facefusion

• Perform VRAM clearance after each processing step
• Restrict TensorFlow memory consumption to 512 MB
• Verify the model files before frame processing
• Introduce --skip-download to skip automated downloads
• Upgrade to the most recent onnxruntime version

• Perform VRAM clearance after each processing step
• Restrict TensorFlow memory consumption to 512 MB
• Verify the model files before frame processing
• Introduce --skip-download to skip automated downloads
• Upgrade to the most recent onnxruntime version

• Establish REALTIME webcam performance
• Optimize reruns by caching the face analyser results
• Optimize image read performance through caching
• Resume interrupted asset and model downloads
• Allow passing --onnxruntime to install.py
• Introduce official facefusion-colab repository
• Remove alignments from each UI components
• Introduce checkbox group for the settings
• Set webcam resolution and fps in the UI
• Disallow empty execution providers in the UI
• Fix frame range processing on videos with audio
• Fix CUDA and ROCM Dockerfile to utilize the GPU
• Fix sorting of temp frame paths

• Installer for common and acceleration dependencies
• Built-in webcam suite that supports udp and v4l2 streaming
• Dedicated --headless mode
• Add Docker support for ROCM
• Allow adjustment of --output-path via the UI
• Enhance output path normalization
• Single warm-up before starting the benchmark suite
• Ability to select runs for the benchmark suite
• Enable benchmarking with partial updates
• Implement a fully event-driven UI for super responsiveness
• Add a max memory slider to select free RAM
• Implement conditional UI based on target media type
• Introduce --output-image-quality option for image output
• Fix crf range for libvpx video encoder
• Fix detect_fps to work with different encoding

Initial release