Merge branch 'feature/forked' into 'main'
Finishing op the TUI version See merge request python_projects3802849/optima-35-tui!1
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README.md
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README.md
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# OPTIMA-35
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# OPTIMA-35 TUI *version*
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## Overview
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**OPTIMA-35** (**Organizing, Processing, Tweaking Images and Modifying scanned Analogs from 35mm Film**) is a Python-based project designed to provide a streamlined way to manage and edit metadata and images from analog photography. But can be used for any images.
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Fork from **OPTIMA-35** (**Organizing, Processing, Tweaking Images and Modifying scanned Analogs from 35mm Film**) which will preserve the TUI
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This project is a *port* of my earlier work, an collection of [bash script](https://gitlab.com/sf-bashscripts/analogphotography), transitioning functionality to a more modular and maintainable design.
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The primary focus is on building a terminal-based user interface (TUI). Initially, the interface will utilize `simple_term_menu`, with plans to expand to `textual` for a more dynamic TUI experience in the future.
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**Please check** if a new branch is available and read the **changelog** to see the progress and current features of the program. The README might sometimes lag behind.
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## **Current Status**
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- While the program works and core features are available, there are currently no safety checks in place. For example, the program will write / save an image without verifying if a file with the same name already exists.
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- While the program works and core features are available, there are currently some safety checks missing. For example, the program will write / save an image without verifying if a file with the same name already exists.
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- Additionally, while EXIF data/metadata should be implemented correctly, there is a possibility of overlooked issues. In the worst case, a program might throw an error when handling EXIF data, though this has not occurred so far.
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### Available Features:
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- Initial basic TUI functionality using `simple_term_menu` (planned to switch to a different interface later).
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- Core features, including image resizing, metadata management, and YAML configuration.
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## Key Features
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- Intuitive TUI for organizing and editing metadata and image properties.
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- Improved modularity with classes split into separate files for flexibility and maintainability.
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- Supports essential tasks like reading, editing, and saving EXIF data, as well as resizing and processing images.
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- Initial basic TUI functionality using `simple_term_menu`
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- Core features:
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- resizing
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- renaming
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- grayscale
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- Change brightness
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- Change contrast
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- Exif management
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- Add watermark
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**Gif of program in action**
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## Dependencies
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To run **OPTIMA-35 TUI**, the following Python libraries are required:
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To run **OPTIMA-35**, the following Python libraries are required:
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- **textual**: For building TUI (planned future updates).
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- **pyyaml**: To handle YAML files for configuration and settings.
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- **piexif**: To read, modify, and write EXIF metadata.
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- **Pillow**: For image processing.
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- **pillow**: For image processing.
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- **simple\_term\_menu**: For building the initial TUI interface.
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### Installing Dependencies
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You can install the dependencies using `pip`:
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```bash
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pip install textual pyyaml piexif pillow simple-term-menu
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pip install pyyaml piexif pillow simple-term-menu
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```
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Alternatively, you can use `conda` or its alternatives (`anaconda`, `mamba`, `micromamba`):
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```bash
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conda install -c conda-forge textual pyyaml piexif pillow simple-term-menu
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conda install -c conda-forge pyyaml piexif pillow simple-term-menu
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```
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## Development Approach
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Compared to my previous project, [FTL Save Manager](https://gitlab.com/python_projects3802849/ftl-save-manager), this project emphasizes:
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- **Enhanced Modularity**: Classes and components are organized into separate files, making the codebase more maintainable and scalable.
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- **Improved Design Principles**: Focus on creating reusable and flexible code for future expansion.
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- **Slower Code Pushes**: Updates and code releases will be less frequent but of higher quality, ensuring stability and adherence to best practices.
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# Use of LLMs
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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.
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@ -71,8 +56,9 @@ In the interest of transparency, I disclose that Generative AI (GAI) large langu
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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.
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mradermacher gguf Q4K-M Instruct version of infly/OpenCoder-1.5B
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unsloth gguf Q4K_M Instruct version of both Qwen/QWEN2 1.5B and 3B
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**ollama**
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- mradermacher gguf Q4K-M Instruct version of infly/OpenCoder-1.5B
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- unsloth gguf Q4K_M Instruct version of both Qwen/QWEN2 1.5B and 3B
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### References
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1. **Huang, Siming, et al.**
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# Example file. You can add and remove entries here.
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make:
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- Nikon
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model:
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6
main.py
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main.py
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class Optima35:
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# The layout of class Optima35 was originally made by ChatGPT, but major adjustments have been made. To remain transparent, I disclose this.
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def __init__(self, settings_file, exif_options_file):
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self.version = "0.2.0"
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self.name = "OPTIMA-35 TUI"
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self.version = "0.2.1"
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self.utilities = Utilities()
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self.image_processor = ImageProcessor()
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self.exif_handler = ExifHandler()
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self.settings["output_folder"] = input("Enter path of output folder: ").strip()
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self.settings["file_format"] = self.take_input_and_validate(question = "Enter export file format (jpg, png, webp): ", accepted_input = ["jpg", "png", "webp"], accepted_type = str)
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self.settings["modifications"] = self.tui.multi_select_menu(
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"Select what you want to do", menu_options
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f"\n{self.name} v.{self.version} \nSelect what you want to do (esc or q to exit)",
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menu_options
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)
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if "Change EXIF" not in self.settings["modifications"]:
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self.settings["copy_exif"] = self.tui.yes_no_menu("Do you want to copy exif info from original file?")
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font = ImageFont.truetype("OpenDyslexic3-Regular.ttf", font_size)
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except:
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print("Error loading font for watermark, please ensure font is installed...\n")
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time.sleep(0.3)
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time.sleep(0.1)
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return image
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c, w, textwidth, textheight, = drawer.textbbox(xy = (0, 0), text = text, font = font) # Getting text size, only need the last two values
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x = imagewidth - textwidth - margin
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y = imageheight - textheight - margin
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drawer.text((x, y), text, font = font)
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# thin border
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drawer.text((x-1, y), text, font=font, fill=(64, 64, 64))
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drawer.text((x+1, y), text, font=font, fill=(64, 64, 64))
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drawer.text((x, y-1), text, font=font, fill=(64, 64, 64))
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drawer.text((x, y+1), text, font=font, fill=(64, 64, 64))
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# Adding text in the desired color
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drawer.text((x, y), text, font = font, fill=(255, 255, 255))
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return image
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