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import custom_nodes.Derfuu_Nodes.types as type
import custom_nodes.Derfuu_Nodes.fields as field
from custom_nodes.Derfuu_Nodes.tree import TREE_LATENTS, TREE_IMAGES
import math
import torch
import comfy.utils
class EmptyLatentImage:
def __init__(self, device="cpu"):
self.device = device
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"TUPLE": (type.TUPLE,),
"batch_size": field.INT,
}
}
RETURN_TYPES = (type.LATENT,)
FUNCTION = "generate"
CATEGORY = TREE_LATENTS
def generate(self, TUPLE, batch_size=1):
width = int(TUPLE[0])
height = int(TUPLE[1])
latent = torch.zeros([batch_size, 4, height // 8, width // 8])
return ({"samples": latent},)
class ImageScale_Ratio:
upscale_methods = ["nearest-exact", "bilinear", "area"]
crop_methods = ["disabled", "center"]
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"IMAGE": (type.IMAGE,),
"TUPLE": (type.TUPLE,),
"modifier": field.FLOAT,
"upscale_method": (cls.upscale_methods,),
"crop": (cls.crop_methods,)}}
RETURN_TYPES = (type.IMAGE, type.TUPLE,)
FUNCTION = "upscale"
CATEGORY = TREE_IMAGES
def upscale(self, IMAGE, upscale_method, TUPLE, modifier, crop):
samples = IMAGE.movedim(-1, 1)
width_B = int(TUPLE[0])
height_B = int(TUPLE[1])
height = math.ceil(height_B * modifier)
width = math.ceil(width_B * modifier)
cls = comfy.utils.common_upscale(samples, width, height, upscale_method, crop)
cls = cls.movedim(1, -1)
return (cls, (width, height),)
class ImageScale_Side:
upscale_methods = ["nearest-exact", "bilinear", "area"]
crop_methods = ["disabled", "center"]
def __init__(self) -> None:
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"IMAGE": (type.IMAGE,),
"TUPLE": (type.TUPLE,),
"side_length": field.INT,
"side": (["Width", "Height"],),
"upscale_method": (cls.upscale_methods,),
"crop": (cls.crop_methods,)}}
RETURN_TYPES = (type.IMAGE, type.TUPLE,)
FUNCTION = "upscale"
CATEGORY = TREE_IMAGES
def upscale(self, IMAGE, upscale_method, TUPLE, side_length, side, crop):
samples = IMAGE.movedim(-1, 1)
width_B = int(TUPLE[0])
height_B = int(TUPLE[1])
width = width_B
height = height_B
if side == "Width":
heigh_ratio = height_B / width_B
width = side_length
height = heigh_ratio * width
elif side == "Height":
width_ratio = width_B / height_B
height = side_length
width = width_ratio * height
width = math.ceil(width)
height = math.ceil(height)
cls = comfy.utils.common_upscale(samples, width, height, upscale_method, crop)
cls = cls.movedim(1, -1)
return (cls, (width, height), )
class LatentScale_Ratio:
scale_methods = (["nearest-exact", "bilinear", "area"],)
crop_methods = (["disabled", "center"],)
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"LATENT": (type.LATENT,),
"TUPLE": (type.TUPLE,),
"modifier": field.FLOAT,
"scale_method": cls.scale_methods,
"crop": cls.crop_methods,
}
}
RETURN_TYPES = (type.LATENT, type.TUPLE,)
FUNCTION = "scale"
CATEGORY = TREE_LATENTS
def scale(self, LATENT, scale_method, crop, modifier, TUPLE):
width = int(TUPLE[0] * modifier)
height = int(TUPLE[1] * modifier)
cls = LATENT.copy()
cls["samples"] = comfy.utils.common_upscale(LATENT["samples"], width // 8, height // 8, scale_method, crop)
return (cls, (width, height),)
class LatentScale_Side:
upscale_methods = ["nearest-exact", "bilinear", "area"]
crop_methods = ["disabled", "center"]
def __init__(self) -> None:
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"LATENT": (type.LATENT,),
"TUPLE": (type.TUPLE,),
"side_length": field.INT,
"side": (["Width", "Height"],),
"scale_method": (cls.upscale_methods,),
"crop": (cls.crop_methods,)}}
RETURN_TYPES = (type.LATENT, type.TUPLE,)
FUNCTION = "upscale"
CATEGORY = TREE_LATENTS
def upscale(self, LATENT, scale_method, TUPLE, side_length, side, crop):
width_B = int(TUPLE[0])
height_B = int(TUPLE[1])
width = width_B
height = height_B
if side == "Width":
heigh_ratio = height_B / width_B
width = side_length
height = heigh_ratio * width
elif side == "Height":
width_ratio = width_B / height_B
height = side_length
width = width_ratio * height
width = math.ceil(width)
height = math.ceil(height)
cls = LATENT.copy()
cls["samples"] = comfy.utils.common_upscale(LATENT["samples"], width // 8, height // 8, scale_method, crop)
return (cls, (width, height),) |