3 changed files with 96 additions and 23 deletions
+25 -4
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@@ -1,13 +1,34 @@
import os
import subprocess
from huggingface_hub import snapshot_download
from huggingface_hub import snapshot_download, hf_hub_download
parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
models_dir = os.path.abspath(os.path.join(parent_dir, '..', "models"))
print(models_dir)
# Download the model from the Hugging Face Hub
repo_id = "LiuZichen/MagicQuill-models" # or any other model/dataset ID
snapshot_download(repo_id=repo_id, local_dir=models_dir)
hugging_face_repos = [
{
'repo_id': 'LiuZichen/MagicQuill-models',
'local_dir': models_dir
},
{
'repo_id': 'InstantX/FLUX.1-dev-Controlnet-Union',
'local_dir': os.path.join(models_dir, 'controlnet', 'FLUX1'),
'filename': 'diffusion_pytorch_model.safetensors',
'target_filename': 'FLUX.1-dev-Controlnet-Union.safetensors'
}
]
for repo in hugging_face_repos:
if 'filename' in repo:
filename = hf_hub_download(repo_id=repo['repo_id'], local_dir=repo['local_dir'], filename=repo['filename'])
current_path = os.path.join(repo['local_dir'], filename)
target_path = os.path.join(repo['local_dir'], repo['target_filename'])
if os.path.exists(current_path):
if current_path != target_path:
os.rename(current_path, target_path)
else:
snapshot_download(repo_id=repo['repo_id'], local_dir=repo['local_dir'])
repos = {
'ComfyUI_BrushNet': 'https://github.com/nullquant/ComfyUI-BrushNet',
+9 -1
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@@ -284,6 +284,14 @@ async def run_magic_quill(request):
sampler_name = post.get("sampler_name", "euler_ancestral")
scheduler = post.get("scheduler", "exponential")
if "FLUX" in checkpoint_name:
base_model_version = "FLUX"
elif "SDXL" in checkpoint_name:
base_model_version = "SDXL"
else:
base_model_version = "SD1.5"
print(f"Base model version: {base_model_version} checkpoint_name: {checkpoint_name}")
print(f"Using files - Main: {main_image_filename}, Original: {original_image_file}, Add Color: {add_color_image_file}, Add Edge: {add_edge_image_file}, Remove Edge: {remove_edge_image_file}")
# Call painter_execute with file paths instead of tensors
@@ -380,7 +388,7 @@ class MagicQuill(object):
"clip": ("CLIP",),
"vae": ("VAE",),
"base_model_version": (['SD1.5'], {"default": "SD1.5"}),
"base_model_version": (['SD1.5', 'FLUX'], {"default": "SD1.5"}),
"positive_prompt": ("STRING", {"default": ""}),
"negative_prompt": ("STRING", {"default": ""}),
"dtype": (['float16', 'bfloat16', 'float32', 'float64'], {"default": "float16"}),
+62 -18
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@@ -16,7 +16,11 @@ from comfyui_controlnet_aux.node_wrappers.lineart import LineArt_Preprocessor
from comfyui_controlnet_aux.node_wrappers.pidinet import PIDINET_Preprocessor
from comfyui_controlnet_aux.node_wrappers.color import Color_Preprocessor
from nodes import ControlNetLoader, ControlNetApplyAdvanced, CLIPTextEncode, KSampler, VAEDecode
from comfy_extras.nodes_controlnet import SetUnionControlNetType
from comfy_extras.nodes_differential_diffusion import DifferentialDiffusion
from comfy_extras.nodes_flux import FluxGuidance
from nodes import ControlNetLoader, ControlNetApplyAdvanced, CLIPTextEncode, KSampler, VAEDecode, InpaintModelConditioning
from nodes_mask import GrowMask
class ScribbleColorEditModel():
@@ -36,17 +40,36 @@ class ScribbleColorEditModel():
# self.load_models('SD1.5', 'float16')
def load_models(self, base_model_version, dtype):
print(f"Loading models for base_model_version: {base_model_version}")
if base_model_version == "SD1.5":
edge_controlnet_name = "control_v11p_sd15_scribble.safetensors"
color_controlnet_name = "color_finetune.safetensors"
brushnet_name = os.path.join("brushnet", "random_mask_brushnet_ckpt", "diffusion_pytorch_model.safetensors")
print(f"Loading models for base_model_version: {base_model_version}")
elif base_model_version == "SDXL":
edge_controlnet_name = os.path.join("SDXL", "sd_xl_base_1.0_controlnet.safetensors")
color_controlnet_name = None # TODO: add color controlnet for SDXL
brushnet_name = None # TODO: add brushnet for SDXL
print(f"Loading models for SDXL base_model_version: {base_model_version}")
elif base_model_version == "FLUX":
edge_controlnet_name = os.path.join("FLUX.1", "Shakker-Labs-ControlNet-Union-Pro","diffusion_pytorch_model.safetensors")
color_controlnet_name = None # TODO: add color controlnet for FLUX
brushnet_name = None # TODO: add brushnet for FLUX
print(f"Loading models for Flux base_model_version: {base_model_version}")
else:
raise ValueError("Invalid base_model_version, not supported yet!!!: {}".format(base_model_version))
self.edge_controlnet = self.controlnet_loader.load_controlnet(edge_controlnet_name)[0]
self.color_controlnet = self.controlnet_loader.load_controlnet(color_controlnet_name)[0]
self.brushnet_loader.inpaint_files = get_files_with_extension('inpaint')
print("self.brushnet_loader.inpaint_files: ", get_files_with_extension('inpaint'))
self.brushnet = self.brushnet_loader.brushnet_loading(brushnet_name, dtype)[0]
if color_controlnet_name:
self.color_controlnet = self.controlnet_loader.load_controlnet(color_controlnet_name)[0]
else:
self.color_controlnet = None
if brushnet_name:
self.brushnet_loader.inpaint_files = get_files_with_extension('inpaint')
print("self.brushnet_loader.inpaint_files: ", get_files_with_extension('inpaint'))
self.brushnet = self.brushnet_loader.brushnet_loading(brushnet_name, dtype)[0]
else:
self.brushnet = None
def safe_vae_decode(self, vae, latent_samples):
"""Safe VAE decoding that handles inference tensors correctly."""
@@ -92,6 +115,8 @@ class ScribbleColorEditModel():
image_copy[bool_add_mask] = 1.0
if not torch.equal(image, colored_image):
if base_model_version == "FLUX":
raise ValueError('Not implemented.')
print("Apply color controlnet")
color_output = self.color_processor.execute(colored_image, resolution=2048)[0]
lineart_output = self.lineart_processor.execute(image, resolution=512, coarse=False)[0]
@@ -116,20 +141,39 @@ class ScribbleColorEditModel():
lineart_output[bool_add_mask_resized] = 1.0
else:
lineart_output[bool_remove_mask_resized & ~bool_add_mask_resized] = 0.0
positive, negative = self.controlnet_apply.apply_controlnet(positive, negative, self.edge_controlnet, lineart_output, edge_strength, 0.0, 1.0)
if base_model_version == "FLUX":
self.edge_controlnet = (SetUnionControlNetType().set_controlnet_type(self.edge_controlnet, 2))[0] # set union type to hed/pidi/scribble/ted
model = (DifferentialDiffusion().apply(model))[0] # apply Differential Diffusion
positive = (FluxGuidance().append(positive, 30))[0] # apply flux guidence
positive, negative = self.controlnet_apply.apply_controlnet(positive, negative, self.edge_controlnet, lineart_output, edge_strength, 0.0, 1.0, vae)
if base_model_version == "FLUX":
positive, negative, latent = InpaintModelConditioning().encode(positive, negative, image, vae, mask, False) # apply inpaint
# if base_model_version == "SD1.5":
# positive, negative = self.controlnet_apply.apply_controlnet(positive, negative, self.edge_controlnet, lineart_output, edge_strength, 0.0, 1.0)
# else:
# positive, negative = self.controlnet_apply.apply_controlnet(positive, negative, self.edge_controlnet, lineart_output, edge_strength, vae, 0.0, 1.0)
if base_model_version == "FLUX":
positive, negative, latent = InpaintModelConditioning().encode(positive, negative, image, vae, mask, False) # apply inpaint
else:
model, positive, negative, latent = self.brushnet_node.model_update(
model=model,
vae=vae,
image=image,
mask=mask,
brushnet=self.brushnet,
positive=positive,
negative=negative,
scale=inpaint_strength,
start_at=0,
end_at=10000
)
model, positive, negative, latent = self.brushnet_node.model_update(
model=model,
vae=vae,
image=image,
mask=mask,
brushnet=self.brushnet,
positive=positive,
negative=negative,
scale=inpaint_strength,
start_at=0,
end_at=10000
)
latent_samples = self.ksampler.sample(
model=model,