JoinImageBatch¶
Documentation¶
- Class name:
easy joinImageBatch
- Category:
EasyUse/Image
- Output node:
False
The easy joinImageBatch
node is designed to transform a batch of images into a single, larger image. This process involves combining multiple images into one cohesive visual output, effectively creating a composite image from a collection of individual images.
Input types¶
Required¶
images
- The collection of images to be combined into a single composite image. This parameter is crucial for determining the content and layout of the final composite output.
- Comfy dtype:
IMAGE
- Python dtype:
List[torch.Tensor]
mode
- Specifies the method or mode used to combine the images into a single batch. This parameter influences the arrangement and blending of individual images within the composite output.
- Comfy dtype:
['horizontal', 'vertical']
- Python dtype:
str
Output types¶
image
- Comfy dtype:
IMAGE
- Represents the output of the node, which is a single, composite image created from the input batch of images.
- Python dtype:
torch.Tensor
- Comfy dtype:
Usage tips¶
- Infra type:
GPU
- Common nodes: unknown
Source code¶
class JoinImageBatch:
"""Turns an image batch into one big image."""
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"images": ("IMAGE",),
"mode": (("horizontal", "vertical"), {"default": "horizontal"}),
},
}
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("image",)
FUNCTION = "join"
CATEGORY = "EasyUse/Image"
def join(self, images, mode):
n, h, w, c = images.shape
image = None
if mode == "vertical":
# for vertical we can just reshape
image = images.reshape(1, n * h, w, c)
elif mode == "horizontal":
# for horizontal we have to swap axes
image = torch.transpose(torch.transpose(images, 1, 2).reshape(1, n * w, h, c), 1, 2)
return (image,)