alphard/efficiency-nodes-comfyui
1
0
Fork 0
mirror of https://github.com/jags111/efficiency-nodes-comfyui.git synced 2026-03-21 21:22:13 -03:00
Code Issues Packages Projects Releases Wiki Activity

Control Net Stack Apply Fix

Browse Source
This commit is contained in:
TSC
2023-09-05 12:36:41 -05:00
committed by GitHub
parent 6ca74a8a68
commit a468ffd7a2
1 changed files with 15 additions and 14 deletions
Download Patch File Download Diff File Expand all files Collapse all files

27
efficiency_nodes.py
View File

@@ -168,7 +168,8 @@ class TSC_EfficientLoader:
# Apply ControlNet Stack if given
if cnet_stack:
positive_encoded = TSC_Apply_ControlNet_Stack().apply_cnet_stack(positive_encoded,cnet_stack)[0]
controlnet_conditioning = TSC_Apply_ControlNet_Stack().apply_cnet_stack(positive_encoded, negative_encoded, cnet_stack)
positive_encoded, negative_encoded = controlnet_conditioning[0], controlnet_conditioning[1]
# Check for custom VAE
if vae_name != "Baked VAE":
@@ -356,22 +357,23 @@ class TSC_Apply_ControlNet_Stack:
@classmethod
def INPUT_TYPES(cls):
return {"required": {"conditioning": ("CONDITIONING",),
return {"required": {"positive": ("CONDITIONING",),
"negative": ("CONDITIONING",),
"cnet_stack": ("CONTROL_NET_STACK",)},
}
RETURN_TYPES = ("CONDITIONING",)
RETURN_NAMES = ("CONDITIONING",)
RETURN_TYPES = ("CONDITIONING","CONDITIONING",)
RETURN_NAMES = ("CONDITIONING+","CONDITIONING-",)
FUNCTION = "apply_cnet_stack"
CATEGORY = "Efficiency Nodes/Stackers"
def apply_cnet_stack(self, conditioning, cnet_stack):
def apply_cnet_stack(self, positive, negative, cnet_stack):
for control_net_tuple in cnet_stack:
control_net, image, strength, start_percent, end_percent = control_net_tuple
conditioning_new = ControlNetApplyAdvanced().apply_controlnet(conditioning, conditioning,
controlnet_conditioning = ControlNetApplyAdvanced().apply_controlnet(positive, negative,
control_net, image, strength,
start_percent, end_percent)[0]
return (conditioning_new,)
start_percent, end_percent)
return controlnet_conditioning
########################################################################################################################
# TSC KSampler (Efficient)
@@ -1379,7 +1381,8 @@ class TSC_KSampler:
empty_latent_height, return_type="base")
# Apply ControlNet Stack if given
if cnet_stack:
positive = TSC_Apply_ControlNet_Stack().apply_cnet_stack(positive, cnet_stack)
controlnet_conditioning = TSC_Apply_ControlNet_Stack().apply_cnet_stack(positive, negative, cnet_stack)
positive, negative = controlnet_conditioning[0], controlnet_conditioning[1]
if encode_refiner == True:
refiner_positive, refiner_negative = \
@@ -1417,10 +1420,8 @@ class TSC_KSampler:
send_command_to_frontend(startListening=True, maxCount=steps - 1, sendBlob=False)
samples = sample_latent_image(model, seed, steps, cfg, sampler_name, scheduler, positive, negative,
latent_image, denoise, sampler_type, add_noise, start_at_step,
end_at_step,
return_with_leftover_noise, refiner_model, refiner_positive,
refiner_negative)
latent_image, denoise, sampler_type, add_noise, start_at_step, end_at_step,
return_with_leftover_noise, refiner_model, refiner_positive, refiner_negative)
# Add the latent tensor to the tensors list
latent_list.append(samples)