🐳 Docker Cache Optimization & Configuration Enhancement #80
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- Set up PyTorch 2.2.2 with CUDA 12.1 support - Install system dependencies and conda packages - Configure Python environment with required libraries - Prepare for headless OpenCV operation
- Define 'hallo2' service with CUDA support - Set up volume mapping for local development - Configure GPU resource allocation
- Specify versions for key libraries including PyTorch, diffusers, and transformers - Include development tools like isort, pylint, and pre-commit - Add Gradio for potential GUI applications
- Ensure consistent file ending in video utility module
- Create VideoWriter class for FFmpeg-based video encoding - Add test function to generate sample video with moving circle - Provide visual verification of video processing capabilities
• Add driving audio sample 6.wav for voice synthesis • Add reference image 7.jpg for face animation • Expand example dataset for improved testing coverage
• Add cache/ and .cache/ to gitignore patterns • Prevent caching artifacts from being tracked • Enhance repository cleanliness and performance
• Add cache volume mount in docker-compose.yml for improved performance • Pin huggingface_hub version to 0.20.3 for stability • Optimize dependency management and caching strategy
• Convert Japanese comments to English for better internationalization • Streamline package installation with force-reinstall flag • Remove redundant OpenCV installation steps • Improve build efficiency and maintainability
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🚀 Overview
This PR optimizes Docker configuration and enhances caching capabilities for improved development experience.
✨ Changes
🛠️ Technical Details
🧪 Testing