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Datasets:
sleepysaurus
/
RailRakshak-Track-Detection-Data

Tasks:
Object Detection
Image Segmentation
Size:
1K<n<10K
Tags:
yolo
railway
security
surveillance
yolov8
License:
Dataset card Files
xet
Community
RailRakshak-Track-Detection-Data
File size: 2,161 Bytes 
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---
license: mit
task_categories:
- object-detection
- image-segmentation
tags:
- yolo
- railway
- security
- surveillance
- yolov8
pretty_name: RailRakshak Security Dataset
size_categories:
- 1K<n<10K
---

# 🚄 RailRakshak: Railway Threat Detection Dataset

![YOLOv8](https://img.shields.io/badge/Format-YOLOv8-blue)
![Task](https://img.shields.io/badge/Task-Object%20Detection%20%26%20Segmentation-green)

## 📖 Dataset Description


### 🎯 Supported Tasks
- **Track Segmentation:** Pixel-wise masks of the railway track (Safe Zone).
- **Threat Detection:** Bounding boxes for obstacles on the track.

## 📂 Dataset Structure
Due to the large number of small files, the dataset is provided as a **single ZIP archive** (`dataset.zip`) to ensure fast downloads and bypass Git LFS rate limits.

**⚠️ You must unzip the file after downloading.**

### Directory Layout (After Unzipping)
```bash
dataset/
├── railway_dataset/
│   ├──Rail-DB/
├── railway_seg
│   ├── train/    
│   └── raildb_raw/        
├── samples/
│   ├── test.mp4        
│   └── Test2.mp4        
└── output/             # EMPTY DIRECTORY 

```

## 🚀 How to Use

### Option 1: Direct Download

1. Go to the **"Files and versions"** tab.
2. Download `dataset.zip`.
3. Unzip it locally:
```bash
unzip dataset.zip

```

### Option 2: Python (Hugging Face Hub)

You can download and unzip programmatically using Python:

```python
from huggingface_hub import hf_hub_download
import zipfile

# Download
path = hf_hub_download(
    repo_id="YOUR_USERNAME/RailRakshak-Track-Detection-Data",
    filename="dataset.zip",
    repo_type="dataset"
)

# Unzip
with zipfile.ZipFile(path, 'r') as zip_ref:
    zip_ref.extractall("./railrakshak_data")

print("✅ Dataset downloaded and extracted!")

```

### Option 3: Training with YOLOv8

Once unzipped, you can train immediately:

```bash
yolo task=segment mode=train model=yolov8n-seg.pt data=./railrakshak_data/data.yaml epochs=100 imgsz=640

```

---

## ✍️ Citation

If you use this dataset, please cite the **RailRakshak Hackathon Project**.

*Created by [RAT]*

---