Hardware Adaptation Performance Optimization Guide
The following hierarchical optimization strategies can be used for different hardware configurations:
- High-end GPU solutions(RTX 3080+):
- Enable all enhancements:
--enhancer face --use_DAIN - exist
inference.pyset up inbatch_size=8accelerated processing
- Enable all enhancements:
- Mid-range GPU solutions(GTX 1660 class):
- utilization
--enhancer lipInstead of full face enhancement - commander-in-chief (military)
--time_stepReduce the amount of frame interpolation calculations by adjusting to 0.6
- utilization
- CPU-only environment::
- Install the CPU version of PyTorch:
pip install torch==1.12.1+cpu - Disables all enhancement parameters:
--enhancer none --no_DAIN - modifications
src/config.pyhit the nail on the headworkers=1
- Install the CPU version of PyTorch:
For laptop users, it is recommended to add--preprocess cropparameter handles only the face region. When running in the Colab environment, the!nvidia-smiMonitor video memory usage and reduce output resolution if necessary.
This answer comes from the articleSVLS: SadTalker Enhanced to Generate Digital People Using Portrait VideoThe
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