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This repository provides a collection of machine learning-based nodes designed to enhance the rigging and animation workflows in Autodesk Maya. Aimed at educators, developers, and artists, it offers practical examples of integrating machine learning techniques into Maya's environment to streamline various processes.
Each node is designed with simplicity in mind, focusing on practical use cases such as linear regression, PCA for blendshapes, and other useful applications for rigging and animation. The goal is to provide a framework for experimentation, learning, and extending the capabilities of Maya through machine learning.
The nodes and tools implemented in this repository are primarily focused on education rather than performance. This is why all nodes are written in Python, ensuring they are easy to read, understand, and modify. The code is intentionally kept simple and free from optimizations that might make it harder to follow. This approach allows educators, students, and developers to focus on learning the core concepts of machine learning and its integration into Maya, without being overwhelmed by complex or highly optimized code.
Explore the nodes, contribute, or customize them for your own projects to enhance your Maya workflows with the power of machine learning!
This project is open-source and licensed under the MIT License.
If you encounter issues or have suggestions, feel free to create an issue on GitHub or contact me directly on Blue Sky