Datasets:
Tasks:
Image Classification
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
1K - 10K
License:
File size: 3,336 Bytes
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pretty_name: harmful-contents
tags:
- image-classification
- multi-label-classification
- computer-vision
- content-moderation
task_categories:
- image-classification
language:
- en
size_categories:
- 1K<n<10K
annotations_creators:
- expert-generated
source_datasets:
- original
license: other
license_name: research-and-non-commercial-use
license_link: https://huggingface.co/datasets/onullusoy/harmful-contents
---
# Harmful-Contents Dataset
A multi-label image dataset for harmful-content classification across eight PEGI-aligned categories.
The dataset consists of 5,153 rights-cleared images, split into train/validation/test sets and annotated with both binary labels and mask fields for controlled negative sampling.
---
## Dataset Structure
```
Harmful-Contents/
csv/
train.csv
val.csv
test.csv
data/
train/*.jpg
val/*.jpg
test/*.jpg
```
Each CSV contains:
```
name,
alcohol,drugs,weapons,gambling,nudity,sexy,smoking,violence,
mask_alcohol,mask_drugs,mask_weapons,mask_gambling,
mask_nudity,mask_sexy,mask_smoking,mask_violence
```
Images are stored in `data/{train,val,test}/` and referenced by name.
---
## Categories
| Category | Unsafe Examples | Safe Examples |
|---------|-----------------|---------------|
| **alcohol** | Alcohol bottles/glasses, alcohol brand logos | Empty glasses, non-alcoholic drinks |
| **drugs** | Cannabis, cocaine, pills, paraphernalia | OTC medication, neutral plants |
| **weapons** | Firearms, combat/attack knives, explosives | Kitchen knives, fruit knives, toy props |
| **gambling** | Casinos, slot machines, gambling chips/coins | Money, clovers, normal playing cards |
| **nudity** | Nudity, explicit sexual acts, pornography | Non-explicit partially clothed persons |
| **sexy** | Lingerie/underwear, sexualized posing | Sportswear, non-sexual clothing |
| **smoking** | Cigarettes, cigars, active smoking | Cigarette-like objects, steam/steam unrelated to smoking |
| **violence** | Blood, fighting, visible injury, aggression | Red liquids, non-violent crowds, hugging |
---
## Base Source (SIMAS)
The dataset is built using the **SIMAS** collection (*Spam Images for Malicious Annotation Set*) as the primary seed:
https://zenodo.org/records/15423637
Additional rights-cleared images were added to improve class balance, yielding the final 5,153-image dataset described in the associated thesis.
---
## Loading With Hugging Face `datasets`
```python
from datasets import load_dataset, Image
data_files = {
"train": "csv/train.csv",
"validation": "csv/val.csv",
"test": "csv/test.csv",
}
ds = load_dataset("csv", data_files=data_files)
def add_path(example, split):
return {"image_path": f"data/{split}/{example['name']}"}
for split in ["train", "validation", "test"]:
ds[split] = ds[split].map(lambda x, idx, s=split: add_path(x, s), with_indices=True)
ds[split] = ds[split].cast_column("image_path", Image())
```
---
## License
Images are rights-cleared for **research and non-commercial use**.
Commercial usage requires independent rights verification.
---
## Citation
If you use this dataset, please cite:
**Ulusoy, O.**
*Evaluating and Fine-Tuning Vision Models for Keyword-Driven Content Filtering.*
Bachelor Thesis, Flensburg University of Applied Sciences, 2025.
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