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Add LatentComposite node.

This can be used to "paste" one latent image on top of the other.
pull/3/head
comfyanonymous 2 years ago
parent
commit
fef41d0a72
  1. 22
      nodes.py

22
nodes.py

@ -241,6 +241,27 @@ class LatentFlip:
s = samples s = samples
return (s,) return (s,)
class LatentComposite:
@classmethod
def INPUT_TYPES(s):
return {"required": { "samples_to": ("LATENT",),
"samples_from": ("LATENT",),
"x": ("INT", {"default": 0, "min": 0, "max": 4096, "step": 8}),
"y": ("INT", {"default": 0, "min": 0, "max": 4096, "step": 8}),
}}
RETURN_TYPES = ("LATENT",)
FUNCTION = "composite"
CATEGORY = "latent"
def composite(self, samples_to, samples_from, x, y, composite_method="normal"):
x = x // 8
y = y // 8
s = samples_to.clone()
s[:,:,y:y+samples_from.shape[2],x:x+samples_from.shape[3]] = samples_from[:,:,:samples_to.shape[2] - y, :samples_to.shape[3] - x]
return (s,)
def common_ksampler(device, model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=1.0, disable_noise=False, start_step=None, last_step=None, force_full_denoise=False): def common_ksampler(device, model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=1.0, disable_noise=False, start_step=None, last_step=None, force_full_denoise=False):
if disable_noise: if disable_noise:
noise = torch.zeros(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, device="cpu") noise = torch.zeros(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, device="cpu")
@ -428,6 +449,7 @@ NODE_CLASS_MAPPINGS = {
"ConditioningCombine": ConditioningCombine, "ConditioningCombine": ConditioningCombine,
"ConditioningSetArea": ConditioningSetArea, "ConditioningSetArea": ConditioningSetArea,
"KSamplerAdvanced": KSamplerAdvanced, "KSamplerAdvanced": KSamplerAdvanced,
"LatentComposite": LatentComposite,
"LatentRotate": LatentRotate, "LatentRotate": LatentRotate,
"LatentFlip": LatentFlip, "LatentFlip": LatentFlip,
} }

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