2.0 KiB
2.0 KiB
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Join Image with Alpha
Documentation
- Class name:
JoinImageWithAlpha - Category:
mask/compositing - Output node:
False
This node is designed for compositing operations, specifically to join an image with its corresponding alpha mask to produce a single output image. It effectively combines visual content with transparency information, enabling the creation of images where certain areas are transparent or semi-transparent.
Input types
Required
image- The main visual content to be combined with an alpha mask. It represents the image without transparency information.
- Comfy dtype:
IMAGE - Python dtype:
torch.Tensor
alpha- The alpha mask that defines the transparency of the corresponding image. It is used to determine which parts of the image should be transparent or semi-transparent.
- Comfy dtype:
MASK - Python dtype:
torch.Tensor
Output types
image- Comfy dtype:
IMAGE - The output is a single image that combines the input image with the alpha mask, incorporating transparency information into the visual content.
- Python dtype:
torch.Tensor
- Comfy dtype:
Usage tips
- Infra type:
GPU - Common nodes: unknown
Source code
class JoinImageWithAlpha:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"image": ("IMAGE",),
"alpha": ("MASK",),
}
}
CATEGORY = "mask/compositing"
RETURN_TYPES = ("IMAGE",)
FUNCTION = "join_image_with_alpha"
def join_image_with_alpha(self, image: torch.Tensor, alpha: torch.Tensor):
batch_size = min(len(image), len(alpha))
out_images = []
alpha = 1.0 - resize_mask(alpha, image.shape[1:])
for i in range(batch_size):
out_images.append(torch.cat((image[i][:,:,:3], alpha[i].unsqueeze(2)), dim=2))
result = (torch.stack(out_images),)
return result