Datasets:

DUET-Bench
/

Dataset

# 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).

	# 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).