# DUET_v1 — Image Dataset **Project:** DUET_v1 **Course:** SC4001 — Nanyang Technological University **Academic Year:** 2026/27 **Team:** Group 66 **Organization:** [DUET-Bench](https://huggingface.co/DUET-Bench) ## Overview This repository hosts curated image datasets used in **DUET_v1**, a project developed by Group 66 for NTU SC4001. The datasets support the development and evaluation of image authenticity detection methods, with an emphasis on reproducible data preparation, structured storage, and sample-level traceability. ## Dataset Collection ### NTIRE / Fake The `ntire_fake` configuration contains **50,000 images labeled as fake**, stored under `NTIRE/Fake/`. The images are organized into self-contained Parquet shards, with the original JPEG bytes embedded in the `image` column. All selected images satisfy the following resolution requirements: - Width > 512 pixels - Height > 512 pixels After applying the dimension filter, deterministic sample selection preserves the original ordering of each source `labels.csv`. **Dataset composition:** | Source Shard | Number of Images | |---|---:| | shard_5 | 13,024 | | shard_1 | 23,732 | | shard_2 | 13,244 | | **Total** | **50,000** | ## Data Integrity and Provenance To support reproducibility and data verification, the repository includes: - `NTIRE/Fake/selection_manifest.csv` — Records sample-level provenance and SHA-256 hashes. - `NTIRE/Fake/summary.json` — Documents dataset construction and verification details. ## Usage The dataset can be accessed through the Hugging Face Datasets library. ```python from datasets import load_dataset dataset = load_dataset( "DUET-Bench/Dataset", "ntire_fake", split="train" ) ``` **Repository:** [DUET-Bench/Dataset](https://huggingface.co/datasets/DUET-Bench/Dataset) ## Usage and Licensing This repository is intended for research and educational use. Before redistributing images or using the dataset beyond the permitted scope, users should verify the licenses, attribution requirements, and usage restrictions of the original source datasets. ## Project For more information about the DUET_v1 project and associated resources, visit the [DUET-Bench Hugging Face organization](https://huggingface.co/DUET-Bench).