- Replace reverse-alpha removal with localize -> fill (template-free mask + one
shared cv2/MI-GAN/big-LaMa fill) for every mark; drops the colour-shift / dark-pit
failure modes, version-robust to a moved or re-rendered mark
- Separate perception/decision/action: engines report Candidates, a pure
decide(candidates, Context) arbiter owns all policy (sensitivity + provenance +
pill gate), remove_auto_marks orchestrates -- behavior-preserving (corpus 46/46/92)
- Three orthogonal knobs replace --method: --backend cv2|migan|lama,
--sensitivity auto|strict|assume-ai, provenance (auto from metadata)
- Add high-level api.remove_visible / visible_provenance (lazy top-level re-export);
visible --mark auto delegates to it so CLI and library share ONE path
- Read+write HEIC/AVIF on the pixel path via pillow-heif; imwrite preserves the input
format at max quality (JPEG q100/4:4:4); a no-op copies the original bytes verbatim
- Lossless byte-level JPEG metadata strip (no DCT re-encode); consolidate the two
remove_ai_metadata into one, delete legacy noai/cleaner + best_auto_mark
- Bump 0.13.0 -> 0.14.0
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
- Add the Jimeng-basic top-left "AI生成" pill as a CAPTURE-LESS mark
(pill_engine.py): synthetic-silhouette edge-NCC detect + inpaint-only removal.
Gated in remove_auto_marks: kept only when Jimeng is confirmed (TC260 metadata
OR the bottom-right "★ 即梦AI" wordmark fired -- the wordmark keeps recall on
metadata-STRIPPED uploads) AND Doubao did not fire.
- Add an inpaint-fallback removal path + MI-GAN ONNX backend (migan extra, MIT,
~28 MB / ~1 GB peak -- droplet-friendly) alongside big-LaMa. New
--method auto|reverse-alpha|inpaint (shared across visible/all/batch) and
erase --backend migan; footprint_mask on each engine.
- auto is deterministic: reverse-alpha for capture marks (recovers exact pixels,
lighter -- measured cleaner than MI-GAN on structured backgrounds) and inpaint
only for the capture-less pill.
- --mark auto now removes EVERY detected mark in one pass (remove_auto_marks),
so a Jimeng-basic image's top-left pill AND bottom-right wordmark both clear.
- Bump 0.12.1 -> 0.13.0.
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
BREAKING:
- Drop `--restore-faces` / `--restore-faces-method` CLI flags
- Drop `restore`, `photomaker`, `instantid` extras
- Drop `restore_faces` / `restore_faces_method` params from
InvisibleEngine.remove_watermark and AutoConfig
Rationale (full empirical record in
docs/synthid-robust-identity-research-2026-06-08.md "Empirical follow-up"):
every face-restore approach evaluated 2026-06-04 - 2026-06-08 (GFPGAN-on-
cleaned, PhotoMaker-V2, InstantID txt2img, InstantID img2img-on-cleaned
at three parameter sweeps) regenerates the face via SDXL diffusion --
output face pixels are diffusion-fresh, so the regenerated face inherits
SDXL's "clean skin" aesthetic and loses original identity precision. The
result looks MORE AI-generated than the cleaned image, not less. The
cleaned controlnet 0.20 image is the least-AI face state we can reach
without re-introducing SynthID.
License:
- MIT -> Apache 2.0 (Apache adds an explicit patent grant + trademark
clause; better fit with the upstream Apache projects this library
mirrors / depends on -- diffusers, transformers, controlnet-aux,
xinsir's controlnet weights)
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The 256px limit caused misses when Gemini places the sparkle further from the
corner than the standard 160px (margin 64 + logo 96). Observed variant at ~300px
reported in issue #30. 512px covers all known Gemini margin variations with room
to spare; matchTemplate on a 512x512 region is still fast on CPU.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
cli.py now emits plain ASCII through a small click.echo shim
(_Console / _Table / _Progress) instead of rich: no colors, markup tags,
panels, progress bar, or Unicode glyphs (Warning: / -> / ... and dropped
checkmark/cross marks). identify and metadata tables render as indented
plain lines.
- drop rich from dependencies (pyproject.toml + uv.lock)
- __init__: set TRANSFORMERS_VERBOSITY=error (setdefault) plus a warnings
filter so the transformers Siglip2ImageProcessorFast deprecation no
longer prints at CLI startup (it fires from the eager noai import)
- TestGpuHintMarkup: the [gpu] hint is now printed verbatim; docstring updated
- CLAUDE.md: replace the obsolete rich-markup lesson, note the verbosity fix
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The 0.8.0 PyPI publish uploaded the wheel but the sdist was rejected
(400 File too large): hatchling's default sdist bundled the committed
data/ test corpora (synthid_corpus images + the new visible-mark
captures), pushing it past PyPI's per-project file-size limit. Add a
sdist target that excludes /data, dropping it ~85 MB -> 9.8 MB. The
wheel already ships only src/ and is unaffected.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
