Processing speed can be optimized in the following ways:
- GPU acceleration: After configuring the CUDA environment, the system automatically uses NVIDIA graphics cards to accelerate CV/ML computation tasks.
- Adjustment of concurrency parameters: Add the number of threads/processes in config.yaml to fully utilize multi-core CPUs.
- Segment size optimization: Adjust the video slice size (default 10MB) according to the hardware performance to balance the memory consumption and processing efficiency.
- Cloud Services Deployment: Deploy API services on high-performance cloud servers to avoid local hardware limitations.
Note: The actual speed is also affected by video resolution, complexity of special effects, and other factors.
This answer comes from the articleAi-movie-clip: an AI-driven automated video editing toolThe
May not be reproduced without permission:AI productivity tools " How to improve the video processing speed of Ai-movie-clip?
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