Update engine.py

engine.py

@@ -547,13 +547,22 @@ def straighten_image(image: Image.Image, angle_deg: float) -> Image.Image:
     old FaceBox coordinates analytically is more error-prone than just
     re-detecting on the already-cheap YuNet pass.
 
+    Always returns RGB (never RGBA) — this runs on `bounded`, which is
+    RGB going into segment_alpha()'s Normalize transform; that transform
+    is hard-coded to 3 channels (see _seg_transform) and raises a shape
+    RuntimeError on 4-channel input. The rotation itself is done in RGBA
+    internally so PIL can fill the corners exposed by expand=True with a
+    real transparent value instead of smearing edge pixels (BICUBIC
+    without an alpha channel would otherwise blend rotated content
+    against whatever garbage sits outside the original frame) — that
+    RGBA intermediate is then flattened onto a neutral gray backing
+    before return, so the corners become plain pixels the segmentation
+    model can process like any other background, not transparency it has
+    never seen and has no defined behavior for.
+
     BICUBIC resample, matching every other resize/rotate op in this file
     that ends up in a printed deliverable (see load_and_bound's docstring
-    for why NEAREST is never used here). Background fill uses transparent
-    (0,0,0,0) since this runs on the RGBA-capable `bounded` stage before
-    background compositing — corners exposed by the rotation get painted
-    over by the spec's background color later in the pipeline, same as
-    crop_to_spec's existing pad logic.
+    for why NEAREST is never used here).
     """
     if abs(angle_deg) < 0.5:
         return image  # sub-half-degree tilt isn't worth a resample pass
@@ -573,7 +582,16 @@ def straighten_image(image: Image.Image, angle_deg: float) -> Image.Image:
         expand=True,
         fillcolor=(0, 0, 0, 0),
     )
-    return rotated
+
+    # Flatten onto a neutral 50%-gray RGB canvas — not white/black, so the
+    # exposed-corner triangles don't accidentally read as a "clean white
+    # background" region to segment_alpha's foreground/background
+    # separation (a pure white corner touching a light shirt could bias
+    # the matte). Gray is a safe, low-signal fill any segmentation model
+    # treats as unremarkable background.
+    backing = Image.new("RGB", rotated.size, (128, 128, 128))
+    backing.paste(rotated, mask=rotated.split()[3])  # alpha channel as mask
+    return backing
 
 
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