---
license: cc-by-4.0
tags:
- computer-vision
- semantic-segmentation
- mining
- industrial-inspection
- monorail
- underground-environment
---

# Mine Monorail Track Segmentation Dataset

This dataset supports semantic segmentation of **mine-use suspended monorails** in simulated underground environments. It was collected in a dedicated experimental workshop provided by an industrial partner and includes images captured under diverse structural and illumination conditions to reflect realistic operational challenges.

## 📷 Data Collection

- **Camera**: Hikvision DS-2CD2820FWD  
- **Sensor**: 1/2.8" Progressive Scan CMOS  
- **Resolution**: 1280×720 (from native 1920×1080)  

Images were captured in a controlled workshop that replicates key characteristics of underground monorail roadways, including track geometry, lighting variability, and common obstructions.

## 🗂️ Dataset Statistics

- **Total images**: 2,681  
- **Annotation tool**: LabelMe (pixel-level precision)  
- **Classes**:  
  - `0`: Background  
  - `1`: Monorail Track  
- **Track configurations**:  
  - Straight segments  
  - Curved sections  
  - Ascending slopes  
  - Descending slopes  
- **Illumination conditions**:  
  - Normal lighting  
  - Low-light  
  - Overexposed  

Each image is paired with a single-channel PNG mask where pixel values correspond to class IDs.

## 🔧 Data Augmentation (for reference)

To improve model robustness under harsh mining conditions, the authors employed a specialized data augmentation pipeline during training that simulates:
- **Low-light scenarios** through controlled brightness reduction,
- **Sensor noise** via Gaussian and salt-and-pepper noise injection,
- **Dust interference** using color overlays, texture synthesis, and visibility attenuation.

> 💡 **Note**: The raw dataset contains only original images and ground-truth masks—**no augmented samples are included**. Full technical details of the augmentation strategy are provided in the associated paper (Section 4.5).

## 📁 Directory Structure

```monorail-seg/
├── images/
│ ├── Training_Input/
│ ├── Validation_Input/
│ └── Test_Input/
├── labels/
│ ├── Training_GroundTruth/
│ ├── Validation_GroundTruth/
│ └── Test_GroundTruth/
├── README.md
└── LICENSE
```