chore(release): v0.9.0

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>

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "remove-ai-watermarks"
-version = "0.8.9"
+version = "0.9.0"
 description = "Remove visible and invisible AI watermarks from images (Gemini / Nano Banana, ChatGPT, Stable Diffusion)"
 readme = "README.md"
 requires-python = ">=3.10"

src/remove_ai_watermarks/__init__.py

@@ -11,4 +11,4 @@ _os.environ.setdefault("TRANSFORMERS_VERBOSITY", "error")
 _warnings.filterwarnings("ignore", message=r".*ImageProcessorFast.*")
 
 
-__version__ = "0.8.9"
+__version__ = "0.9.0"

uv.lock

@@ -2243,7 +2243,7 @@ wheels = [
 
 [[package]]
 name = "remove-ai-watermarks"
-version = "0.8.9"
+version = "0.9.0"
 source = { editable = "." }
 dependencies = [
     { name = "click" },