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matitie/image-bank-202601

📂 matitie/image-bank-202601 Dataset Description This dataset is part of the Top10Fans monthly archival system, designed to store and deliver processed visual assets for blog content, historical reference, and automated publishing workflows. Each month, a new dataset is created to isolate and version image collections by time period. 📅 Timeframe Month: 202601 (January 2026, UTC) 🎯 Purpose Serve as a durable, versioned storage… See the full description on the dataset page: https://huggingface.co/datasets/matitie/image-bank-202601.

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Dataset Card

📂 matitie/image-bank-202601

Dataset Description

This dataset is part of the Top10Fans monthly archival system, designed to store and deliver processed visual assets for blog content, historical reference, and automated publishing workflows. Each month, a new dataset is created to isolate and version image collections by time period.

📅 Timeframe

—Month: 202601 (January 2026, UTC)

🎯 Purpose

—Serve as a durable, versioned storage layer for web-optimized images.
—Enable reproducible content pipelines via immutable monthly snapshots.
—Support auditability and rollback in case of data corruption or policy changes.

🏗️ Directory Structure

The dataset uses a clean, flat partitioning scheme: . ├── images/ │ ├── img0001.webp │ ├── img0002.webp │ └── ... └── meta/ ├── manifest.jsonl └── audit.log

—`images/`: Contains .webp files (lossy-compressed, ～80% quality) optimized for fast web delivery.
—`meta/manifest.jsonl`: One JSON object per line, with fields:

json

  {"id": "img_0001", "source_url": "...", "width": 1200, "height": 800, "checksum": "sha256:..."}

  meta/audit.log: Plain-text log of ingestion events (timestamp, source, operator).
📦 Data Characteristics
Format: WebP (RGB, no EXIF)
Resolution: Typically 800×600 to 1920×1080
Volume: ～10,000–50,000 images per month
Total Size: ～1–5 GB/month
Usage
Loading with Hugging Face Datasets
While this dataset isn’t structured as a conventional HF Dataset, you can access files directly:

from huggingface_hub import hf_hub_download

# Download a specific image
path = hf_hub_download(
    repo_id="matitie/image-bank-202601",
    filename="images/img_0001.webp",
    repo_type="dataset"
)
Git LFS Access
Clone the entire dataset (requires Git LFS):
git lfs install
git clone https://huggingface.co/datasets/matitie/image-bank-202601

⚠️ Note: Large datasets may take time to download. Use selective file access when possible.

License
MIT License. See LICENSE for full text.
You are free to:
Use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies.
Include in commercial products.
Provided that:
Original copyright notice and permission notice are included.
Acknowledgements
Images sourced from public web content under fair use and transformation policies.
Processed using automated pipelines with human-in-the-loop validation.
Hosted on Hugging Face Hub for open archival and reproducibility.
Maintenance
Owner: Top10Fans Infrastructure Team (@matitie)
Automation: CI/CD pipeline creates this dataset on the 1st of each month.
Retention: Datasets are retained indefinitely unless deprecated.
🔁 This dataset is append-only—no files are ever modified after initial upload.