RVC-Project / RVC-Project/Retrieval-based-Voice-Conversion-WebUI
[Feature request] Automatic batch processing of long files on harvest for limited RAM machines
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- Dominant language
- Python
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Description
A common complaint from Google Colab users is harvest being unusable without manually splitting their song into parts. I wonder if an argument in the command to run python infer-web.py could be used to forcefully do it in batches so that it still exports without erroring out? If not that, splitting the song into ~30s intervals that cut off at silence and then stitching them together to serve a complete wav?
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First steps
- Read the whole issue, then the project's contributing guide.
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Research direction
Start by reading the harvest path in infer-web.py and reproduce the long-file failure on a limited-RAM environment such as Google Colab. Determine whether batching or silence-based splitting is feasible, then verify that a complete WAV exports without requiring manual splitting.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100