Datasets:

fadhilafif98
/

triples-objekts

Catatan: Data di bawah ini tersimpan otomatis di file sync_checkpoint.json. Ketika ada rilis kartu baru dari Modhaus/COSMO, script update akan otomatis membandingkan dengan checkpoint ini sehingga tidak akan men-download ulang kartu atau gambar yang sudah ada.

Parameter	Nilai Terakhir
Tanggal Sync Terakhir	`2026-08-16`
Timestamp Data Terakhir (`latest_created_at`)	`1786582823000` (2026-08-13T01:00:23Z)
Total Objekts Terindeks	`10,983` unik objekts
Total Foto Photocard Ter-upload	`21,298` file (`_front.png` & `_back.png`)
Total Video Motion & Voice Ter-upload	`125` file (`.mp4`)
Daftar Season yang Sudah Masuk	`Atom01`, `Atom02`, `Binary01`, `Binary02`, `Cream01`, `Cream02`, `Divine01`, `Ever01`
Total Member Tercover	24 Member (S1–S24) + Semua Sub-unit
File Tracker Status	`sync_checkpoint.json` (Track 10,983 slug unik)

1. Cara Menggunakan Dataset via Python `datasets`

A. Load Standar

pip install datasets pillow

from datasets import load_dataset

# 1. Download & load dataset
dataset = load_dataset("fadhilafif98/triples-objekts", split="train")
print(f"Total data: {len(dataset)}")

# 2. Akses item pertama
sample = dataset[0]
print("Member :", sample["member"])
print("Season :", sample["season"])
print("Class  :", sample["class"])
print("Side   :", sample["side"])

# 3. Tampilkan gambar photocard
img = sample["image"]
img.show()

2. Cara Menggunakan Hugging Face sebagai Direct CDN (Web / App / Bot)

Hugging Face menyediakan endpoint CDN global Cloudflare gratis berkecepatan tinggi.

A. Format URL CDN Gambar (Photocard)

https://huggingface.co/datasets/fadhilafif98/triples-objekts/resolve/main/images/{season}/{member}/{slug}_{side}.png

Front Image: https://huggingface.co/datasets/fadhilafif98/triples-objekts/resolve/main/images/Atom01/JiWoo/atom01-jiwoo-100z_front.png
Back Image: https://huggingface.co/datasets/fadhilafif98/triples-objekts/resolve/main/images/Atom01/JiWoo/atom01-jiwoo-100z_back.png

B. Format URL CDN Video / Motion / Voice Objekts (MP4)

https://huggingface.co/datasets/fadhilafif98/triples-objekts/resolve/main/media/{season}/{member}/{slug}.mp4

Motion Loop: https://huggingface.co/datasets/fadhilafif98/triples-objekts/resolve/main/media/Binary02/SeoYeon/binary02-seoyeon-503z.mp4
Voice Clip: https://huggingface.co/datasets/fadhilafif98/triples-objekts/resolve/main/media/Binary02/SeoYeon/binary02-seoyeon-360z.mp4

Contoh di HTML:

<video autoplay loop muted playsinline width="300">
  <source 
    src="https://huggingface.co/datasets/fadhilafif98/triples-objekts/resolve/main/media/Binary02/SeoYeon/binary02-seoyeon-503z.mp4" 
    type="video/mp4" 
  />
</video>

C. Helper Function di JavaScript / TypeScript

const HF_CDN_BASE = "https://huggingface.co/datasets/fadhilafif98/triples-objekts/resolve/main";

// 1. Photocard Image CDN URL
export function getObjektImageUrl(season, member, slug, side = 'front', ext = 'png') {
  return `${HF_CDN_BASE}/images/${season}/${member}/${slug}_${side}.${ext}`;
}

// 2. Motion Video / Voice CDN URL
export function getObjektVideoUrl(season, member, slug) {
  return `${HF_CDN_BASE}/media/${season}/${member}/${slug}.mp4`;
}

D. Akses Raw JSON / Metadata via CDN

Master JSON: https://huggingface.co/datasets/fadhilafif98/triples-objekts/resolve/main/all_objekts.json
Summary Stats: https://huggingface.co/datasets/fadhilafif98/triples-objekts/resolve/main/summary.json
Checkpoint Tracker: https://huggingface.co/datasets/fadhilafif98/triples-objekts/resolve/main/sync_checkpoint.json
Per-Member (e.g. JiWoo): https://huggingface.co/datasets/fadhilafif98/triples-objekts/resolve/main/by_member/JiWoo.json
Per-Season (e.g. Atom01): https://huggingface.co/datasets/fadhilafif98/triples-objekts/resolve/main/by_season/Atom01.json

3. Cara Update Data Baru di Masa Depan (Tanpa Mulai dari Awal)

Sistem sudah dilengkapi checkpoint anti-duplikasi. Ketika Modhaus merilis season/objekts baru, jalankan 3 langkah ini:

Langkah 1: Unduh Hanya Data & Gambar Baru (Delta Fetch)

Script otomatis membaca sync_checkpoint.json dan hanya mengunduh data/media yang belum pernah tersimpan:

# 1. Unduh metadata baru & foto baru
python3 fetch_objekts.py --download-images

# 2. Unduh video baru jika ada rilis Motion Class baru
python3 fetch_media.py

Langkah 2: Sinkronkan Checkpoint & Index Hugging Face

Regenerasi index metadata.jsonl dan perbarui snapshot sync_checkpoint.json:

python3 prepare_hf_dataset.py
python3 generate_checkpoint.py

Langkah 3: Upload Hanya File Baru ke Hugging Face

Script upload menggunakan chunking dan hanya mengunggah file-file baru (delta changes):

python3 upload_to_hf.py --repo-id fadhilafif98/triples-objekts --token YOUR_HF_TOKEN

(Setelah upload selesai, Anda aman menghapus folder lokal images/ atau media/ lagi untuk menghemat kapasitas harddisk).

4. Struktur File Lokal & Fungsinya

File / Direktori	Deskripsi
`sync_checkpoint.json`	File state tracker berisi riwayat 10,983 objekts yang sudah ter-upload agar update berikutnya tidak download ulang
`all_objekts.json`	Master JSON mentah seluruh objekts dari Apollo / COSMO API
`summary.json`	Ringkasan statistik jumlah objekts per member, season, dan class
`by_member/`	Direktori berisi file JSON yang dipisah per masing-masing member (S1-S24)
`by_season/`	Direktori berisi file JSON yang dipisah per masing-masing season
`images/`	Direktori lokal foto photocard HD (`_front.png` & `_back.png`)
`media/`	Direktori lokal video motion & voice (`.mp4`)
`metadata.jsonl`	File mapping index standar Hugging Face ImageFolder
`fetch_objekts.py`	Script fetcher dengan auto-checkpoint filter
`fetch_media.py`	Script downloader untuk video Motion MP4
`prepare_hf_dataset.py`	Script mapping file ke `metadata.jsonl`
`upload_to_hf.py`	Script pengunggah multi-commit ke Hugging Face
`step.md`	Dokumentasi panduan penggunaan, CDN, dan update
`README.md`	Dataset Card resmi di Hugging Face

Panduan Penggunaan, CDN & Update Dataset tripleS Objekts

📌 Status Terakhir Snapshot Data (Sync Checkpoint)

1. Cara Menggunakan Dataset via Python datasets