Help Cull Photos

Help: Cull Photos (beta)

Beta feature. Culling results are useful as a starting point but should be treated as suggestions, not final decisions. Always review Picks and Reject Candidates before deleting anything. No photos are ever deleted automatically.

What the culling workflow does

The Cull Photos workflow groups similar photos (bursts and near-duplicates), ranks them using technical and face-aware metrics, and creates Lightroom collections so you can quickly review:

• Picks – best candidates per group
• Alternates – reasonable alternatives you might still keep
• Reject Candidates – clearly weaker shots
• optional Duplicates / Near Duplicates
• Brackets / Stacks / Panoramas (keep all) – see below

No photos are deleted automatically. All results are non-destructive and shown via collections.

Sets that must not be culled

An exposure bracket, a focus stack and a panorama all look like a burst to a grouper: same framing, seconds apart, near-identical. But there is no keeper to pick — every frame is part of one picture, and rejecting four of five destroys the shot. The backend detects these sets and switches ranking off for them: no winner, no reject candidates, and the whole group goes to the Brackets / Stacks / Panoramas (keep all) collection instead.

Detection is deliberately cautious and needs corroborating evidence from more than one signal, so it can miss a set rather than misread an ordinary burst. Exposure-bracket detection reads the exposure compensation value from your photos, so it works best on frames shot with AEB.

Prerequisites

• The backend server is running and reachable from Lightroom.
• The photos have been processed with Analyze & Index Photos so the backend has embeddings and culling metrics for them.

How to run culling

1. In Lightroom Classic, select the photos you want to cull or switch to a filtered view (for example a single shoot or folder).
2. Open the menu:
   Library → Plug-in Extras → Cull Similar Photos....
3. Choose:
   • Apply to – Selected photos only or Current view.
   • Burst time window (seconds) – how far apart two frames may be and still count as the same burst.
   • Culling preset – tunes thresholds and weights: Default (balanced), Portrait (face-focused), Street (technical-focused), Event (people + moments), Sports (motion-tolerant).
   • Create 'Duplicates / Near Duplicates' collection – on by default.
4. Start the task and wait until the progress dialog completes.

The plugin calls the backend culling endpoint, which:

• groups photos into similarity clusters (single, burst, near_duplicate, and the keep-all types bracket, focus_stack, panorama)
• scores each image per group
• selects winners, alternates, and reject candidates — except in keep-all groups

Result collections in Lightroom

For each culling run, the plugin creates a new collection set:

• Name: Culling Results @ <timestamp>
• Contents:
  • Picks
  • Alternates
  • Reject Candidates
  • optional Duplicates / Near Duplicates

After creation, Lightroom automatically switches to the Picks collection inside that set so you can start your review immediately.

You can safely rename or move these collections later; they are standard Lightroom collections.

Understanding scores and explanations

For each photo, the backend stores culling-related fields such as:

• group information: cull_group_id, cull_group_type, cull_group_rank, cull_group_winner
• technical scores: cull_sharpness, cull_sharpness_peak, cull_exposure, cull_highlight_clip, cull_shadow_clip, cull_noise, cull_motion_anisotropy (camera shake vs. subject motion), cull_sharp_region_x / cull_sharp_region_y (where in the frame the sharpness actually sits, so a sharp background does not win over a sharp subject)
• face scores: cull_face_score, cull_face_count, cull_face_sharpness, cull_face_prominence, cull_face_visibility, cull_eye_openness, cull_blink_penalty, cull_occlusion
• aesthetic scores: cull_aesthetic, cull_aesthetic_iqa, cull_semantic_iqa
• explanations: cull_reason_codes, cull_explanation

The plugin writes a subset of these values into plugin-specific metadata fields on each photo so they can be inspected or used for diagnostics.

Typical reason codes include:

• sharpest_in_group
• blurred
• underexposed / overexposed
• best_face_quality / weak_face_quality
• eyes_open_best
• possible_blink
• possible_occlusion
• no_face_detected_in_group
• near_duplicate_weaker
• bracket_frame_kept / focus_stack_frame_kept / panorama_frame_kept

These help explain why a specific frame was chosen as a pick or flagged as a reject candidate.

"Some culling signals are missing"

When the selected photos have no culling data yet, the plugin offers to prepare them — a fast pass that computes only what culling reads. It never runs a language model, so when the backend is on this machine it hands over a group of photos at a time and they are read and measured across several CPU cores rather than one after another. If a signal could not be computed, the plugin says so before the culling run starts instead of quietly grading photos without it. The usual cause is that the on-device models are not downloaded yet: open File → Plug-in Manager → LrGeniusAI and press Download AI models, then run culling again. Culling still works in the meantime, but face-aware ranking (eyes open, sharpness, occlusion) is inactive.

Tips for best results

• Run culling after you have narrowed down an initial selection for a shoot (for example by folder or date range).
• Use Analyze & Index Photos with face detection enabled if you want face-aware ranking (eyes open, sharpness, occlusion).
• Start with conservative presets (default) and treat the result as a review aid, not an automatic delete list.