Optimized hardware resource allocation scheme
The following optimization strategies can be used for cases where the GPU has insufficient memory or limited computing power:
- Chunking technology: Add -tile_size parameter to split the video into 512×512 chunks to significantly reduce the video memory usage.
- Precision Adjustment Program: change torch to fp16 version in requirements.txt, run command to add -half_precision parameter
- Cache reuse mechanism: For reused noise patterns, create a local cache repository with the -cache_noise parameter to avoid repeated computations
- Cloud Collaboration Solutions: perform GPU-intensive steps using cloud services like AWS Lambda or Colab after completing GUI editing locally
Contingency plan: When experiencing a video memory overflow, try lowering the resolution (-downsample 2), reducing the number of inference steps (-num_inference_steps 3), or turning off the real-time preview (-no_preview), in that order.
This answer comes from the articleGo-with-the-Flow: Controls the movement of objects in the video, adding or subtracting any moving objects in the video.The
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