Creating a custom ML model for integration into a Blender add-on

Creating a custom ML model for integration into a Blender add-on is a comprehensive process. Below are detailed step-by-step instructions, starting from installation to deployment and integration. 1. Environment Setup Install Required Tools Python: Install Python (>=3.8). Recommended version: Python 3.9. Libraries: Install key libraries: pip install numpy pandas matplotlib torch torchvision tensorflow librosa phonemizer Install Blender's Python Dependencies Blender uses its own Python version. Add required libraries: 1. Locate Blender's Python path: Example: C:\Program Files\Blender Foundation\Blender 3.x\3.x\python\bin 2. Open a terminal in this directory: ./python.exe -m ensurepip ./python.exe -m pip install numpy pandas torch librosa phonemizer Install Jupyter Notebook (Optional) For an interactive data preparation and training environment: pip install notebook 2. Collect Data Dataset Example For lip-syncing, use datasets like: LibriSpeech: Speech audio with transcripts...

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2. SEO Question and answer:

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