| .woodpecker | ||
| flatpak | ||
| media | ||
| src | ||
| .gitignore | ||
| CHANGELOG.md | ||
| GitVersion.yml | ||
| LICENSE.md | ||
| pip_README.md | ||
| README.md | ||
| requirements.txt | ||
OptimaLab35
Developed on my forgejo instance, GitLab is used as backup.
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
The program has reached a stable release. All functions have been tested, and there should be no bugs. While there is always room for additional features and optimizations, the core functionality is complete and reliable.
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 changes in brightness and contrast affect 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
Settings
- Option to use
PyQtDarkThemeand select Dark, Light, or auto theme - Checks for updates on PyPI, automatically downloads and installs the latest version
Installation
Install via pip (dependencies are handled automatically):
pip install OptimaLab35
GUI Preview
The layout remains consistent with v1.0.0. The UI is OS-dependent, but a custom theme can be enabled in the settings.
Main tab
{width=40%}
{width=40%}
Exif tab
{width=40%}
{width=40%}
Preview window
{width=40%}
{width=40%}
Settings
{width=40%}
{width=40%}
Updater
{width=40%}
{width=40%}
Contribution
Thanks to developer Mr Finch for contributing to this project.
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