Fix alpha in PorterDuffImageComposite. (#3411)

There were two bugs in PorterDuffImageComposite.

The first one is the fact that it uses the mask input directly as alpha, missing the conversion (`1-a`). The fix is similar to c16f5744.

The second one is that all color composition formulas assume alpha premultiplied values, while the input is not premultiplied.

This change fixes both of these issue.

comfy_extras/nodes_compositing.py

@@ -28,6 +28,14 @@ class PorterDuffMode(Enum):
 
 
 def porter_duff_composite(src_image: torch.Tensor, src_alpha: torch.Tensor, dst_image: torch.Tensor, dst_alpha: torch.Tensor, mode: PorterDuffMode):
+    # convert mask to alpha
+    src_alpha = 1 - src_alpha
+    dst_alpha = 1 - dst_alpha
+    # premultiply alpha
+    src_image = src_image * src_alpha
+    dst_image = dst_image * dst_alpha
+
+    # composite ops below assume alpha-premultiplied images
     if mode == PorterDuffMode.ADD:
         out_alpha = torch.clamp(src_alpha + dst_alpha, 0, 1)
         out_image = torch.clamp(src_image + dst_image, 0, 1)
@@ -35,7 +43,7 @@ def porter_duff_composite(src_image: torch.Tensor, src_alpha: torch.Tensor, dst_
         out_alpha = torch.zeros_like(dst_alpha)
         out_image = torch.zeros_like(dst_image)
     elif mode == PorterDuffMode.DARKEN:
-        out_alpha = src_alpha + dst_alpha  - src_alpha * dst_alpha
+        out_alpha = src_alpha + dst_alpha - src_alpha * dst_alpha
         out_image = (1 - dst_alpha) * src_image + (1 - src_alpha) * dst_image + torch.min(src_image, dst_image)
     elif mode == PorterDuffMode.DST:
         out_alpha = dst_alpha
@@ -84,8 +92,13 @@ def porter_duff_composite(src_image: torch.Tensor, src_alpha: torch.Tensor, dst_
         out_alpha = (1 - dst_alpha) * src_alpha + (1 - src_alpha) * dst_alpha
         out_image = (1 - dst_alpha) * src_image + (1 - src_alpha) * dst_image
     else:
-        out_alpha = None
-        out_image = None
+        return None, None
+
+    # back to non-premultiplied alpha
+    out_image = torch.where(out_alpha > 1e-5, out_image / out_alpha, torch.zeros_like(out_image))
+    out_image = torch.clamp(out_image, 0, 1)
+    # convert alpha to mask
+    out_alpha = 1 - out_alpha
     return out_image, out_alpha