| --- |
| dataset_name: PPE Detection |
| datasets: |
| - <your-username>/ppe-detection |
| license: cc-by-4.0 |
| task_categories: |
| - object-detection |
| tags: |
| - computer-vision |
| - object-detection |
| - safety |
| - ppe |
| - yolo |
| pretty_name: PPE Detection Dataset |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # PPE Detection Dataset 🦺🪖😷 |
|
|
| A high-quality, annotated dataset for **Personal Protective Equipment (PPE)** detection in industrial and construction environments. |
| The dataset is suitable for training **object detection models** such as YOLOv8, YOLOv5, Detectron2, etc. |
|
|
| --- |
|
|
| ## 1. Dataset Summary |
|
|
| This dataset contains images annotated with **6 PPE classes**: |
|
|
| - Vest |
| - Safety Shoe |
| - Mask |
| - Helmet |
| - Goggles |
| - Gloves |
|
|
| It is designed for: |
|
|
| - Construction site safety compliance |
| - Industrial worker monitoring |
| - Automated PPE detection for CCTV / RTSP cameras |
| - Real-time analytics on edge devices (Jetson, Raspberry Pi, etc.) |
|
|
| ### Class Distribution |
|
|
| | Class | Count | |
| |-------------|-------| |
| | Vest | 4,418 | |
| | Safety Shoe | 2,006 | |
| | Mask | 2,763 | |
| | Helmet | 2,703 | |
| | Goggles | 1,431 | |
| | Gloves | 2,693 | |
| | **Total Objects** | **16,014** | |
|
|
| > Note: Counts refer to **annotated objects**, not number of images. |
|
|
| --- |
|
|
| ## 2. Supported Tasks and Leaderboards |
|
|
| **Task type:** `Object Detection` |
|
|
| Typical use cases: |
|
|
| - PPE presence/absence detection |
| - Safety rule enforcement |
| - Worker compliance monitoring |
| - Scene understanding in industrial environments |
|
|
| No official leaderboard is maintained yet. |
|
|
| --- |
|
|
| ## 3. Dataset Structure |
|
|
| The dataset follows a **YOLO-style folder structure**, typically like: |
|
|
| ```text |
| PPE/ |
| ├── train/ |
| │ ├── images/ |
| │ └── labels/ |
| ├── valid/ |
| │ ├── images/ |
| │ └── labels/ |
| ├── test/ |
| │ ├── images/ |
| │ └── labels/ |
| └── data.yaml |
| |
| --- |
| |
| 🤝 Thanks / Contact |
| For improvements, issues, or contributions—open a Pull Request or Discussion. |
| |
