nodes/LAOGOU-666-ComfyUI-LG_SamplingUtils
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增加2511兼容以及修复sigmas编辑器bug

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LAOGOU-666
2025-12-25 07:54:51 +08:00
parent e6642dc27f
commit 8a725e3182
3 changed files with 53 additions and 17 deletions
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py/noise_injection.py
+48 -14
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@@ -70,7 +70,7 @@ class LGNoiseInjection:
RETURN_TYPES = ("MODEL",)
FUNCTION = "apply"
CATEGORY = "🎈LAOGOU/Sampling Utils"
CATEGORY = "advanced/model"
DESCRIPTION = "将参考图像的特征（如水珠、纹理等）注入到生成结果中。"
def apply(self, model, vae, reference_image, strength, start_percent, end_percent, mask=None):
@@ -79,8 +79,8 @@ class LGNoiseInjection:
m = model.clone()
# 编码参考图像
ref_latent = self._encode_reference(vae, reference_image)
# 编码参考图像（使用模型的 latent format）
ref_latent = self._encode_reference(vae, reference_image, model)
# 预处理 mask
mask_latent = None
@@ -113,11 +113,19 @@ class LGNoiseInjection:
ref = ref_latent.to(device=cfg_result.device, dtype=cfg_result.dtype)
if ref.shape[2:] != cfg_result.shape[2:]:
ref = F.interpolate(ref, size=cfg_result.shape[2:], mode='bilinear', align_corners=False)
# 根据张量维度选择插值模式
if len(ref.shape) == 5: # 5D张量 [B, C, T, H, W]
ref = F.interpolate(ref, size=cfg_result.shape[2:], mode='trilinear', align_corners=False)
else: # 4D张量 [B, C, H, W]
ref = F.interpolate(ref, size=cfg_result.shape[2:], mode='bilinear', align_corners=False)
if ref.shape[0] != cfg_result.shape[0]:
if ref.shape[0] == 1:
ref = ref.expand(cfg_result.shape[0], -1, -1, -1)
# 根据张量维度调整expand
if len(ref.shape) == 5:
ref = ref.expand(cfg_result.shape[0], -1, -1, -1, -1)
else:
ref = ref.expand(cfg_result.shape[0], -1, -1, -1)
else:
ref = ref[:cfg_result.shape[0]]
@@ -127,11 +135,19 @@ class LGNoiseInjection:
current_mask = mask_latent.to(device=cfg_result.device, dtype=cfg_result.dtype)
# 调整 mask 尺寸到 latent 空间
if current_mask.shape[2:] != cfg_result.shape[2:]:
current_mask = F.interpolate(current_mask, size=cfg_result.shape[2:], mode='bilinear', align_corners=False)
# 根据张量维度选择插值模式
if len(current_mask.shape) == 5: # 5D张量 [B, C, T, H, W]
current_mask = F.interpolate(current_mask, size=cfg_result.shape[2:], mode='trilinear', align_corners=False)
else: # 4D张量 [B, C, H, W]
current_mask = F.interpolate(current_mask, size=cfg_result.shape[2:], mode='bilinear', align_corners=False)
# 调整 batch size
if current_mask.shape[0] != cfg_result.shape[0]:
if current_mask.shape[0] == 1:
current_mask = current_mask.expand(cfg_result.shape[0], -1, -1, -1)
# 根据张量维度调整expand
if len(current_mask.shape) == 5:
current_mask = current_mask.expand(cfg_result.shape[0], -1, -1, -1, -1)
else:
current_mask = current_mask.expand(cfg_result.shape[0], -1, -1, -1)
else:
current_mask = current_mask[:cfg_result.shape[0]]
@@ -170,11 +186,13 @@ class LGNoiseInjection:
return (m,)
def _encode_reference(self, vae, reference_image):
def _encode_reference(self, vae, reference_image, model):
"""编码参考图像"""
loaded_models = comfy.model_management.loaded_models(only_currently_used=True)
latent = vae.encode(reference_image)
latent = comfy.latent_formats.Flux().process_in(latent)
# 使用模型自己的 latent format，而不是硬编码 Flux
latent_format = model.get_model_object("latent_format")
latent = latent_format.process_in(latent)
comfy.model_management.load_models_gpu(loaded_models)
logging.warning(f"[FeatureInj] Reference encoded: shape={latent.shape}")
return latent
@@ -242,7 +260,7 @@ class LGNoiseInjectionLatent:
RETURN_TYPES = ("MODEL",)
FUNCTION = "apply"
CATEGORY = "🎈LAOGOU/Sampling Utils"
CATEGORY = "advanced/model"
DESCRIPTION = "直接输入 latent 进行特征注入，自动使用 latent 的 noise_mask 作为遮罩。"
def apply(self, model, reference_latent, strength, start_percent, end_percent):
@@ -288,11 +306,19 @@ class LGNoiseInjectionLatent:
ref = ref_latent.to(device=cfg_result.device, dtype=cfg_result.dtype)
if ref.shape[2:] != cfg_result.shape[2:]:
ref = F.interpolate(ref, size=cfg_result.shape[2:], mode='bilinear', align_corners=False)
# 根据张量维度选择插值模式
if len(ref.shape) == 5: # 5D张量 [B, C, T, H, W]
ref = F.interpolate(ref, size=cfg_result.shape[2:], mode='trilinear', align_corners=False)
else: # 4D张量 [B, C, H, W]
ref = F.interpolate(ref, size=cfg_result.shape[2:], mode='bilinear', align_corners=False)
if ref.shape[0] != cfg_result.shape[0]:
if ref.shape[0] == 1:
ref = ref.expand(cfg_result.shape[0], -1, -1, -1)
# 根据张量维度调整expand
if len(ref.shape) == 5:
ref = ref.expand(cfg_result.shape[0], -1, -1, -1, -1)
else:
ref = ref.expand(cfg_result.shape[0], -1, -1, -1)
else:
ref = ref[:cfg_result.shape[0]]
@@ -302,11 +328,19 @@ class LGNoiseInjectionLatent:
current_mask = mask_latent.to(device=cfg_result.device, dtype=cfg_result.dtype)
# 调整 mask 尺寸到 latent 空间
if current_mask.shape[2:] != cfg_result.shape[2:]:
current_mask = F.interpolate(current_mask, size=cfg_result.shape[2:], mode='bilinear', align_corners=False)
# 根据张量维度选择插值模式
if len(current_mask.shape) == 5: # 5D张量 [B, C, T, H, W]
current_mask = F.interpolate(current_mask, size=cfg_result.shape[2:], mode='trilinear', align_corners=False)
else: # 4D张量 [B, C, H, W]
current_mask = F.interpolate(current_mask, size=cfg_result.shape[2:], mode='bilinear', align_corners=False)
# 调整 batch size
if current_mask.shape[0] != cfg_result.shape[0]:
if current_mask.shape[0] == 1:
current_mask = current_mask.expand(cfg_result.shape[0], -1, -1, -1)
# 根据张量维度调整expand
if len(current_mask.shape) == 5:
current_mask = current_mask.expand(cfg_result.shape[0], -1, -1, -1, -1)
else:
current_mask = current_mask.expand(cfg_result.shape[0], -1, -1, -1)
else:
current_mask = current_mask[:cfg_result.shape[0]]
py/sigmas_editor.py
+4 -2
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@@ -73,18 +73,20 @@ class SigmasEditor:
# Send sigmas data to frontend via PromptServer (只有输入sigmas改变时才发送)
if unique_id is not None:
# 只根据输入的sigmas创建缓存键（不包括adjustments）
current_sigmas_key = tuple(sigmas_np.tolist())
# 使用 hash(sigmas_np.tobytes()) 避免浮点数精度比较问题
current_sigmas_key = hash(sigmas_np.tobytes())
# 检查是否与上次输入的sigmas相同
last_sigmas_key = self._last_sent_data.get(unique_id)
# 只有输入sigmas改变时才发送数据到前端
if last_sigmas_key != current_sigmas_key:
# 当输入sigmas改变时，不发送旧的调整值，让前端重置为原始值
PromptServer.instance.send_sync("sigmas_editor_update", {
"node_id": unique_id,
"sigmas_data": {
"original": sigmas_np.tolist(),
"adjusted": adjusted_sigmas.tolist(),
"adjusted": None, # 重置为None，让前端使用新的原始值
}
})
pyproject.toml
+1 -1
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@@ -1,7 +1,7 @@
[project]
name = "comfyui_lg_samplingutils"
description = "This is a toolset designed for ComfyUI by LAOGOU-666, providing a series of practical sampling nodes, making our operation more intuitive and convenient"
version = "1.0.1"
version = "1.0.2"
license = { text = "LICENSE.txt" }
dependencies = [""]