84 lines
2.4 KiB
Python
84 lines
2.4 KiB
Python
"""
|
|
LLS / Image
|
|
===========
|
|
功能域：图像处理与后处理（对应功能分类总览第 5 节）
|
|
|
|
CATEGORY = "LLS/Image"
|
|
"""
|
|
from __future__ import annotations
|
|
|
|
|
|
# ---------- 节点类 ----------
|
|
|
|
class LLSSimpleVAEDecode:
|
|
"""
|
|
简化版 VAE Decode 节点。
|
|
内部复用 ComfyUI 原生 VAEDecode 能力，将 Latent 解码为像素图像。
|
|
第一版只做普通解码，不实现 Tiled VAE。
|
|
"""
|
|
|
|
CATEGORY = "LLS/Image"
|
|
FUNCTION = "decode"
|
|
RETURN_TYPES = ("IMAGE", "STRING")
|
|
RETURN_NAMES = ("image", "decode_info")
|
|
DESCRIPTION = (
|
|
"Decode a LATENT tensor into a pixel IMAGE using the VAE. "
|
|
"First version uses standard (non-tiled) decoding."
|
|
)
|
|
|
|
@classmethod
|
|
def INPUT_TYPES(cls):
|
|
return {
|
|
"required": {
|
|
"samples": ("LATENT",),
|
|
"vae": ("VAE",),
|
|
}
|
|
}
|
|
|
|
def decode(self, samples, vae):
|
|
if vae is None:
|
|
raise RuntimeError(
|
|
"[LLS] VAE is None. Make sure a checkpoint is loaded and VAE is connected."
|
|
)
|
|
if samples is None:
|
|
raise RuntimeError(
|
|
"[LLS] LATENT samples is None. Connect the output of KSampler to this node."
|
|
)
|
|
|
|
latent_tensor = samples.get("samples")
|
|
if latent_tensor is None:
|
|
raise RuntimeError(
|
|
"[LLS] LATENT dict does not contain 'samples' key. "
|
|
"Make sure the upstream node outputs a valid LATENT."
|
|
)
|
|
if getattr(latent_tensor, "is_nested", False):
|
|
latent_tensor = latent_tensor.unbind()[0]
|
|
|
|
# 复用 ComfyUI VAE 原生 decode 方法
|
|
try:
|
|
image = vae.decode(latent_tensor)
|
|
except Exception as exc:
|
|
raise RuntimeError(
|
|
f"[LLS] VAE decode failed: {exc}"
|
|
) from exc
|
|
|
|
if len(getattr(image, "shape", ())) == 5:
|
|
image = image.reshape(-1, image.shape[-3], image.shape[-2], image.shape[-1])
|
|
|
|
h, w = latent_tensor.shape[2] * 8, latent_tensor.shape[3] * 8
|
|
batch = latent_tensor.shape[0]
|
|
decode_info = f"decoded={w}x{h} | batch={batch} | latent_shape={list(latent_tensor.shape)}"
|
|
|
|
return (image, decode_info)
|
|
|
|
|
|
# ---------- 注册表 ----------
|
|
|
|
NODE_CLASS_MAPPINGS: dict[str, type] = {
|
|
"LLSSimpleVAEDecode": LLSSimpleVAEDecode,
|
|
}
|
|
|
|
NODE_DISPLAY_NAME_MAPPINGS: dict[str, str] = {
|
|
"LLSSimpleVAEDecode": "LLS Simple VAE Decode",
|
|
}
|