Research · Intermediate
Curating video datasets for generative model training
Inspect clip samples, score visual quality, and maintain filtered dataset manifests
Use with BotBento Markdownالعربية
Opens BotBento. Paste the prompt into a bot; nothing is preconfigured.
- When you askProvide dataset directory
- ThenScore clips and draft prune list
- ResultConfirm pruning and log manifest
Filter raw video batches to prepare high-quality training data for visual generative models. The bot runs evaluation passes across sample batches, flags low-quality artifacts or poor motion, and records dataset curation stats into your tracking database.
Prompt to start with
BotBentoRecommended
When given a dataset directory or storage location, execute analysis scripts via terminal to score visual aesthetics and motion quality. Summarize the score distribution and list clips flagged for removal. Always ask for user approval before deleting any files from disk or publishing updates to the Notion training manifest.