Create README.md

README.md

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+---
+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
+```