Similarity, Bursts, and Search

Similarity groups visually related frames into bursts and suggests strong candidates. It shortens review while leaving the final choice to you.

RawCull uses DataComp CLIP for visual grouping and semantic search. Install and enable it in Settings > AI before indexing a catalog.

Analyze a Catalog

1. Open Similarity.
2. Choose Analyze Bursts.
3. Open Needs Review when analysis finishes.

RawCull runs any missing sharpness scoring and CLIP indexing automatically. Use Re-index after the catalog changes or when you want to rebuild the analysis.

Re-index after updating DataComp CLIP or changing the catalog so RawCull can create compatible embeddings for every photo.

The similarity slider controls grouping: lower values make tighter groups; higher values include more related frames.

Review Bursts

Each group can include a suggested pick and supporting sharpness or subject information. Open a group to inspect its filmstrip, rate frames, defer the group, mark it reviewed, or open Compare for a closer view.

Use Set pick to override the suggestion. One-click Keep Best rates the suggested frame 3 stars and rejects the other frames; Keep Top Two rates the first two candidates 3 and 2 stars and rejects the rest. Review the suggestion before applying either action.

The main queues are:

Analysis results are cached for the catalog. Ratings and manual picks are saved with the rest of the culling data.

For deeper model-based review, select photographs in Grid View and open AI Analysis. SAM 3 and Qwen operate on the selected set rather than on every catalog photograph.

Semantic Search

After DataComp CLIP indexing finishes, enter a short English description such as bird in flight or backlit portrait. RawCull ranks the catalog by relative text-to-image similarity. The ranking is not a confidence score, so inspect the results before making culling decisions.