Merge branch 'master' into range-type

.gitignore

@@ -21,5 +21,6 @@ venv*/
 *.log
 web_custom_versions/
 .DS_Store
+openapi.yaml
 filtered-openapi.yaml
 uv.lock

comfy_extras/nodes_compositing.py

@@ -185,36 +185,6 @@ class SplitImageWithAlpha(io.ComfyNode):
         return io.NodeOutput(torch.stack(out_images), 1.0 - torch.stack(out_alphas))
 
 
-class SplitImageChannels(io.ComfyNode):
-    @classmethod
-    def define_schema(cls):
-        return io.Schema(
-            node_id="SplitImageChannels",
-            search_aliases=["convert to grayscale", "extract channels", "grayscale", "split channels", "RGB channels"],
-            display_name="Split Image Channels",
-            category="mask/compositing",
-            inputs=[
-                io.Image.Input("image"),
-            ],
-            outputs=[
-                io.Image.Output(display_name="red"),
-                io.Image.Output(display_name="green"),
-                io.Image.Output(display_name="blue"),
-                io.Mask.Output(display_name="alpha")
-            ],
-        )
-
-    @classmethod
-    def execute(cls, image: torch.Tensor) -> io.NodeOutput:
-        images = [i[:,:,:3] for i in image]
-        stacked = torch.stack(images)
-        reds = stacked[:, :, :, 0:1].repeat(1, 1, 1, 3)
-        greens = stacked[:, :, :, 1:2].repeat(1, 1, 1, 3)
-        blues = stacked[:, :, :, 2:3].repeat(1, 1, 1, 3)
-        alphas = [i[:,:,3] if i.shape[2] > 3 else torch.ones_like(i[:,:,0]) for i in image]
-        return io.NodeOutput(reds, greens, blues, 1.0 - torch.stack(alphas))
-
-
 class JoinImageWithAlpha(io.ComfyNode):
     @classmethod
     def define_schema(cls):
@@ -247,7 +217,6 @@ class CompositingExtension(ComfyExtension):
     async def get_node_list(self) -> list[type[io.ComfyNode]]:
         return [
             PorterDuffImageComposite,
-            SplitImageChannels,
             SplitImageWithAlpha,
             JoinImageWithAlpha,
         ]