remove-ai-watermarks/data/jimeng_capture/README.md

Jimeng (即梦AI) visible watermark capture

Status (completed 2026-05-30): solid black/gray/white Jimeng captures were obtained (issue #13, from @powersee) and the alpha map was solved. Removal is reverse-alpha plus a residual inpaint over the glyph footprint; see the jimeng_engine.py notes in the root CLAUDE.md. The text below is kept as the capture plan.

Goal: capture the Jimeng / Dreamina "★ 即梦AI" visible wordmark over known flat backgrounds so we can build a per-pixel alpha map and a reverse-alpha remover, the same way the Gemini sparkle and Doubao strip engines work (src/remove_ai_watermarks/gemini_engine.py, doubao_engine.py).

What we learned (verified from the captures, 2026-05-30)

• Mark: a four-point sparkle icon followed by the "即梦AI" characters, near-white semi-transparent overlay, bottom-right corner.
• Blend model: alpha compositing with a pure-white logo watermarked = a*255 + (1-a)*original, confirmed in sRGB (a linear-light solve made the black/gray cross-residual much worse, so the compositing is plain sRGB). An L-pair-solve (independent of the L assumption) lands at ~254.6, confirming white.
• Alpha is solved from the GRAY capture, not black: a = (I - B)/(255 - B) with B a per-capture CUBIC background fit over the non-glyph pixels, averaged over channels, at FULL halo extent (down to a~0.02) and UNBLURRED. Gray (bg ~132) is the best proxy for real content (the mark sits on bright photo areas, not on black). This careful build drops the gray self-residual to ~1.3; an earlier max-channel / quadratic-bg / blurred / halo-truncated build (and a black-dominated least-squares solve) left a visible outline -- the mask quality, not the method, was the limit.
• Geometry (fraction of image WIDTH, at the captured 2048): asset width ~0.211, height ~0.068, right margin ~0.023, bottom margin ~0.023. The mark scales with width; a real 1440-wide download matched width_frac ~0.21.
• Per-image render variation: the alpha maps solved independently from the black and the gray capture correlate 0.998 but not 1.0 (mean |Δa| ~0.02). Jimeng re-rasterizes the mark per generation AND jitters its position a few px, so a single alpha map does NOT pixel-cancel the mark the way Doubao's deterministic overlay does. Removal therefore: NCC-aligns the alpha to the actual mark (always, not only off-native), reverse-alphas, then clears the residual with a THIN inpaint over the glyph footprint (a wide full-footprint pass smeared the texture/edges).

How to capture (image-edit path, most reliable)

For each solid-color seed:

1. Open Jimeng image generation, use the image-edit / reference mode, upload the seed.
2. Prompt (Chinese preferred): 请完全按照原图重新生成这张图片，保持完全一致，不要添加或修改任何内容
3. Download the ORIGINAL output file (not a screenshot). Do not crop / edit / re-save.

The black capture is the key one (white logo on black -> captured ~= a*255); the gray capture refines the alpha at mid-tones; the white capture confirms the logo is pure white (the mark is nearly invisible on white, as expected).

Hygiene

• Original download, never a screenshot. PNG preferred; if Jimeng only gives JPEG, note it.
• No crop / edit / re-save. Default settings, watermark left ON.

Naming, drop into captures/

jimeng_cap_A.png   # black seed run through Jimeng
jimeng_cap_B.png   # white seed
jimeng_cap_C.png   # gray seed
jimeng_content_1.png  # a normal-content download, for end-to-end validation

The solid jimeng_cap_{A,B,C}.png captures are committed (content-free: a solid colour + the watermark; the source for scripts/visible_alpha_solve.py jimeng). The synthetic seeds/ and the real-content jimeng_content_*.png validation download are gitignored (local-only). Rebuild the alpha asset with:

uv run python scripts/visible_alpha_solve.py jimeng   # or: all