---
pretty_name: 'Enhanced Parquet Edition: IMD2020: A Large-Scale Annotated Dataset Tailored
  for Detecting Manipulated Images'
language:
- en
tags:
- parquet
- image
- image-forgery
- image-manipulation-detection
size_categories:
- 1K<n<10K
task_categories:
- image-classification
- image-segmentation
dataset_info:
- config_name: imd2020
  features:
  - name: image
    dtype: image
  - name: mask
    dtype: image
  - name: sample_id
    dtype: string
  - name: label
    dtype: int64
  - name: manipulation
    dtype: string
  - name: source_split
    dtype: string
  - name: filename_source_id
    dtype: string
  - name: source_image_path
    dtype: string
  - name: source_mask_path
    dtype: string
  - name: width
    dtype: int64
  - name: height
    dtype: int64
  - name: has_mask
    dtype: bool
  splits:
  - name: full
    num_examples: 2424
configs:
- config_name: imd2020
  default: true
  data_files:
  - split: full
    path:
    - imd2020/parquet/full-00000-of-00008.parquet
    - imd2020/parquet/full-00001-of-00008.parquet
    - imd2020/parquet/full-00002-of-00008.parquet
    - imd2020/parquet/full-00003-of-00008.parquet
    - imd2020/parquet/full-00004-of-00008.parquet
    - imd2020/parquet/full-00005-of-00008.parquet
    - imd2020/parquet/full-00006-of-00008.parquet
    - imd2020/parquet/full-00007-of-00008.parquet
---

# Enhanced Parquet Edition: IMD2020: A Large-Scale Annotated Dataset Tailored for Detecting Manipulated Images

This repository packages the IMD2020 archives distributed by [ForgeryVCR](https://huggingface.co/datasets/ForgeryVCR-Team/ForgeryVCR) into a Hugging Face Parquet configuration. It contains **2,424 images** (414 real and 2,010 tampered), with image bytes, supplied masks, and per-sample metadata embedded in Parquet.

The source archives are the ForgeryVCR 832-size preprocessed release under `datasets/train/rl`. The `full` split contains all supplied samples and introduces no new train/test partition.

## Subsets

| Config | Split | Rows | Image size | Pixel masks | Parquet files |
| --- | --- | ---: | --- | --- | ---: |
| `imd2020` | `full` | 2,424 | 832 × 832 | Tampered images | 8 |

## Columns

- `image`: the image from the supplied archive, decoded with the Hugging Face `Image` feature.
- `mask`: the supplied grayscale annotation; white marks edited regions and black marks background. Intermediate grayscale values are preserved. Real images have a null mask.
- `label`: image-level authenticity label, **0 = real, 1 = fake**.
- `manipulation`: `real` or `tampered`.
- `sample_id`, `source_image_path`: the image path relative to the extracted release directory.
- `source_split`: the upstream ForgeryVCR directory, `train/rl`.
- `filename_source_id`: the original filename stem.
- `source_mask_path`: the mask path relative to the extracted release directory; null for real images.
- `width`, `height`: supplied image dimensions in pixels.
- `has_mask`: whether a pixel annotation is supplied.

## Metadata Files

Each configuration includes `stats.json` with sample and label counts, image dimensions, mask statistics, and Parquet shard paths and sizes.

The root `inventory.json` collects these statistics and records the total row count, shard count, and encoded byte sizes. `provenance/` retains the supplied sample listings and bounding-box annotations.

## Citation

If you reference IMD2020, please cite the [original paper](https://doi.org/10.1109/WACVW50321.2020.9096940):

```bibtex
@inproceedings{Novozamsky_2020_WACV,
  author={Novozamsky, Adam and Mahdian, Babak and Saic, Stanislav},
  title={IMD2020: A Large-Scale Annotated Dataset Tailored for Detecting Manipulated Images},
  booktitle={2020 IEEE Winter Applications of Computer Vision Workshops (WACVW)},
  pages={71--80},
  year={2020},
  doi={10.1109/WACVW50321.2020.9096940}
}
```

## Dataset Export

This Parquet edition reorganizes the [ForgeryVCR IMD2020 release](https://huggingface.co/datasets/ForgeryVCR-Team/ForgeryVCR/tree/main/datasets/train/rl) and adds per-sample metadata. Supplied image and mask bytes are preserved. Please also reference this dataset repository when using the packaged version.

```bibtex
@misc{thanejoss_imd2020_2026,
  author={{ThaneJoss}},
  title={{IMD2020}},
  year={2026},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/ThaneJoss/IMD2020},
  note={Dataset available on Hugging Face}
}
```