README.md

metadata

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

📖 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)

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:

unzip dataset.zip

Option 2: Python (Hugging Face Hub)

You can download and unzip programmatically using 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:

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

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✍️ Citation

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

Created by [RAT]

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