WalkIndia-200K Video Clips

~115K video clips (4-10s each) from 714 Indian street videos (walking tours, driving tours, drone views) across 21+ cities for evaluating video foundation models on non-Western urban scenes.

Dataset Description

Property	Value
Format	WebDataset (TAR shards)
Total Clips	115,687
Shards	116 x ~1 GB TAR files
Source Videos	714
Duration Range	4.0s - 10.0s
Mean Duration	~8.6s
Total Size	121.5 GB
Total Hours	~277 hours source footage
Cities	21+ (6 tier-1, 15 tier-2, Goa, monuments)

Format

WebDataset TAR shards with paired mp4 + json files:

data/
├── train-00000.tar
│   ├── 000000.mp4    # video clip
│   ├── 000000.json   # metadata (video_id, section, duration, etc.)
│   ├── 000001.mp4
│   ├── 000001.json
│   └── ...
├── train-00001.tar
└── ...

Loading

from datasets import load_dataset

# Streaming (recommended — no local download)
ds = load_dataset("anonymousML123/walkindia-200k", streaming=True)
for sample in ds["train"]:
    video = sample["mp4"]
    metadata = sample["json"]

Processing Pipeline

1. Download: yt-dlp at 480p (714 videos from YouTube)
2. Scene Detection: PySceneDetect ContentDetector (threshold=15.0)
3. Greedy Split: Scene-aware splitting, 4-10s clips, libx264 CRF 28

Metadata Fields

Each clip's JSON sidecar contains:

Field	Description
video_id	YouTube video ID
section	Geographic section (e.g., tier1/mumbai/drive)
tier	City tier (tier1, tier2, goa, monuments)
city	City name
tour_type	Tour type (walking, drive, drone, rain)
duration_sec	Clip duration in seconds
size_mb	File size in MB
source_file	Original clip filename

Intended Use

• Evaluate V-JEPA 2 video embeddings on Indian urban scenes
• Test geographic transfer of video foundation models
• Research on non-Western video understanding

Citation

@dataset{walkindia200k,
  title={WalkIndia-200K: Indian Street Video Clips for Video Foundation Model Evaluation},
  author={Anonymous},
  year={2026},
  url={https://huggingface.co/datasets/anonymousML123/walkindia-200k}
}

License

CC-BY-4.0 (Creative Commons Attribution 4.0)

Original videos sourced from YouTube walking/driving/drone tour channels.