mirror of
https://github.com/justUmen/Bjornulf_custom_nodes.git
synced 2026-03-21 12:42:11 -03:00
46 lines
1.4 KiB
Python
46 lines
1.4 KiB
Python
import torch
|
|
import numpy as np
|
|
from PIL import Image
|
|
|
|
class MergeImagesVertically:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"image1": ("IMAGE",),
|
|
"image2": ("IMAGE",),
|
|
},
|
|
"optional": {
|
|
"image3": ("IMAGE",),
|
|
"image4": ("IMAGE",),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ("IMAGE",)
|
|
FUNCTION = "combine_images"
|
|
|
|
CATEGORY = "Bjornulf"
|
|
|
|
def combine_images(self, image1, image2, image3=None, image4=None):
|
|
# Collect all provided images
|
|
images = [image1, image2]
|
|
if image3 is not None:
|
|
images.append(image3)
|
|
if image4 is not None:
|
|
images.append(image4)
|
|
|
|
# Calculate the total width and maximum height
|
|
total_width = sum(img.shape[1] for img in images)
|
|
max_height = max(img.shape[2] for img in images)
|
|
|
|
# Create a new tensor for the combined image
|
|
combined_image = torch.zeros((images[0].shape[0], total_width, max_height, 3), dtype=images[0].dtype, device=images[0].device)
|
|
|
|
# Paste images side by side
|
|
current_x = 0
|
|
for img in images:
|
|
w, h = img.shape[1:3]
|
|
combined_image[:, current_x:current_x+w, :h, :] = img[:, :, :, :]
|
|
current_x += w
|
|
|
|
return (combined_image,) |