AI Step by Step

RawCull uses three local AI models. Each has a different job:

In Deep Review, SAM 3 and CLIP work together. CLIP suggests what the subject is; SAM 3 uses that information to find the subject; RawCull then measures detail inside the mask. If CLIP cannot supply a useful label, SAM 3 can still use the general Subject prompt.

All three models run on the Mac. They advise you; they do not replace your decision. Before starting, install the models you want under Settings › AI; SAM 3 also requires acceptance of its licence.

Why analyze only a small set with AI?

CLIP runs quickly enough to index every photograph in the catalog for similarity and semantic search. Its cached embeddings can be reused without processing each image again for every search.

Detailed AI review is much heavier than ordinary thumbnail browsing. SAM 3 must create a subject mask for each photograph, while Qwen examines and describes one photograph at a time. Running both over every file would spend time on obvious rejects and repeated frames.

RawCull therefore uses a funnel:

1. Burst Review quickly reduces the complete catalog.
2. You keep a small set by selecting images or rating them with two or more stars.
3. AI Analysis gives those finalists a closer review.

This is both faster and more useful: AI spends its time on the difficult choices. For a SAM 3 + CLIP batch larger than 12 images, RawCull reviews at most eight candidates, using the available burst ranking or the current file order.

1. Begin with Burst Review

Open a catalog, go to Similarity, and choose Analyze Bursts. Open a group from Needs Review to compare its frames in the burst reviewer.

RawCull performs three steps:

1. Similarity: CLIP creates a numeric image embedding and groups near-duplicates. If CLIP is unavailable, RawCull can use Apple Vision for similarity instead.
2. Sharpness: RawCull measures focus and useful detail. This is traditional image analysis, not a generative AI opinion.
3. Ranking: similarity and sharpness evidence are combined to suggest the strongest frames in each burst.

Start with Needs review. Compare the best-ranked frames, check important details at a useful zoom level, and make your own decision. Select the remaining candidates in Grid View, or rate promising images with two or more stars so that they appear as Tagged images later.

2. Choose the finalists

Open AI Analysis from the toolbar. At the top right, choose one input:

• Selected uses the images currently selected in Grid View.
• Tagged uses every active-catalog image rated two stars or higher.

Keep this set small. A handful of close candidates is ideal.

3. Run SAM 3 + CLIP

Choose SAM 3 + CLIP, then select a review target:

• Auto lets the detected subject guide the mask.
• Full Subject checks detail across the complete subject.
• Head / Face concentrates on the area that often decides portraits and wildlife photographs.

Choose Run Deep Review. For each candidate, inspect the subject outline, the Deep score, the normal Sharp score, mask status, AF position, and any warning in Notes. A high score is useful only when the mask covers the subject you intended. If the outline is wrong, trust the photograph—not the number.

Use this review to answer: Which frame contains the best detail on the subject that matters?

4. Run Qwen Vision

Choose Qwen Vision. The default prompt asks about composition, exposure, subject visibility, expression, and obstructions. You may replace it with a specific question, for example: Which visible problems would matter in a final edit?

Choose Run Analyze. Qwen processes the pending images one at a time and returns scores plus strengths and issues. It may also report whether eyes are open when that can be judged from the image.

Use this review to answer: Does the photograph work as a photograph? Qwen adds a visual critique; it does not participate in burst similarity or SAM 3 subject-detail scoring.

5. Run AI Objects

Choose Objects and keep Selected or Tagged as the input. SAM 3 and Qwen must both show as ready.

1. Leave Concepts on Automatic for Qwen to suggest concrete subjects in each photograph. If you already know what to look for, choose Specific Concepts and enter short comma-separated terms such as puffin or deer, fawn.
2. Optionally edit the additional photographic criteria, then choose Analyze [number] Images to process the pending photos. You can cancel a running batch, retry failed results, or clear results from this view.
3. Select a completed row. Compare the numbered outlines with the original image, then choose an object in the list to inspect its crop and Qwen description. The table also shows discovered concepts, object count, Qwen assessment confidence, and status.
4. Read the whole-photo summary, per-object visibility and focus notes, relationships, strengths, and problems. Treat the SAM 3 mask score and Qwen assessment confidence as different signals. Check the crop, outline, and wording against the source photo; small or overlapping subjects can be missed or mixed up.

Objects is useful when a frame contains several subjects, such as a deer with fawns or a group of musk oxen. Its numbered crops help you inspect each subject, but the analysis remains advisory. It does not rate, reject, or select a photograph for you.

6. Make the final choice

Use each result to answer a different question:

• Your visual judgment: does the pose, timing, and framing match your intent?
• SAM 3 + CLIP: is the intended subject masked correctly, and which candidate has useful subject detail?
• Objects: are the individual subjects visible, and do their outlines and crops match the photograph?
• Qwen Vision: which composition or visibility issues deserve a closer look?
• Burst Review: which neighboring frames are worth comparing before you decide?

When the signals disagree, inspect the original preview at a useful zoom level. Focus-map overlap and model confidence do not prove sharpness or photographic quality. Ratings and final picks remain your decision; RawCull does not automatically turn a Qwen result into a rating.

For catalog grouping, see Similarity, Bursts, and Search. For models and downloads, see AI Analysis. The AI Screenshots tour shows the results in each tab.