Datasetpublic

Bubu0320/NTIRE_LLE_2025

NTIRE 2025 Low Light Image Enhancement Challenge Dataset Overview The NTIRE 2025 dataset is crafted to benchmark low-light image enhancement algorithms, featuring a diverse set of challenging low-light conditions. It is structured to support both the development and evaluation phases of the challenge. Dataset Composition Training Set: 219 images with paired low-light inputs and corresponding ground truth images. Validation Set: 46 images provided… See the full description on the dataset page: https://huggingface.co/datasets/Bubu0320/NTIRE_LLE_2025.

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Dataset Card

license: apache-2.0 ---

NTIRE 2025 Low Light Image Enhancement Challenge Dataset

Overview

The NTIRE 2025 dataset is crafted to benchmark low-light image enhancement algorithms, featuring a diverse set of challenging low-light conditions. It is structured to support both the development and evaluation phases of the challenge.

Dataset Composition

—Training Set: 219 images with paired low-light inputs and corresponding ground truth images.
—Validation Set: 46 images provided as low-light inputs.
—Test Set: 30 images provided as low-light inputs.

Folder Structure

The dataset is organized as follows:

NTIRE2025/
  ├── train/ │
    └── samples/ # Paired samples for training
      │ ├── sample_001/ │
        │ ├── GT.jpg # Ground Truth image │
        │ └── Input.jpg # Low Light image │
      ├── sample_002/ │
        │ ├── GT.jpg │
        │ └── Input.jpg
      │ └── ...
  ├── val/
    │ └── samples/ # Samples for validation (low-light images only)
      │ ├── sample_001/
        │ │ └── Input.jpg
        │ └── ...
  └── test/
    └── samples/ # Samples for testing (low-light images only)
      ├── sample_001/
      │ └── Input.jpg
        └── ...

Data Source

The dataset is available via designated download links provided by the organizers. Participants can access the dataset using the provided Google Drive links or via Baidu WangPan (password: 2025). For more details on the challenge, please visit the NTIRE 2025 Challenge Page.

Code Samples for Data Loading

—For data loaders and preprocessing examples, see "loaddataloaders.py".
—For dataset loading and inspection examples, see "load_dataset.py".

Citation

If you use this dataset in your research, please cite the following paper:

bibtex

@article{codalab_competitions_JMLR,
  author  = {Adrien Pavao and Isabelle Guyon and Anne-Catherine Letournel and Dinh-Tuan Tran and Xavier Baro and Hugo Jair Escalante and Sergio Escalera and Tyler Thomas and Zhen Xu},
  title   = {CodaLab Competitions: An Open Source Platform to Organize Scientific Challenges},
  journal = {Journal of Machine Learning Research},
  year    = {2023},
  volume  = {24},
  number  = {198},
  pages   = {1--6},
  url     = {http://jmlr.org/papers/v24/21-1436.html}
}

Additionally, if you find the dataset card useful in your workflow, please consider citing the dataset card as follows:

@misc{NTIRE2025_dataset_card,
  author       = {Omar Khater},
  title        = {NTIRE 2025 Low Light Image Enhancement Challenge Dataset Card},
  howpublished = {\url{https://huggingface.co/datasets/okhater/NTIRE_LLE_2025}},
  year         = {2025},
  note         = {Dataset card curated for clarity and efficient access to the NTIRE 2025 challenge data}
}