Add InstructPixToPixConditioning node.

This commit is contained in:
comfyanonymous 2024-04-04 15:06:17 -04:00
parent 5272fd4b03
commit 1f8d8e6c77
2 changed files with 46 additions and 0 deletions

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@ -0,0 +1,45 @@
import torch
class InstructPixToPixConditioning:
@classmethod
def INPUT_TYPES(s):
return {"required": {"positive": ("CONDITIONING", ),
"negative": ("CONDITIONING", ),
"vae": ("VAE", ),
"pixels": ("IMAGE", ),
}}
RETURN_TYPES = ("CONDITIONING","CONDITIONING","LATENT")
RETURN_NAMES = ("positive", "negative", "latent")
FUNCTION = "encode"
CATEGORY = "conditioning/instructpix2pix"
def encode(self, positive, negative, pixels, vae):
x = (pixels.shape[1] // 8) * 8
y = (pixels.shape[2] // 8) * 8
if pixels.shape[1] != x or pixels.shape[2] != y:
x_offset = (pixels.shape[1] % 8) // 2
y_offset = (pixels.shape[2] % 8) // 2
pixels = pixels[:,x_offset:x + x_offset, y_offset:y + y_offset,:]
concat_latent = vae.encode(pixels)
out_latent = {}
out_latent["samples"] = torch.zeros_like(concat_latent)
out = []
for conditioning in [positive, negative]:
c = []
for t in conditioning:
d = t[1].copy()
d["concat_latent_image"] = concat_latent
n = [t[0], d]
c.append(n)
out.append(c)
return (out[0], out[1], out_latent)
NODE_CLASS_MAPPINGS = {
"InstructPixToPixConditioning": InstructPixToPixConditioning,
}

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@ -1965,6 +1965,7 @@ def init_custom_nodes():
"nodes_morphology.py", "nodes_morphology.py",
"nodes_stable_cascade.py", "nodes_stable_cascade.py",
"nodes_differential_diffusion.py", "nodes_differential_diffusion.py",
"nodes_ip2p.py",
] ]
import_failed = [] import_failed = []