A GUI tool to pixelate images by averaging colors within an interactively adaptable grid.
Project description
adaptive-pixelizer
adaptive-pixelizer is a simple GUI tool to pixelate images by averaging colors within a user-defined grid. It's designed for easily converting high-resolution pixel art or photos into a low-resolution, dot-art style.
Features
- Interactive Grid Editing: Manually add, delete, and move grid lines directly on the image using mouse clicks and drags.
- Shift + Left Click: Add vertical line
- Shift + Right Click: Add horizontal line
- Ctrl + Click: Delete line under cursor
- Drag line: Move line
- Delete/Backspace: Delete line under cursor
- Zoom and Pan: Easily navigate large images. (Mouse wheel, Alt+Drag)
- Multiple Color Averaging Methods: Choose between Average, Median, or Mode color calculation for pixelation.
- Real-time Preview: See the pixelated result instantly (can be toggled on/off).
- Undo/Redo: Supports undo/redo for grid modifications.
- Simple Interface: Lightweight and easy to use.
Installation
You can install adaptive-pixelizer using pip:
pip install adaptive-pixelizer
Optional Dependencies:
For potentially faster median color calculation, NumPy is recommended:
pip install adaptive-pixelizer[numpy]
or just "pip install numpy" separately
Usage
-
Launch the application by typing the following command in your terminal:
adaptive-pixelizer
-
Click "画像ファイルを開く" (Open Image File) to load an image.
-
Adjust the grid lines on the left panel (original image):
- Use the initial grid spinboxes, or
- Use Shift+Click, Ctrl+Click, Drag, or Delete/Backspace key as described in Features.
-
Select the desired color calculation method (Average, Median, Mode).
-
The pixelated preview will update automatically on the right panel (if "プレビュー自動更新" is checked). Click "プレビュー更新 / 実行" to manually update.
-
Once satisfied, save the processed image using "ファイル" > "名前を付けて保存...".
Requirements
- Python 3.8 or later
- PyQt6
- Pillow
- NumPy (Optional, recommended for Median calculation)
- OS: Primarily tested on macOS, should work on Windows/Linux.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Contributing / Issues
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