Image composite node

comfy_extras/nodes_post_processing.py

@@ -435,7 +435,43 @@ class Merge:
 
         return (result,)
 
+class Composite:
+    def __init__(self):
+        pass
 
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "image_a": ("IMAGE",),
+                "image_b": ("IMAGE",),
+                "mask": ("MASK",),
+            },
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "composite"
+
+    CATEGORY = "image/postprocessing"
+
+    def composite(self, image_a: torch.Tensor, image_b: torch.Tensor, mask: torch.Tensor):
+        batch_size, height, width, _ = image_a.shape
+        result = torch.zeros_like(image_a)
+
+        for b in range(batch_size):
+            img_a = (image_a[b] * 255).to(torch.uint8).numpy()
+            img_b = (image_b[b] * 255).to(torch.uint8).numpy()
+            img_mask = (mask * 255).to(torch.uint8).numpy()
+            pil_image_a = Image.fromarray(img_a, mode='RGB')
+            pil_image_b = Image.fromarray(img_b, mode='RGB')
+            pil_image_mask = Image.fromarray(img_mask, mode='L')
+
+            output_image = Image.composite(pil_image_a, pil_image_b, pil_image_mask)
+
+            output_array = torch.tensor(np.array(output_image.convert("RGB"))).float() / 255
+            result[b] = output_array
+
+        return (result,)
 
 NODE_CLASS_MAPPINGS = {
     "ImageBlend": Blend,
@@ -447,6 +483,7 @@ NODE_CLASS_MAPPINGS = {
     "ImageGetChannel": GetChannel,
     "ImageSplit": Split,
     "ImageMerge": Merge,
+    "ImageComposite": Composite,
 }
 
 NODE_DISPLAY_NAME_MAPPINGS  = {
@@ -459,4 +496,5 @@ NODE_DISPLAY_NAME_MAPPINGS  = {
     "ImageGetChannel": "Extract Channel",
     "ImageSplit": "Split Channels",
     "ImageMerge": "Merge Channels",
+    "ImageComposite": "Composite Images",
 }