License Python 3.8+ JavaScript

Blazing fast image archive format with instant web access - 4GB archives load in 1 second! ⚡

A high-performance, lightweight binary archive for your photo collections, complete with a GUI packer and a serverless web-based gallery viewer.

This project provides a complete toolkit for efficiently storing and browsing large numbers of images. It uses a custom, highly-optimized binary format (.yufi) to pack entire directory structures into a single, portable file.

The cross-platform GUI Packer tool.

The feature-rich, serverless Web Viewer.

• Web comics/manga viewers
• Image galleries with thousands of images
• Game asset bundles

• Highly Optimized Binary Format: The custom .yufi format is designed for minimal size and extremely fast, on-demand data access.
• Directory Structure Preservation: Archives maintain the original folder hierarchy, allowing for organized collections.(File names are not preserved. After unpacking, they take the form: image_*)
• Large File Support: Optimized to handle large archives (up to 4GB) without loading the entire file into memory.
• Cross-Platform GUI Packer: An easy-to-use tool built with Python and Tkinter to pack and unpack archives. It runs on Windows, macOS, and Linux.
• Serverless Web Viewer: A single, self-contained HTML file that can open and browse .yufi archives directly in your web browser. No backend or server required!
• Advanced Viewer Features:
  • Lazy Loading: Only images currently on-screen are loaded, ensuring smooth performance even with thousands of photos.
  • Directory Filtering: Instantly filter the gallery by the original folder structure.
  • Full Pagination: Complete navigation controls, including "First," "Last," "Next," "Previous," and a "Go to page" input.
  • Lightbox: Click any thumbnail to view a full-sized version of the image.
  • Comic Book View:
    • Seamless reading experience with continuous vertical flow
    • Smart chapter detection and navigation (supports fractional chapters like 65.5, 90.1, etc.)
    • Chapter navigation buttons at both top and bottom of the page
    • Automatic scrolling to top when changing chapters
    • No gaps between images for authentic comic book reading
    • Perfect for comics, manga, and other sequential art

For optimal compatibility with the comic book view feature, please use the following naming pattern for directories containing chapters:

Standard format: chapter_X where X is the chapter number

Examples: chapter_1, chapter_2, chapter_15

Fractional chapters supported: chapter_65.5, chapter_90.1, chapter_90.2

The viewer will automatically:

• Detect and sort chapters numerically

• Handle fractional chapter numbers correctly

• Provide seamless navigation between chapters in comic book view

1. The Packer (Yuffin-Image-Archive.py) A Python application with a graphical user interface for creating (.yufi) archives from a folder of images and for unpacking them back into their original directory structure.

2. The Viewer (index.html) A powerful, client-side web application written in pure JavaScript. It can open a local .yufi file, parse its structure, and display an interactive, filterable, and paginated gallery.

1. Make sure you have Python installed on your system.
2. Run the Yuffin-Image-Archive.py file.
3. To Pack:
   • Click "Browse..." to select your source folder containing images.
   • Click "Save As..." to choose a location and name for your .yufi archive.
   • Click PACK.
4. To Unpack:
   • Click "Browse..." to select an existing .yufi archive file.
   • Click "Browse..." to choose an empty output folder.
   • Click UNPACK.

1. Open the index.html file in any modern web browser (Chrome, Firefox, Edge, Safari).
2. Click the "Select .yufi File" button.
3. Select your .yufi archive file from your computer.
4. The gallery will load instantly. Use the filter and pagination controls to browse your collection.

The file format is designed for efficiency and random access.

• Packer/Unpacker: Python, Tkinter (for GUI)
• Viewer: HTML5, CSS3, Vanilla JavaScript (no frameworks, no dependencies)

This project is licensed under the MIT License - see the LICENSE file for details.