Remove the unreachable ESRGAN upscale chain

The min-resolution floor lifted small inputs toward SDXL's ~1024 training size,
and Real-ESRGAN was an optional way to do that lifting. Both surviving profiles
run at native geometry, so the engine forced the floor to 0 on every path; the
floor never fired, `upscaling` was never true, and nothing downstream of it could
execute. Gone: upscaler.py, _esrgan_upscale, the min_resolution and upscaler
parameters, _target_size's floor branch, --min-resolution, --upscaler,
_warn_if_esrgan_unavailable and the `esrgan` extra. max_resolution stays and is
now the only lever on geometry; it can only scale down.

scripts/smoke_matrix.py was the one live consumer and neither gate saw it -
Pyright is scoped to src/ and Ruff cannot resolve its function-local import - so
`--diffusion` would have died at import. Its knob rows were written for the
removed profiles besides (--pipeline sdxl, --steps 20, --guidance-scale 5.0,
--device mps), so they are rewritten rather than patched: most now assert a knob
is REJECTED, which is the coverage worth having when the CLI accepts a value the
library refuses several layers down. Accepted-knob rows skip without CUDA, so the
row count is host-dependent and verification-plan.md no longer claims a fixed 68.

This removes a public module, a CLI option and a published extra, so the next
release is 0.25.0, not a patch.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

docs/installation.md

@@ -98,7 +98,6 @@ application actually uses:
 | `diffusion` | Diffusion-based invisible watermark removal | `pixels`, Torch, Diffusers | Yes |
 | `migan` | MI-GAN ONNX fill backend | `visible`, ONNX Runtime | Model download, no Torch |
 | `lama` | big-LaMa ONNX fill backend | `visible`, ONNX Runtime | Model download, no Torch |
-| `esrgan` | Real-ESRGAN upscaling before diffusion | `pixels`, spandrel | Yes |
 | `qwen-zimage` | CUDA-only Qwen Image plus Z-Image pipeline | `diffusion`, DiffSynth | Yes |
 | `all` | Every production feature | All rows above | Yes |
 | `dev` | Tests, linting, typing, and upstream parity checks | `visible`, `detect`, upstream invisible-watermark | Yes, for parity tests |
@@ -113,7 +112,6 @@ flowchart LR
     diffusion --> pixels
     migan --> visible
     lama --> visible
-    esrgan --> pixels
     qwen["qwen-zimage"] --> diffusion
     heif
     trustmark

docs/known-limitations.md

@@ -150,13 +150,14 @@ deprecated, emits a warning, and changes nothing.
 
 ## Resolution and memory
 
-### Small images are enlarged before SDXL based diffusion
+### Small images are processed at their native size
 
-The SDXL, ControlNet, and base Qwen paths use a default minimum long side of
-`1024`. Smaller inputs are enlarged before diffusion and restored to their
-original dimensions afterward. Set `--min-resolution 0` to disable the floor.
+There is no minimum-resolution floor. It existed to enlarge small inputs toward
+SDXL's ~1024 training resolution and was removed with the SDXL profiles, which
+never applied it anyway. Both surviving profiles run at native geometry, so a
+small input is neither enlarged before diffusion nor restored afterward.
 
-`qwen-zimage` does not apply this SDXL minimum resolution floor.
+`--max-resolution` still caps very large inputs, and only ever scales down.
 
 ### Large images stay at native resolution unless capped
 

docs/module-internals.md

@@ -492,7 +492,7 @@ stage.
 router.
 
 [`invisible_engine.py`](../src/remove_ai_watermarks/invisible_engine.py) handles
-image sizing, optional pre-upscaling, postprocessing, and the public engine
+image sizing, postprocessing, and the public engine
 interface. It delegates model execution to
 [`_internal/watermark_remover.py`](../src/remove_ai_watermarks/_internal/watermark_remover.py).
 
@@ -725,18 +725,20 @@ Regression coverage:
 
 - [`test_tiling.py`](../tests/test_tiling.py)
 
-### Upscaling and postprocessing
-
-[`upscaler.py`](../src/remove_ai_watermarks/upscaler.py) is the optional
-Real-ESRGAN path used only when enlarging a small image to the minimum
-resolution floor. Failure or an absent extra falls back to Lanczos.
+### Postprocessing
 
 [`humanizer.py`](../src/remove_ai_watermarks/humanizer.py) contains explicit
 grain, unsharp masking, and adaptive polish helpers.
 
+`upscaler.py` held an optional Real-ESRGAN path, reachable only when enlarging a
+small image to the minimum-resolution floor. That floor existed to lift small
+inputs toward SDXL's ~1024 training size; when the SDXL profiles were removed it
+was forced to 0 on every path, so the module, the `--min-resolution` and
+`--upscaler` options and the `esrgan` extra were all unreachable and went with
+it. Only the `max_resolution` cap can move geometry now, and it only scales down.
+
 Regression coverage:
 
-- [`test_upscaler.py`](../tests/test_upscaler.py)
 - [`test_humanizer.py`](../tests/test_humanizer.py)
 
 ## Image input and output

docs/python-api.md

@@ -422,7 +422,7 @@ engine = InvisibleEngine(pipeline="sdxl-zimage")
 The `qwen-zimage` extra must be installed for that profile.
 
 The full `remove_watermark` signature includes strength, steps, guidance,
-seeding, tiling, resolution, upscaling, and postprocessing controls. Read the
+seeding, tiling, resolution, and postprocessing controls. Read the
 method signature in
 [`invisible_engine.py`](../src/remove_ai_watermarks/invisible_engine.py) or use
 the CLI guide for the concepts.

docs/verification-plan.md

@@ -72,8 +72,10 @@ Run detection, removal, and re-detection over a representative local set. Confir
 
 ### A5. Contract sweep across every parameter choice
 
-`scripts/smoke_matrix.py` (exists, 68 rows, 0 skipped with `--diffusion`) covers every
-choice-valued flag on fixtures. Extend from fixtures to a stratified corpus slice
+`scripts/smoke_matrix.py` covers every choice-valued flag on fixtures. Its knob rows
+were rewritten when the CPU/MPS profiles and the ESRGAN chain were removed: most now
+assert a knob is REJECTED, and the accepted-knob rows skip without a CUDA device, so
+the row count is host-dependent rather than the fixed 68 recorded here before. Extend from fixtures to a stratified corpus slice
 (~500 images spanning format x provenance x aspect ratio), asserting exit-code semantics
 rather than just absence of crash.
 
@@ -85,7 +87,7 @@ sweep asserts on stderr, or the codes get split -- the latter is the better fix.
 
 Compare the flags and values exercised by the matrix against the options declared by
 the CLI. Include optional backends, batch modes, tiling, region-targeted composition,
-the ESRGAN upscaler, and the ffmpeg audio/video strip. The gap to find is not only
+and the ffmpeg audio/video strip. The gap to find is not only
 "logic untested" but
 "never executed on real data", which is precisely what this campaign is for.