommended seed:** `42`
- **Enhancement strength:** `alpha` in `[0, 1]`, where larger values produce stronger low-light enhancement.

### Example Settings

| Task | Setting |
| --- | --- |
| Mild Low-light Enhancement | `alpha=0.25` |
| Medium Low-light Enhancement | `alpha=0.50` |
| Strong Low-light Enhancement | `alpha=0.75` |
| Full Low-light Enhancement | `alpha=1.00` |
| Custom Enhancement Sweep | `--alphas 0.20,0.40,0.60,0.80` |

## Additional Resources

- **Project Page:** [ControlLight Project Page](https://yfyang007.github.io/ControlLight/)
- **GitHub Repository:** [yfyang007/ControlLight](https://github.com/yfyang007/ControlLight)
- **Model:** [ControlLight/ControlLight](https://huggingface.co/ControlLight/ControlLight)
- **Dataset:** [ControlLight/Light100K](https://huggingface.co/datasets/ControlLight/Light100K)
- **Base Model:** [black-forest-labs/FLUX.2-klein-base-9B](https://huggingface.co/black-forest-labs/FLUX.2-klein-base-9B)

## License and Disclaimer

The code of ControlLight is intended to be released under the Apache License 2.0.

ControlLight is built on top of **FLUX.2 [klein] 9B** and uses third-party components, datasets, and model assets. All underlying base models and third-party components remain governed by their original licenses and terms. Users must comply with all applicable upstream licenses when using this project.

## Citation

If you find ControlLight useful in your research, please star and cite:

```bibtex
@misc{yang2026controllightcontrollableconsistentgeneralizable,
      title={ControlLight: Towards Controllable, Consistent, and Generalizable Low-Light Enhancement}, 
      author={Yufeng Yang and Jianzhuang Liu and Jisheng Chu and Yuqi Peng and Xianfang Zeng and Jiancheng Huang and Shifeng Chen},
      year={2026},
      eprint={2605.25569},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2605.25569}, 
}
```