OptimaLab35

OptimaLab35 is a graphical and terminal user interface for optima35. It is under heavy development, and both UI elements and cross-platform compatibility may change.

Overview

OptimaLab35 extends OPTIMA35 (Organizing, Processing, Tweaking Images, and Modifying scanned Analogs from 35mm Film) by providing an intuitive interface for image and metadata management. While tailored for analog photography, it supports any type of image.

Current Status

Versioning and Compatibility

The preserved version v0.1.0 ensures stability with the current GUI design. It depends on optima35==0.6.4, a version confirmed to work seamlessly with this release. Future updates may introduce breaking changes, especially as the project evolves across platforms.

Installation

Install via pip (dependencies are automatically managed, except for simple-term-menu used in TUI mode, which is Linux-only):

pip install OptimaLab35

Development and Notes

Alpha Stage

• UI designs (GUI and TUI) are evolving, and breaking changes may occur.
• The CHANGELOG provides detailed updates.
• Some safety checks are still under development.

Modes:

• GUI: Default if PySide6 is available.
• TUI: Fallback if PySide6 is missing or can be explicitly started using the --tui flag.

Preview GUI

PREVIEW might be out of date.

Main tab

{width=40%}

Preview window

{width=40%}

Exif tab

{width=40%}

Exif editor

{width=40%}

Info window

{width=40%}

Features

Image Processing

• Resizing
• Renaming with custom order
• Grayscale conversion
• Brightness and contrast adjustment

EXIF Management

• Copy or add custom EXIF data
• Add GPS coordinates
• Add or modify EXIF dates
• Remove EXIF metadata

Watermarking

• Add customizable watermarks

Dependencies

GUI Mode:

• optima35
• pyside6

TUI Mode (Linux only):

• simple-term-menu

Use of LLMs

In the interest of transparency, I disclose that Generative AI (GAI) large language models (LLMs), including OpenAI’s ChatGPT and Ollama models (e.g., OpenCoder and Qwen2.5-coder), have been used to assist in this project.

Areas of Assistance:

• Project discussions and planning
• Spelling and grammar corrections
• Suggestions for suitable packages and libraries
• Guidance on code structure and organization

In cases where LLMs contribute directly to code or provide substantial optimizations, such contributions will be disclosed and documented in the relevant sections of the codebase.

Ollama

• mradermacher gguf Q4K-M Instruct version of infly/OpenCoder-1.5B
• unsloth gguf Q4K_M Instruct version of both Qwen/QWEN2 1.5B and 3B

References

1. Huang, Siming, et al. OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models. 2024. PDF

2. Hui, Binyuan, et al. Qwen2.5-Coder Technical Report. arXiv preprint arXiv:2409.12186, 2024. arXiv

3. Yang, An, et al. Qwen2 Technical Report. arXiv preprint arXiv:2407.10671, 2024. arXiv