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... | fake_00020.jpg |
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End of preview. Expand in Data Studio
sowaiba01-deepfake-fake
Mirror of the exact bmcore v24 holdout subset. Source: Sowaiba01/Deepfake.
All 5,426 local fake basenames match the public fake/ subset. Face swaps remain semisynthetic.
Contains 5426 semisynthetic image files. This mirror repackages the media; it does not grant additional rights.
Source revision reviewed: d8b189507fc026b3e0c794a06c318cb13d0c8743.
Original source card
license: mit task_categories: - image-classification language: - en tags: - deepfake - face-swap - detection - computer-vision - insightface size_categories: - 10K<n<100K
DeepGuard Deepfake Dataset
A paired deepfake dataset for training and benchmarking deepfake detection models. Generated as part of the DeepGuard AI Project (2026).
📥 2,301+ all-time downloads
Dataset Statistics
- Fake images: 5426 (face-swapped using InsightFace inswapper_128)
- Real images: 5426 (original paired faces)
- Total: 10852 images
- Format: JPEG, high quality (95%)
- Generation method: InsightFace inswapper_128 (ONNX runtime)
Why This Dataset is Unique
- Paired structure: Every fake has a matching real image of the same target person
- Modern method: inswapper_128 powers most 2024-2026 real-world deepfake apps
- Traceable metadata: Source identity, target face, and method per image
- Open access: No sign-up required, instant
load_dataset()access
Quick Start
from datasets import load_dataset
ds = load_dataset('Sowaiba01/Deepfake')
Detection Model
Trained EfficientNet-B4 detection model also available:
from huggingface_hub import hf_hub_download
model_path = hf_hub_download('Sowaiba01/deepguard-ai', 'efficientnet_b4_deepguard.pth')
Validation accuracy: 91.54% on 140K Real & Fake Faces dataset.
Citation
@dataset{deepguard2026,
author = {Arshad, Sowaiba},
title = {DeepGuard Deepfake Dataset},
year = {2026},
url = {https://huggingface.co/datasets/Sowaiba01/Deepfake}
}
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