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README.md

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+---
+license: mit
+task_categories:
+  - object-detection
+language:
+  - en
+tags:
+  - yolo
+  - ppe-detection
+  - safety
+  - computer-vision
+  - construction
+size_categories:
+  - 10K<n<100K
+---
+
+# PPE Detection Dataset (3-Class)
+
+딥러닝 기반 건설현장 안전 장비(PPE) 착용 모니터링을 위한 데이터셋
+
+## Dataset Description
+
+개인보호구(Personal Protective Equipment) **착용/미착용 상태**를 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
+
+| Class ID | Class Name | Description |
+|----------|------------|-------------|
+| 0 | helmet | 안전 헬멧 착용 ✅ |
+| 1 | head | 헬멧 미착용 (머리만) ⚠️ |
+| 2 | vest | 반사 안전 조끼 착용 ✅ |
+
+### Dataset Statistics
+
+| Split | Images | Labels | Helmet | Head | Vest | Total Objects |
+|-------|--------|--------|--------|------|------|---------------|
+| Train | 9,999 | 9,999 | 25,425 | 3,679 | 10,351 | 39,455 |
+| Val | 2,750 | 2,750 | 6,793 | 1,144 | 2,737 | 10,674 |
+| Test | 2,751 | 2,751 | 6,939 | 962 | 2,961 | 10,862 |
+| **Total** | **15,500** | **15,500** | **39,157** | **5,785** | **16,049** | **60,991** |
+
+**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
+
+```bash
+# Install huggingface-hub
+pip install huggingface-hub
+
+# Download dataset
+huggingface-cli download jhboyo/ppe-dataset --repo-type dataset --local-dir ./dataset
+```
+
+### Using with uv
+
+```bash
+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:
+
+```yaml
+# 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
+
+```python
+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. **Hard Hat Detection** (5,000 images)
+   - Original classes: helmet, head, person
+   - Used: **helmet, head** (착용/미착용 모두 탐지)
+
+2. **Safety Helmet and Reflective Jacket** (10,500 images)
+   - Classes: Safety-Helmet, Reflective-Jacket
+   - 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
+
+```bibtex
+@dataset{ppe_detection_3class_2025,
+  title={PPE Detection Dataset with Helmet Wearing/Non-Wearing Classification (3-Class)},
+  author={SafetyVisionAI Team},
+  year={2025},
+  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.
+
+- GitHub: [SafetyVisionAI](https://github.com/jhboyo/SafetyVisionAI)

test/labels/ds1_hard_hat_workers124.txt

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