RefurnishAI / custom_nodes /rgthree-comfy /py /sdxl_empty_latent_image.py
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from nodes import EmptyLatentImage
from .constants import get_category, get_name
class RgthreeSDXLEmptyLatentImage:
NAME = get_name('SDXL Empty Latent Image')
CATEGORY = get_category()
@classmethod
def INPUT_TYPES(cls): # pylint: disable = invalid-name, missing-function-docstring
return {
"required": {
"dimensions": (
[
# 'Custom',
'1536 x 640 (landscape)',
'1344 x 768 (landscape)',
'1216 x 832 (landscape)',
'1152 x 896 (landscape)',
'1024 x 1024 (square)',
' 896 x 1152 (portrait)',
' 832 x 1216 (portrait)',
' 768 x 1344 (portrait)',
' 640 x 1536 (portrait)',
],
{
"default": '1024 x 1024 (square)'
}),
"clip_scale": ("FLOAT", {
"default": 2.0,
"min": 1.0,
"max": 10.0,
"step": .5
}),
"batch_size": ("INT", {
"default": 1,
"min": 1,
"max": 64
}),
},
# "optional": {
# "custom_width": ("INT", {"min": 1, "max": MAX_RESOLUTION, "step": 64}),
# "custom_height": ("INT", {"min": 1, "max": MAX_RESOLUTION, "step": 64}),
# }
}
RETURN_TYPES = ("LATENT", "INT", "INT")
RETURN_NAMES = ("LATENT", "CLIP_WIDTH", "CLIP_HEIGHT")
FUNCTION = "generate"
def generate(self, dimensions, clip_scale, batch_size):
"""Generates the latent and exposes the clip_width and clip_height"""
if True:
result = [x.strip() for x in dimensions.split('x')]
width = int(result[0])
height = int(result[1].split(' ')[0])
latent = EmptyLatentImage().generate(width, height, batch_size)[0]
return (
latent,
int(width * clip_scale),
int(height * clip_scale),
)