Atelierparser

Description

Atelierparser is a Python tool that makes it easy to turn images into Supernote Atelier-friendly .spd files.
With this tool, you can import any image as a background layer in Atelier, This opens up possibilities for image tracing, using custom templates, grids, and much more.

Features

• Convert any image (e.g., PNG, JPG, BMP, GIF, WebP) to an .spd file.
• Preview images before convertion.
• Simple drag-and-drop functionality.
• Automatic alignment for consistent template formatting.

This project has now be superseded by the superior Atelier-Companion https://github.com/Ziv-Ink/Atelier-Companion

Requirements

The executable is standalone and has no requirements—just download and run! If you prefer to run the Python script rather than the .exe, you will need the following dependencies:

• Python 3.7+
• Pillow (PIL)
• TkinterDnD2
• Tkinter
• sqlite3

You can install the required dependencies using pip:

pip install pillow tk tkinterdnd2

Installation

For the Precompiled Executable

Simply download the executable from the release section. No installation is required—just run the executable. After saving the .spd file, move it to the tablet and open it using Atelier.

For Running the Python Version

1. Clone or download the repository.
2. Install the dependencies listed in the "Requirements" section.
3. Run the script:

python atelierparser.py

Usage

1. Open the Program: Launch the executable or run the Python script as described above.
2. Select an Image: Drag and drop an image into the window or use the "Browse" button to select an image from your filesystem.
3. Preview and Confirm: After selecting an image, a preview will be displayed. Click "Confirm" to proceed.
4. Save the .spd File: Choose a location to save the .spd file.
5. Transfer the .spd File: After saving the .spd file, move it to the tablet and open it using Atelier.

License

This project is licensed under the Apache License 2.0. You may use, distribute, and modify this project under the terms of the license. See the LICENSE file for full details.

Acknowledgments

The project utilizes the Pillow library for image processing and TkinterDnD2 for drag-and-drop functionality. Special thanks to the Supernote community for their support and feedback on all my projects, with special thanks to @mmujynya for his support and development of PySN. Additionally, I would like to thank the Supernote team for all their hard work and dedication to the community.