Pin published ONNX classifier snapshot

docs/module-internals.md

@@ -1105,8 +1105,8 @@ buffers are fully materialized.
 
 The optional CPU-only `backend="onnx"` path reads a static batch-one,
 vision-only FP32 graph produced by `scripts/export_photo_classify_onnx.py`.
-PyTorch remains the default until that artifact is published in the pinned Hub
-snapshot. The graph is 1,216,102,506 bytes versus the 1,710,697,163-byte full
+The graph is published in the pinned Hub snapshot; PyTorch remains the default.
+It is 1,216,102,506 bytes versus the 1,710,697,163-byte full
 PyTorch checkpoint; the removed text tower alone is 494,601,216 bytes. A
 2026-09-10 stress comparison covered 500 locally available catalog photographs
 closest to either Model 1 threshold plus 500 deterministic family-stratified

docs/photo-classify.md

@@ -40,9 +40,9 @@ Missing extra raises `RuntimeError` with
 `pip install 'remove-ai-watermarks[classify]'`. `device` is a library
 parameter (`None` / `"auto"` / `"cpu"` / `"cuda"`), not a CLI option. The
 explicit `backend="onnx"` path is CPU-only and requires
-`clip-l-ft-vision-fp32.onnx` in `RAIW_CLASSIFY_WEIGHTS`; PyTorch remains the
-default until that artifact is published in the pinned Hub snapshot. Install
-the experimental runtime with `pip install 'remove-ai-watermarks[classify-onnx]'`.
+`clip-l-ft-vision-fp32.onnx` in `RAIW_CLASSIFY_WEIGHTS` or the pinned Hub
+snapshot. PyTorch remains the default. Install the optional runtime with
+`pip install 'remove-ai-watermarks[classify-onnx]'`.
 
 Weights are not in git. First call downloads
 [`wiltodelta/raiw-photo-classify`](https://huggingface.co/wiltodelta/raiw-photo-classify)

pyproject.toml

@@ -155,7 +155,7 @@ classify = [
     "huggingface-hub>=0.20.0",
 ]
 # Optional vision-only CPU runtime for the photo classifier. Keep it separate
-# until the ONNX artifact is published and the backend becomes the default.
+# because PyTorch remains the default and ONNX Runtime is needed only on opt-in.
 classify-onnx = [
     "remove-ai-watermarks[classify]",
     "onnxruntime>=1.24.0",

src/remove_ai_watermarks/classify.py

@@ -22,7 +22,7 @@ CLASSIFY_EXTRA = "'remove-ai-watermarks[classify]'"
 CLASSIFY_ONNX_EXTRA = "'remove-ai-watermarks[classify-onnx]'"
 WEIGHTS_ENV = "RAIW_CLASSIFY_WEIGHTS"
 WEIGHTS_REPO = "wiltodelta/raiw-photo-classify"
-WEIGHTS_REVISION = "4c2763766dd1c8c212d64e01e1cc3f166243c47d"
+WEIGHTS_REVISION = "de668f0d8a53412923478cc21382a56890748310"
 CLIP_FILE = "clip-l-ft.pt"
 CLIP_ONNX_FILE = "clip-l-ft-vision-fp32.onnx"
 PROBE_FILE = "probe-weights-clip-l-ft.npz"

tests/test_classify.py

@@ -55,7 +55,7 @@ def _scores(
 
 def test_hub_snapshot_is_the_freeze_revision() -> None:
     assert WEIGHTS_REPO == "wiltodelta/raiw-photo-classify"
-    assert WEIGHTS_REVISION == "4c2763766dd1c8c212d64e01e1cc3f166243c47d"
+    assert WEIGHTS_REVISION == "de668f0d8a53412923478cc21382a56890748310"
 
 
 def test_runtime_requests_only_the_selected_backend_model(monkeypatch: pytest.MonkeyPatch) -> None: