Datasets:

ersace
/

IITU_Safety-Helmet_Dataset_v1.0_Demo

annotations_creators:
  - expert-generated
language_creators:
  - crowdsourced
license: cc-by-4.0
multilinguality: monolingual
language:
  - en
size_categories:
  - 1K<n<10K
tasks:
  - object-detection
  - classification
dataset_type: image-folder
tags:
  - object-detection
  - classification
  - safety-helmet
  - hardhat-detection
  - construction-safety
  - drone-imagery
  - night-vision
  - computer-vision
  - yolo-format
  - color-classification

IITU Safety-Helmet Dataset v1.0 Demo

Overview:

This dataset contains annotated images of safety helmets captured both by drone and at ground level, designed for helmet detection and color classification tasks in computer vision.

This is the DEMO version of the dataset, now it contains only 14 images and annotations.

📖 Dataset Summary

This dataset contains 1,664 images annotated for safety-helmet detection and color classification.

6,473 helmet instances
Captured by drone (3–5 m, 10–15 m; angles 0°, 45°, 90°) and at ground level
Lighting conditions: daytime (clear) and night (lamp light)

📂 Dataset Structure

iitu-safety-helmet/
├── data
│   ├── frames_daytime
│   │   ├── horizontal_0deg
│   │   │   ├── 3-5_meters
│   │   │   │   ├── images/
│   │   │   │   └── annotations/
│   │   │   └── 10-15_meters
│   │   │       ├── images/
│   │   │       └── annotations/
│   │   ├── tilted_45deg
│   │   └── vertical_90deg
│   └── frames_night_time
│       ├── horizontal_0deg
│       │   ├── images/
│       │   └── annotations/
│       ├── tilted_45deg
│       └── vertical_90deg
├── classes.txt
└── README.md

Annotation Format:

Each .txt annotation file corresponds to one image and contains one line per helmet.
Line format (YOLO v5-style with high-precision floats): "class_id", "x_center", "y_center", "width", "height".
All five values are space-separated; the four geometry values are normalized to [0, 1] and may have up to 16 decimal places.

Classes:

0 blue helmet
1 green helmet
2 red helmet
3 white helmet
4 yellow helmet

Paper / Citation
Bektemyssova, G.; Bykov, A.; Keresh, A.; Yergazy, Y.; Shaikemelev, G.;

IITU Safety-Helmet Dataset: Drone-Captured and Ground-Level Images with Color Annotations. 2025.
DOI: soon

License:
CC BY 4.0