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| .gitlab-ci.yml | ||
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| README.md | ||
OptimaLab35
Last updated: 28 Jan 2025
Overview
OptimaLab35 enhances OPTIMA35 (Organizing, Processing, Tweaking Images, and Modifying scanned Analogs from 35mm Film) by offering a user-friendly graphical interface for efficient image and metadata management.
It serves as a GUI for the OPTIMA35 library, providing an intuitive way to interact with the core functionalities.
Current Status
Alpha Stage
OptimaLab35 is built using PySide6 and Qt, offering a modern and flexible interface for OPTIMA35.
The program is under active development, and while versions released on PyPI should not contain major bugs, occasional issues may arise.
For the most accurate and detailed update information, please refer to the well-maintained CHANGELOG, as this README may occasionally lag behind the latest updates.
Features
Image Processing
- Resize images (upscale or downscale)
- Convert images to grayscale
- Adjust brightness and contrast
- Add customizable text-based watermarks
Image preview
- Load a single image and see how change in brightness and contrast changes the image
EXIF Management
- Add EXIF data using a simple dictionary
- Copy EXIF data from the original image
- Remove EXIF metadata completely
- Add timestamps (e.g., original photo timestamp)
- Automatically adjust EXIF timestamps based on image file names
- Add GPS coordinates to images
Installation
Install via pip (dependencies are handled automatically):
pip install OptimaLab35
Preview GUI
PREVIEW might be out of date.
Main tab
{width=40%}
Preview window
{width=40%}
Exif tab
{width=40%}
Exif editor
{width=40%}
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