sushan98/youtube-creative-commons-15k

🎬 Creative Commons YouTube Video Metadata Dataset (14,600 Videos)

A comprehensive, balanced benchmark dataset of 14,600 Creative Commons YouTube video links and metadata spanning 20 diverse categories, including everyday ambient scenes and extensive Nepal-related cultural, trekking, and heritage content.

⚠️ Important Legal & License Notice:
Links and metadata only, no video files included. Each video keeps its original Creative Commons license; credit the creators.

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📌 Dataset Overview

• Total Records: 14,600 unique video links and metadata records
• Categories: 20 balanced categories with exactly 730 videos per category (5.00% each)
• License: Creative Commons Attribution (CC-BY / CC-BY-SA)
• Formats Provided: metadata.jsonl (JSON Lines) and metadata.csv (Comma-Separated Values)
• Duration Filter: Strictly filtered between 5 seconds and 20 minutes (1,200 seconds) — zero ultra-short clips (<5s) and zero livestreams/full movies (>20min)
• Deduplication: 100% deduplicated by unique video_id
• Geographic & Cultural Diversity: Global coverage with dedicated focus on Nepal (trekking, Himalayan mountain trails, festivals like Dashain/Tihar, Newari heritage, rural villages, local markets).

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🗂️ Categories & Distribution

Category	Description & Scope	Video Count	% of Dataset
animals	Safari wildlife, pets, birds of prey, marine life, domestic animals	730	5.00%
art	Oil painting, watercolors, sculpture, printmaking, calligraphy, murals	730	5.00%
city_life	Walking tours, urban architecture, street atmosphere, transit, skylines	730	5.00%
cooking	Recipes, sourdough baking, curry making, campfire meals, culinary skills	730	5.00%
dance	Ballet, hip-hop, contemporary, traditional folk, tango, salsa, bboy	730	5.00%
diy_crafts	Woodworking, pottery, leathercraft, knitting, origami, blacksmithing	730	5.00%
education	Mathematics, history, physics, philosophy, linguistics, biology, astronomy	730	5.00%
everyday_scenes	Rain against windows, coffee rituals, quiet libraries, peaceful gardens	730	5.00%
fashion	Sustainable fashion, handloom weaving, vintage styling, bespoke tailoring	730	5.00%
festivals_culture	Lantern festivals, street carnivals, folk pageants, solstice bonfires	730	5.00%
food	Street food night markets, artisan bread, coffee culture, cheese making	730	5.00%
gaming	Indie game showcases, retro speedruns, flight simulators, chess, sandboxes	730	5.00%
music	Fingerstyle guitar, piano solos, ambient modular synths, lofi beats	730	5.00%
nature	Mountain landscapes, ocean waves, waterfalls, forest wilderness, 4K vistas	730	5.00%
nepal_content	Nepali culture, Annapurna/Everest trekking, Kathmandu, villages, festivals	730	5.00%
science	Chemical reactions, deep space astrophotography, fluid dynamics, botany	730	5.00%
sports	Skateboarding, rock climbing, ocean surfing, basketball, cycling, workouts	730	5.00%
technology	Linux OS, electronics soldering, 3D printing, robotics, custom keyboards	730	5.00%
travel	Solo backpacking, historic towns, road trips, islands, scenic railways	730	5.00%
vehicles	Classic car restoration, motorcycles, ebikes, train cab rides, aviation	730	5.00%
TOTAL	20 Balanced Categories	14,600	100.00%

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🏷️ Field Explanations

Both metadata.jsonl and metadata.csv contain the following 13 metadata fields:

Field Name	Type	Example	Description
video_id	string	QT97HgUUW8w	Unique 11-character YouTube video identifier
url	string	https://www.youtube.com/watch?v=QT97HgUUW8w	Canonical YouTube watch URL
title	string	Unreal Sunrise at Khumai Danda | Nepal Trek	Full video title
description	string	Join our trek to Khumai and Korchan hilltop...	First 500 characters of the video description
channel_name	string	Anmol Aashish	Channel or creator display name
channel_id	string	UCx7...	Unique YouTube channel identifier
category	string	nepal_content	One of the 20 target categories
duration_seconds	integer	908	Video duration in seconds (5s to 1200s)
language	string	ne	Detected language (en, ne, ja, etc.)
upload_date	string	2024-03-15	ISO 8601 upload date (YYYY-MM-DD)
view_count	integer	45200	Recorded view count
license	string	Creative Commons (CC-BY)	Creative Commons license declaration
tags	list / string	["sunrise", "khumai", "nepal", "trek"]	Topical keywords associated with the video

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💻 Quickstart: Loading the Dataset

Method 1: Using Hugging Face datasets

from datasets import load_dataset

# Load directly from Hugging Face
dataset = load_dataset("sushan98/youtube-creative-commons-15k", split="train")

print(f"Loaded {len(dataset):,} video metadata entries!")
sample = dataset[0]
print(f"Title:    {sample['title']}")
print(f"Category: {sample['category']}")
print(f"URL:      {sample['url']}")
print(f"Duration: {sample['duration_seconds']}s")

Method 2: Using Pandas

import pandas as pd

# Read CSV directly
df = pd.read_csv("https://huggingface.co/datasets/sushan98/youtube-creative-commons-15k/raw/main/metadata.csv")
print(df.groupby("category")["video_id"].count())

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⬇️ How to Download Videos with yt-dlp

You can use yt-dlp to download videos or extract audio locally.

1. Download a Single Video (MP4, Max 720p/1080p):

yt-dlp -f "bestvideo[height<=720][ext=mp4]+bestaudio[ext=m4a]/best[height<=720][ext=mp4]/best" \
       -o "downloads/%(title)s.%(ext)s" \
       "https://www.youtube.com/watch?v=QT97HgUUW8w"

2. Batch Download Script in Python:

import json
import subprocess
import os

os.makedirs("downloads", exist_ok=True)

# Read metadata.jsonl
with open("metadata.jsonl", "r", encoding="utf-8") as f:
    for i, line in enumerate(f):
        item = json.loads(line)
        url = item["url"]
        cat = item["category"]
        title = item["title"]

        print(f"[{i+1}/14600] Downloading [{cat}]: {title} ({url})")

        # Run yt-dlp to download video
        subprocess.run([
            "yt-dlp",
            "-f", "bestvideo[height<=720]+bestaudio/best[height<=720]",
            "-o", f"downloads/{cat}/%(id)s.%(ext)s",
            "--max-filesize", "150M",
            "--no-playlist",
            url
        ])

        if i >= 5:  # Sample run
            break

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🛠️ Reproducing or Resuming the Collection

The companion script collector.py provides a complete, self-healing, resumable collector:

1. API Mode: Uses YouTube Data API v3 (YOUTUBE_API_KEY) with automatic daily quota tracking (10,000 units/day: 100 units/search, 1 unit/videos.list).
2. Direct Engine: High-performance multi-threaded search using Creative Commons protobuf filter (params='EgIwAQ==').
3. Resumable Storage: SQLite database (dataset.db) checkpoints progress automatically.

Run the collector:

python collector.py --target 730 --repo-id sushan98/youtube-creative-commons-15k

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🛡️ License & Attribution

Links and metadata only, no video files included. Each video keeps its original Creative Commons license; credit the creators.
Metadata compilation released under CC-BY 4.0.