Open-Sora provides three core optimizations to improve generation quality:
- detailed descriptive method:: Suggest specific, vivid descriptors, for example, optimize "sea" to "dark blue sea in a storm, white waves slamming against black reefs, lightning flashing through dark clouds".
- GPT-4o Assisted Optimization: The system has a built-in interface to the GPT-4o, which can be set up by
OPENAI_API_KEYPost-enable automatic cue word optimization:export OPENAI_API_KEY=sk-xxxx torchrun ... --refine-prompt True
- Dynamic scoring adjustment: By
--motion-scoreParameters (range 1-7) control the degree of dynamics of the screen, for example, setting 7 can generate more dramatic movement effects.
Additional optimization suggestions include:
- The text-to-image-to-video process is usually of higher quality than direct text-to-video
- For complex scenes, it is recommended to check the effect of the 256p version before generating the HD version.
- utilization
--offload Trueparameter to enable memory optimization when graphics memory is low
This answer comes from the articleOpen Sora: An Open Source Video Generation Tool for Optimizing Face ConsistencyThe
May not be reproduced without permission:AI productivity tools " How to improve the quality of Open-Sora's video generation through cue word optimization?
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