qnloft
/
ComfyUI
mirror of https://github.com/comfyanonymous/ComfyUI.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Support AliMama SD3 and Flux inpaint controlnets. 

Use the ControlNetInpaintingAliMamaApply node.
This commit is contained in:
comfyanonymous 2024-09-14 09:05:16 -04:00
parent 369a6dd2c4
commit f48e390032
4 changed files with 68 additions and 11 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
comfy/cldm/mmdit.py
View File

@ -6,6 +6,7 @@ class ControlNet(comfy.ldm.modules.diffusionmodules.mmdit.MMDiT):
def __init__(
self,
num_blocks = None,
control_latent_channels = None,
dtype = None,
device = None,
operations = None,
@ -17,10 +18,13 @@ class ControlNet(comfy.ldm.modules.diffusionmodules.mmdit.MMDiT):
for _ in range(len(self.joint_blocks)):
self.controlnet_blocks.append(operations.Linear(self.hidden_size, self.hidden_size, device=device, dtype=dtype))
if control_latent_channels is None:
control_latent_channels = self.in_channels
self.pos_embed_input = comfy.ldm.modules.diffusionmodules.mmdit.PatchEmbed(
None,
self.patch_size,
self.in_channels,
control_latent_channels,
self.hidden_size,
bias=True,
strict_img_size=False,

38
comfy/controlnet.py
View File

@ -79,13 +79,19 @@ class ControlBase:
self.previous_controlnet = None
self.extra_conds = []
self.strength_type = StrengthType.CONSTANT
self.concat_mask = False
self.extra_concat_orig = []
self.extra_concat = None
def set_cond_hint(self, cond_hint, strength=1.0, timestep_percent_range=(0.0, 1.0), vae=None):
def set_cond_hint(self, cond_hint, strength=1.0, timestep_percent_range=(0.0, 1.0), vae=None, extra_concat=[]):
self.cond_hint_original = cond_hint
self.strength = strength
self.timestep_percent_range = timestep_percent_range
if self.latent_format is not None:
self.vae = vae
self.extra_concat_orig = extra_concat.copy()
if self.concat_mask and len(self.extra_concat_orig) == 0:
self.extra_concat_orig.append(torch.tensor([[[[1.0]]]]))
return self
def pre_run(self, model, percent_to_timestep_function):
@ -100,9 +106,9 @@ class ControlBase:
def cleanup(self):
if self.previous_controlnet is not None:
self.previous_controlnet.cleanup()
if self.cond_hint is not None:
del self.cond_hint
self.cond_hint = None
self.extra_concat = None
self.timestep_range = None
def get_models(self):
@ -123,6 +129,8 @@ class ControlBase:
c.vae = self.vae
c.extra_conds = self.extra_conds.copy()
c.strength_type = self.strength_type
c.concat_mask = self.concat_mask
c.extra_concat_orig = self.extra_concat_orig.copy()
def inference_memory_requirements(self, dtype):
if self.previous_controlnet is not None:
@ -175,7 +183,7 @@ class ControlBase:
class ControlNet(ControlBase):
def __init__(self, control_model=None, global_average_pooling=False, compression_ratio=8, latent_format=None, device=None, load_device=None, manual_cast_dtype=None, extra_conds=["y"], strength_type=StrengthType.CONSTANT):
def __init__(self, control_model=None, global_average_pooling=False, compression_ratio=8, latent_format=None, device=None, load_device=None, manual_cast_dtype=None, extra_conds=["y"], strength_type=StrengthType.CONSTANT, concat_mask=False):
super().__init__(device)
self.control_model = control_model
self.load_device = load_device
@ -189,6 +197,7 @@ class ControlNet(ControlBase):
self.latent_format = latent_format
self.extra_conds += extra_conds
self.strength_type = strength_type
self.concat_mask = concat_mask
def get_control(self, x_noisy, t, cond, batched_number):
control_prev = None
@ -220,6 +229,13 @@ class ControlNet(ControlBase):
comfy.model_management.load_models_gpu(loaded_models)
if self.latent_format is not None:
self.cond_hint = self.latent_format.process_in(self.cond_hint)
if len(self.extra_concat_orig) > 0:
to_concat = []
for c in self.extra_concat_orig:
c = comfy.utils.common_upscale(c, self.cond_hint.shape[3], self.cond_hint.shape[2], self.upscale_algorithm, "center")
to_concat.append(comfy.utils.repeat_to_batch_size(c, self.cond_hint.shape[0]))
self.cond_hint = torch.cat([self.cond_hint] + to_concat, dim=1)
self.cond_hint = self.cond_hint.to(device=self.device, dtype=dtype)
if x_noisy.shape[0] != self.cond_hint.shape[0]:
self.cond_hint = broadcast_image_to(self.cond_hint, x_noisy.shape[0], batched_number)
@ -410,12 +426,17 @@ def load_controlnet_mmdit(sd):
for k in sd:
new_sd[k] = sd[k]
control_model = comfy.cldm.mmdit.ControlNet(num_blocks=num_blocks, operations=operations, device=offload_device, dtype=unet_dtype, **model_config.unet_config)
concat_mask = False
control_latent_channels = new_sd.get("pos_embed_input.proj.weight").shape[1]
if control_latent_channels == 17: #inpaint controlnet
concat_mask = True
control_model = comfy.cldm.mmdit.ControlNet(num_blocks=num_blocks, control_latent_channels=control_latent_channels, operations=operations, device=offload_device, dtype=unet_dtype, **model_config.unet_config)
control_model = controlnet_load_state_dict(control_model, new_sd)
latent_format = comfy.latent_formats.SD3()
latent_format.shift_factor = 0 #SD3 controlnet weirdness
control = ControlNet(control_model, compression_ratio=1, latent_format=latent_format, load_device=load_device, manual_cast_dtype=manual_cast_dtype)
control = ControlNet(control_model, compression_ratio=1, latent_format=latent_format, concat_mask=concat_mask, load_device=load_device, manual_cast_dtype=manual_cast_dtype)
return control
@ -450,13 +471,16 @@ def load_controlnet_flux_instantx(sd):
num_union_modes = new_sd[union_cnet].shape[0]
control_latent_channels = new_sd.get("pos_embed_input.weight").shape[1] // 4
concat_mask = False
if control_latent_channels == 17:
concat_mask = True
control_model = comfy.ldm.flux.controlnet.ControlNetFlux(latent_input=True, num_union_modes=num_union_modes, control_latent_channels=control_latent_channels, operations=operations, device=offload_device, dtype=unet_dtype, **model_config.unet_config)
control_model = controlnet_load_state_dict(control_model, new_sd)
latent_format = comfy.latent_formats.Flux()
extra_conds = ['y', 'guidance']
control = ControlNet(control_model, compression_ratio=1, latent_format=latent_format, load_device=load_device, manual_cast_dtype=manual_cast_dtype, extra_conds=extra_conds)
control = ControlNet(control_model, compression_ratio=1, latent_format=latent_format, concat_mask=concat_mask, load_device=load_device, manual_cast_dtype=manual_cast_dtype, extra_conds=extra_conds)
return control
def convert_mistoline(sd):

29
comfy_extras/nodes_controlnet.py
View File

@ -1,4 +1,6 @@
from comfy.cldm.control_types import UNION_CONTROLNET_TYPES
import nodes
import comfy.utils
class SetUnionControlNetType:
@classmethod
@ -22,6 +24,33 @@ class SetUnionControlNetType:
return (control_net,)
class ControlNetInpaintingAliMamaApply(nodes.ControlNetApplyAdvanced):
@classmethod
def INPUT_TYPES(s):
return {"required": {"positive": ("CONDITIONING", ),
"negative": ("CONDITIONING", ),
"control_net": ("CONTROL_NET", ),
"vae": ("VAE", ),
"image": ("IMAGE", ),
"mask": ("MASK", ),
"strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}),
"start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}),
"end_percent": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001})
}}
FUNCTION = "apply_inpaint_controlnet"
CATEGORY = "conditioning/controlnet"
def apply_inpaint_controlnet(self, positive, negative, control_net, vae, image, mask, strength, start_percent, end_percent):
mask = 1.0 - mask.reshape((-1, 1, mask.shape[-2], mask.shape[-1]))
mask_apply = comfy.utils.common_upscale(mask, image.shape[2], image.shape[1], "bilinear", "center").round()
image = image * mask_apply.movedim(1, -1).repeat(1, 1, 1, image.shape[3])
return self.apply_controlnet(positive, negative, control_net, image, strength, start_percent, end_percent, vae=vae, extra_concat=[mask])
NODE_CLASS_MAPPINGS = {
"SetUnionControlNetType": SetUnionControlNetType,
"ControlNetInpaintingAliMamaApply": ControlNetInpaintingAliMamaApply,
}

4
nodes.py
View File

@ -824,7 +824,7 @@ class ControlNetApplyAdvanced:
CATEGORY = "conditioning/controlnet"
def apply_controlnet(self, positive, negative, control_net, image, strength, start_percent, end_percent, vae=None):
def apply_controlnet(self, positive, negative, control_net, image, strength, start_percent, end_percent, vae=None, extra_concat=[]):
if strength == 0:
return (positive, negative)
@ -841,7 +841,7 @@ class ControlNetApplyAdvanced:
if prev_cnet in cnets:
c_net = cnets[prev_cnet]
else:
c_net = control_net.copy().set_cond_hint(control_hint, strength, (start_percent, end_percent), vae)
c_net = control_net.copy().set_cond_hint(control_hint, strength, (start_percent, end_percent), vae=vae, extra_concat=extra_concat)
c_net.set_previous_controlnet(prev_cnet)
cnets[prev_cnet] = c_net