docs(auto): drop stale face-restore mentions from --auto

The face-restore family was removed in 20d7eda, but the auto_config
module docstring still claimed "PhotoMaker face restoration is enabled
when a face is present" and the --auto help text (CLI + README example)
listed "face restore" as something --auto picks. A detected face now
only routes to the controlnet pipeline (canny preserves face STRUCTURE,
not identity); there is no identity restoration. Comments/docstrings/help
only, no code behavior change.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

README.md

@@ -294,7 +294,7 @@ remove-ai-watermarks invisible image.png -o clean.png --humanize 4.0 --unsharp 0
 # GPU/MPS, cap the long side: --max-resolution 2048
 # Strength is vendor-adaptive by default (OpenAI 0.10 / Google 0.15); override
 # with --strength. To preserve text/face structure, use --pipeline controlnet
-# Or let it choose: --auto picks the pipeline, face restore, and an adaptive polish
+# Or let it choose: --auto picks the pipeline and an adaptive polish
 # from the image content (controlnet when there is text/structure, polish that
 # restores the input's detail level while sparing text). Every choice is
 # overridable: --pipeline and --no-adaptive-polish win over the auto pick.

src/remove_ai_watermarks/auto_config.py

@@ -8,11 +8,14 @@ host (image work there OOM-crashes the container).
 
 Routing is **quality-priority**: ControlNet (text/face-structure preservation) is the
 default; it is only skipped for a clearly structure-less image (no face, no text,
-near-zero edges), where plain SDXL is cheaper and just as good. PhotoMaker face
-restoration is enabled when a face is present. When a smoothing pass (controlnet or
-face restore) ran, the **adaptive polish** (``humanizer.adaptive_polish``) restores
-the input's detail level -- a capped unsharp + edge-masked grain targeting the input's
-Laplacian variance -- to counter the over-smoothed "AI look". It is self-limiting on
+near-zero edges), where plain SDXL is cheaper and just as good. A detected face only
+routes to controlnet (canny preserves face STRUCTURE, not identity); there is no
+identity restoration -- the whole face-restore family was removed (it regenerated the
+face via SDXL and looked MORE AI-generated, see
+docs/synthid-robust-identity-research-2026-06-08.md). When the controlnet smoothing
+pass ran, the **adaptive polish** (``humanizer.adaptive_polish``) restores the input's
+detail level -- a capped unsharp + edge-masked grain targeting the input's Laplacian
+variance -- to counter the over-smoothed "AI look". It is self-limiting on
 text/graphics (already high-frequency, so almost no polish) and spares text/edges by
 masking the grain.
 
@@ -71,7 +74,7 @@ _DBNET_INPUT_SIDE = 736  # square input, multiple of 32 (PP-OCRv3 default)
 _DBNET_MEAN = (122.67891434, 116.66876762, 104.00698793)  # ImageNet mean * 255
 _dbnet: Any = None  # lazy singleton; set to False after a load failure (-> MSER fallback)
 
-# When a smoothing pass ran (controlnet or face restore), the adaptive polish
+# When the controlnet smoothing pass ran, the adaptive polish
 # (humanizer.adaptive_polish) restores the input's detail level, sparing text --
 # replacing the old fixed unsharp/grain which over-/under-corrected and speckled text.
 _UPSCALE_FLOOR = 1024

src/remove_ai_watermarks/cli.py

@@ -173,7 +173,7 @@ _auto_option = click.option(
     "--auto",
     is_flag=True,
     default=False,
-    help="Auto-pick the pipeline, face restore, and adaptive polish from image content. "
+    help="Auto-pick the pipeline and adaptive polish from image content. "
     "Every choice is overridable -- an explicit --pipeline / --adaptive-polish "
     "always wins. EXPERIMENTAL.",
 )