jhboyo/ppe-dataset

PPE Detection Dataset (3-Class)

딥러닝 기반 건설현장 안전 장비(PPE) 착용 모니터링을 위한 데이터셋

Dataset Description

개인보호구(Personal Protective Equipment) 착용/미착용 상태를 감지하기 위한 YOLO 형식의 객체 탐지 데이터셋입니다.

주요 특징:

• —✅ 헬멧 착용 감지 (helmet)
• —⚠️ 헬멧 미착용 감지 (head) - 실시간 안전 경고 가능
• —✅ 안전조끼 착용 감지 (vest)
• —15,500개 이미지, 60,991개 객체
• —YOLOv8 최적화 포맷

Classes

Dataset Statistics

Class Distribution:

• —Helmet: 39,157개 (64.2%) - 헬멧 착용
• —Head: 5,785개 (9.5%) - 헬멧 미착용
• —Vest: 16,049개 (26.3%) - 안전조끼 착용

Split Ratio:

• —Train: 64.5% (9,999 images)
• —Val: 17.7% (2,750 images)
• —Test: 17.7% (2,751 images)

Data Format

YOLO 형식 (normalized coordinates):

class_id x_center y_center width height

Example:

0 0.456789 0.345678 0.123456 0.234567  # helmet
1 0.234567 0.123456 0.098765 0.187654  # head
2 0.567890 0.456789 0.145678 0.256789  # vest

Dataset Structure

ppe-dataset/
├── train/
│   ├── images/     # 9,999 images
│   └── labels/     # 9,999 label files (3 classes)
├── val/
│   ├── images/     # 2,750 images
│   └── labels/     # 2,750 label files (3 classes)
└── test/
    ├── images/     # 2,751 images
    └── labels/     # 2,751 label files (3 classes)

Usage

Download with Hugging Face CLI

# Install huggingface-hub
pip install huggingface-hub

# Download dataset
huggingface-cli download jhboyo/ppe-dataset --repo-type dataset --local-dir ./dataset

Using with uv

uv tool install huggingface-hub
uv tool run hf download jhboyo/ppe-dataset --repo-type dataset --local-dir ./dataset/data

YOLO Training Configuration

Create a YAML configuration file:

# ppe_dataset.yaml
path: /path/to/dataset
train: train/images
val: val/images
test: test/images

nc: 3
names:
  0: helmet
  1: head
  2: vest

Training with YOLOv8

from ultralytics import YOLO

# Load model
model = YOLO('yolov8n.pt')

# Train
model.train(
    data='ppe_dataset.yaml',
    epochs=100,
    imgsz=640,
    batch=16
)

Data Sources

This dataset is merged from two Kaggle datasets:

1. 1.Hard Hat Detection (5,000 images)
2. 2.Original classes: helmet, head, person
3. 3.Used: helmet, head (착용/미착용 모두 탐지)

1. 1.Safety Helmet and Reflective Jacket (10,500 images)
2. 2.Classes: Safety-Helmet, Reflective-Jacket
3. 3.Used: both classes (helmet, vest)

Preprocessing

• —VOC to YOLO format conversion for Dataset 1
• —3-Class Mapping:
• —helmet: 0 (헬멧 착용)
• —head: 1 (헬멧 미착용, Dataset 1 only)
• —vest: 2 (안전조끼 착용)
• —File naming with prefix (ds1, ds2) to avoid conflicts
• —Dataset split:
• —Train: 64.5% (9,999 images)
• —Val: 17.7% (2,750 images)
• —Test: 17.7% (2,751 images)
• —Seed: 42 (reproducible)

License

MIT License

Citation

@dataset{ppe_detection_2024,
  title={PPE Detection Dataset for Construction Safety},
  author={SafetyVisionAI Team},
  year={2024},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/jhboyo/ppe-dataset}
}

Project

This dataset is part of the Safety Vision AI project - a deep learning-based construction site safety equipment monitoring platform.

Original Dataset Sources

This dataset is created by merging and preprocessing the following Kaggle datasets:

1. 1.Hard Hat Detection Dataset
2. 2.Source: Hard Hat Detection on Kaggle
3. 3.Original classes: helmet, head, person
4. 4.Format: Pascal VOC
5. 5.Images: 5,000

1. 1.Safety Helmet and Reflective Jacket Dataset
2. 2.Source: Construction Site Safety Image Dataset on Kaggle
3. 3.Original classes: Safety-Helmet, Reflective-Jacket
4. 4.Format: YOLO
5. 5.Images: 10,500

Acknowledgments: We thank the original dataset creators for making their work publicly available.