72 lines
2.4 KiB
Markdown
72 lines
2.4 KiB
Markdown
# Atlas Refine Baseline Deck Analysis
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Date: 2026-07-01
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Folder:
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`/media/unraid/comfyui/output/CodexMCP-Atlas-Refine`
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Subject id:
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`atlas_refine_same_woman_001`
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## Folder State
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The folder contains 16 complete `.png` / `.txt` atlas prompt pairs.
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Coverage report:
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- 10 clean `baseline_only` entries
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- 6 `needs_prompt_cleanup` entries
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- 0 sidecar prompt variants
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- 0 seedable catalog cue candidates
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- 0 missing image/text pairs
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The deck is useful as a controlled same-woman baseline set, not yet as a
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seed/cue system. Reviewed sidecar variants still need to be authored from
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actual prompt/image evidence.
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## Prompt Cleanup Queue
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These baseline prompts still contain positive-channel negative wording through
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`without` and should be rewritten before visual scoring or seed promotion:
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- `pov_cowgirl_alt_low_squat_penetration`
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- `pov_cowgirl_frontal_straddle_penetration`
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- `pov_ejaculation_aftermath_open_thigh_candidate`
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- `pov_handjob_upright_centered`
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- `pov_reverse_cowgirl_alt_upright_back_facing_penetration`
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- `pov_reverse_cowgirl_back_facing_penetration`
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## Visual Deck Read
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The deck is strong for same-subject comparison:
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- the woman identity is stable across poses;
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- the coworking lounge style is consistent;
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- desk rows, laptops, chair wheels, plants, glass partitions, and warm window
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depth are repeated enough to support workspace-continuity scoring;
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- most poses place the action as the primary foreground subject.
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Current limitations:
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- all entries are single baseline images, so they do not test seedable
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alternatives yet;
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- several prompts still use cleanup-needed wording;
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- clothing/control is not represented across most poses;
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- workspace interaction is mostly background context, not varied physical use
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of the lounge furniture;
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- exact top-view oral remains weak under text-only prompting even after the
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second MCP batch.
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## Next Evidence Priorities
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1. Clean the six `without` prompts before using them for cue seeds.
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2. Build prompt-variant sidecars only from tested cues, not invented wording.
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3. For each pose family, collect same-subject fixed-seed variants before
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touching generator defaults.
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4. Score scene/pose height from background cues: floor plane, desk height,
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chair wheels, table bases, and whether the viewer/partner appears standing,
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seated, kneeling, reclined, or supported by furniture.
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5. Keep clothing restore as woman-owned visible detail, and only for garments
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that the pose crop can actually show.
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