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Multi-video corpus indexing and cross-video search
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Basierend auf der SOC-Berufsklassifikation
Compositional pixel analysis patterns using kuavi_eval for counting, motion detection, change tracking, and visual comparison. Use when questions require precise measurements, object counting, or frame-by-frame comparison.
Full end-to-end video analysis with KUAVi
Deep multi-pass video analysis with parallel sharding and zoom
Multi-pass search with query refinement for hard-to-find video content. Use when initial search returns low-confidence results or no matches.
Index a video file for KUAVi analysis
Predictive video understanding — anticipate actions, predict future content, verify coherence, classify activities
| name | kuavi-corpus |
| description | Multi-video corpus indexing and cross-video search |
Index and search across multiple videos simultaneously.
Index multiple videos in parallel for cross-video search.
kuavi_index_corpus(video_paths=["/path/to/video1.mp4", "/path/to/video2.mp4"])
Semantic search across all videos in the corpus.
kuavi_search_corpus(query="person presenting slides", field="summary", top_k=10)
Get statistics about the current corpus.
kuavi_corpus_stats()
Returns: video count, total segments, total duration, action vocabulary.
kuavi_index_corpus(video_paths=[...]) to build the corpuskuavi_search_corpus(query="topic X") to find relevant segments across videoskuavi_corpus_stats() to get action vocabularykuavi_search_corpus(query="common action", field="action") across all videos