Synfig

Mentors: Student: ahmedfathy0-0

Currently, Synfig artists rely on complex skeleton rigging to achieve organic deformations like squash-and-stretch or facial movements. This project introduces a 2D Free-Form Deformation (FFD) layer, allowing users to intuitively warp artwork using a manipulatable control grid (lattice) instead of bones. The implementation involves creating the core deformation math engine (upgrading from Bilinear to Catmull-Rom spline interpolation for C1 continuity), integrating the grid points with Synfig's Duckmatic UI system .

Mentors: Student: Yukta

This project introduces native per-character text animation support in Synfig. Currently, text is rendered as a single shape, making effects like staggered animation, typewriter effects, or per-letter transforms difficult without workarounds. The proposed solution decomposes text into glyph-level elements and enables independent animation of position, rotation, scale, color, and opacity for each character. A reusable stagger engine will be implemented to support delayed animations across characters, with a design that can be extended to general group-based animation in the future. The project will deliver new layer types for glyph-based rendering, full integration with Synfig’s animation system, UI support, file format compatibility, and user documentation.

Mentors: Student: Nitish Itankar

The current macOS app bundle creation process for Synfig relies on an outdated Bash script that is slow, error-prone with incorrect paths, and lacks code signing, hindering efficient distribution and user trust. This project aims to replace the script with a robust, automated solution to streamline bundle generation, ensure macOS security compliance, and enhance the native user experience. By leveraging Python for dependency collection, C++ for environment setup, and CMake/CPack for packaging, the project will deliver a signed, distributable SynfigStudio.app bundle. Key improvements include faster dependency gathering, proper code signing, embedded environment setup, Python/lxml integration, and macOS-native interface enhancements. Approach: • Develop a Python script to efficiently collect and stage dependencies, optimizing with caching and parallelization. • Implement code signing in reverse dependency order using codesign, including Python and lxml binaries. • Remove the external launcher script by embedding environment setup in the C++ entry point. • Package Python and lxml into the bundle, ensuring compatibility and signing. • Integrate CPack into CMake to generate a polished .dmg installer. • Enhance the UI with macOS-native menu bar and window behaviours using GTK. Deliverables: • A CMake/CPack-based build system producing a signed SynfigStudio.app bundle. • A Python script for automated dependency collection and path rewriting. • Code signing support for all binaries, including Python and lxml. • Embedded environment setup within SynfigStudio, eliminating the launcher script. • A bundled Python runtime with lxml, fully signed and functional. • A distributable .dmg installer generated via CPack. • macOS-native UI improvements (e.g., menu bar, shortcuts, dialogs boxes). • Comprehensive documentation covering installation, usage, and build instructions.

Mentors: Student: Abdelhadi Wael

This project will deliver a performant integrated Raster Brush Tool alongside a basic Brush Profile Editor. The core implementation uses a real-time overlay preview for smooth interaction and a robust atomic command structure enabling multiple user-selectable undo modes. Key deliverables include the core draw/erase tool, the editor for viewing/modifying key brush parameters , support for standard brush presets and parameters , reliable undo functionality across implemented modes, and fully animatable raster output integrated into synfig.

Mentors: Student: Ahmed Khaled (Akayiz)

This project aims to improve and automate the generation of release notes for Synfig and make Synfig easier for Linux users to download. This is done by: 1—Creating a script that uses Synfig's repository git conventional commits history to automatically generate nice-looking Synfig release notes grouped by change type (fix, feature, etc.), automatically adding them to new GitHub releases, and showing contributors using a GitHub bot how their pull requests will affect the release notes when merged. This aims to enhance the pull requests and release notes descriptions and give Synfig’s pull requests a more professional feel to attract more contributors. 2—Currently, Synfig is bundled to work on Linux using AppImage v1.0 complicated scripts. AppImage v1.0 is outdated and has the critical issue that it doesn’t work smoothly on newer systems (Ubuntu v22.04 and others); the AppImage scripts will be updated to use the latest AppImage version to run smoothly on old as well as newer Linux distributions.