Pishtiwan MoradiandClaude Sonnet 4.5
92e062ff34
Added models: - Wan2.2 diffusion models: T2V, Animate 14B, T2V Low Noise - Wan2.2 LoRAs: Lightning 4-step, Lightx2v, Relight, Distill - Text encoders: UMT5-XXL (fp8 and bf16 variants) - CLIP Vision H for Wan workflows - InsightFace buffalo_l model for face detection - IP-Adapter Plus SDXL VIT-H - RealESRGAN x4 upscaler - Wan 2.1 VAE Updated file permissions to executable for all Python files and documentation. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
305 lines
11 KiB
Python
Executable File
305 lines
11 KiB
Python
Executable File
import torch
|
|
import numpy as np
|
|
from PIL import Image
|
|
import folder_paths
|
|
import comfy.model_management as mm
|
|
|
|
|
|
class CharacterSwapNode:
|
|
"""
|
|
ComfyUI node that takes a reference image for pose/scene and applies a character's face.
|
|
Uses ControlNet for structure transfer and face models for identity preservation.
|
|
"""
|
|
|
|
def __init__(self):
|
|
self.type = "CharacterSwapNode"
|
|
|
|
@classmethod
|
|
def INPUT_TYPES(cls):
|
|
return {
|
|
"required": {
|
|
"reference_image": ("IMAGE",),
|
|
"character_face": ("IMAGE",),
|
|
"positive_prompt": ("STRING", {
|
|
"multiline": True,
|
|
"default": "high quality, detailed face, professional photo, 8k"
|
|
}),
|
|
"negative_prompt": ("STRING", {
|
|
"multiline": True,
|
|
"default": "bad face, deformed, ugly, blurry, low quality, bad anatomy"
|
|
}),
|
|
"pose_strength": ("FLOAT", {
|
|
"default": 1.0,
|
|
"min": 0.0,
|
|
"max": 2.0,
|
|
"step": 0.05,
|
|
"display": "slider"
|
|
}),
|
|
"depth_strength": ("FLOAT", {
|
|
"default": 0.7,
|
|
"min": 0.0,
|
|
"max": 2.0,
|
|
"step": 0.05,
|
|
"display": "slider"
|
|
}),
|
|
"face_strength": ("FLOAT", {
|
|
"default": 0.85,
|
|
"min": 0.0,
|
|
"max": 1.0,
|
|
"step": 0.05,
|
|
"display": "slider"
|
|
}),
|
|
"seed": ("INT", {
|
|
"default": 0,
|
|
"min": 0,
|
|
"max": 0xffffffffffffffff
|
|
}),
|
|
},
|
|
"optional": {
|
|
"canny_strength": ("FLOAT", {
|
|
"default": 0.5,
|
|
"min": 0.0,
|
|
"max": 2.0,
|
|
"step": 0.05,
|
|
"display": "slider"
|
|
}),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ("IMAGE", "IMAGE", "IMAGE")
|
|
RETURN_NAMES = ("output_image", "pose_preview", "depth_preview")
|
|
FUNCTION = "swap_character"
|
|
CATEGORY = "PMA Utils/Character"
|
|
|
|
def swap_character(self, reference_image, character_face, positive_prompt,
|
|
negative_prompt, pose_strength, depth_strength, face_strength,
|
|
seed, canny_strength=0.5):
|
|
"""
|
|
Main function to swap character face into reference pose/scene.
|
|
|
|
Args:
|
|
reference_image: Source image for pose/background/scene
|
|
character_face: Character's face reference image
|
|
positive_prompt: Text prompt for generation
|
|
negative_prompt: Negative prompt
|
|
pose_strength: OpenPose ControlNet strength
|
|
depth_strength: Depth ControlNet strength
|
|
face_strength: Face identity strength
|
|
seed: Random seed
|
|
canny_strength: Canny edge ControlNet strength
|
|
|
|
Returns:
|
|
Tuple of (output_image, pose_preview, depth_preview)
|
|
"""
|
|
|
|
print("[CharacterSwap] Starting character swap process...")
|
|
|
|
# Convert ComfyUI image format to PIL
|
|
ref_pil = self.tensor_to_pil(reference_image)
|
|
char_face_pil = self.tensor_to_pil(character_face)
|
|
|
|
# STEP 1: Extract ControlNet maps
|
|
print("[CharacterSwap] Extracting ControlNet preprocessors...")
|
|
pose_map = self.extract_openpose(ref_pil)
|
|
depth_map = self.extract_depth(ref_pil)
|
|
|
|
# STEP 2: For now, return previews and placeholder
|
|
# TODO: Integrate with ComfyUI's ControlNet pipeline
|
|
# TODO: Add IP-Adapter FaceID integration
|
|
# TODO: Add ReActor face swap integration
|
|
|
|
print("[CharacterSwap] WARNING: This is a placeholder implementation.")
|
|
print("[CharacterSwap] Full ControlNet integration requires:")
|
|
print("[CharacterSwap] - ComfyUI-ControlNet-Aux for preprocessors")
|
|
print("[CharacterSwap] - ControlNet models loaded")
|
|
print("[CharacterSwap] - IP-Adapter or ReActor nodes")
|
|
|
|
# Convert back to ComfyUI tensor format
|
|
pose_tensor = self.pil_to_tensor(pose_map)
|
|
depth_tensor = self.pil_to_tensor(depth_map)
|
|
output_tensor = reference_image # Placeholder - return original for now
|
|
|
|
return (output_tensor, pose_tensor, depth_tensor)
|
|
|
|
def tensor_to_pil(self, tensor):
|
|
"""Convert ComfyUI image tensor to PIL Image."""
|
|
# ComfyUI format: [B, H, W, C] in range [0, 1]
|
|
if len(tensor.shape) == 4:
|
|
tensor = tensor[0] # Take first batch item
|
|
|
|
# Convert to numpy and scale to [0, 255]
|
|
np_image = (tensor.cpu().numpy() * 255).astype(np.uint8)
|
|
|
|
# Convert to PIL
|
|
pil_image = Image.fromarray(np_image)
|
|
return pil_image
|
|
|
|
def pil_to_tensor(self, pil_image):
|
|
"""Convert PIL Image to ComfyUI image tensor."""
|
|
# Convert to numpy
|
|
np_image = np.array(pil_image).astype(np.float32) / 255.0
|
|
|
|
# Convert to torch tensor [H, W, C]
|
|
tensor = torch.from_numpy(np_image)
|
|
|
|
# Add batch dimension [1, H, W, C]
|
|
tensor = tensor.unsqueeze(0)
|
|
|
|
return tensor
|
|
|
|
def extract_openpose(self, pil_image):
|
|
"""
|
|
Extract OpenPose skeleton from image.
|
|
|
|
NOTE: This requires ComfyUI-ControlNet-Aux to be installed.
|
|
Install: cd custom_nodes && git clone https://github.com/Fannovel16/comfyui_controlnet_aux
|
|
"""
|
|
try:
|
|
from controlnet_aux import OpenposeDetector
|
|
|
|
detector = OpenposeDetector.from_pretrained("lllyasviel/ControlNet")
|
|
pose_image = detector(pil_image)
|
|
|
|
print("[CharacterSwap] OpenPose extracted successfully")
|
|
return pose_image
|
|
|
|
except ImportError:
|
|
print("[CharacterSwap] ERROR: controlnet_aux not found!")
|
|
print("[CharacterSwap] Install: pip install controlnet-aux")
|
|
print("[CharacterSwap] Or clone: https://github.com/Fannovel16/comfyui_controlnet_aux")
|
|
|
|
# Return grayscale placeholder
|
|
return pil_image.convert("L").convert("RGB")
|
|
except Exception as e:
|
|
print(f"[CharacterSwap] Error extracting OpenPose: {e}")
|
|
return pil_image.convert("L").convert("RGB")
|
|
|
|
def extract_depth(self, pil_image):
|
|
"""
|
|
Extract depth map from image.
|
|
|
|
NOTE: This requires ComfyUI-ControlNet-Aux to be installed.
|
|
"""
|
|
try:
|
|
from controlnet_aux import MidasDetector
|
|
|
|
detector = MidasDetector.from_pretrained("lllyasviel/ControlNet")
|
|
depth_image = detector(pil_image)
|
|
|
|
print("[CharacterSwap] Depth map extracted successfully")
|
|
return depth_image
|
|
|
|
except ImportError:
|
|
print("[CharacterSwap] ERROR: controlnet_aux not found!")
|
|
print("[CharacterSwap] Install: pip install controlnet-aux")
|
|
|
|
# Return grayscale placeholder
|
|
return pil_image.convert("L").convert("RGB")
|
|
except Exception as e:
|
|
print(f"[CharacterSwap] Error extracting depth: {e}")
|
|
return pil_image.convert("L").convert("RGB")
|
|
|
|
def extract_canny(self, pil_image, low_threshold=100, high_threshold=200):
|
|
"""Extract Canny edges from image."""
|
|
try:
|
|
from controlnet_aux import CannyDetector
|
|
|
|
detector = CannyDetector()
|
|
canny_image = detector(pil_image, low_threshold, high_threshold)
|
|
|
|
print("[CharacterSwap] Canny edges extracted successfully")
|
|
return canny_image
|
|
|
|
except ImportError:
|
|
print("[CharacterSwap] ERROR: controlnet_aux not found!")
|
|
return pil_image.convert("L").convert("RGB")
|
|
except Exception as e:
|
|
print(f"[CharacterSwap] Error extracting Canny: {e}")
|
|
return pil_image.convert("L").convert("RGB")
|
|
|
|
|
|
class CharacterSwapAdvanced(CharacterSwapNode):
|
|
"""
|
|
Advanced version with full pipeline integration.
|
|
This will require the following nodes to be properly connected in the workflow.
|
|
"""
|
|
|
|
@classmethod
|
|
def INPUT_TYPES(cls):
|
|
base_inputs = super().INPUT_TYPES()
|
|
|
|
# Add model and ControlNet inputs
|
|
base_inputs["required"].update({
|
|
"model": ("MODEL",),
|
|
"vae": ("VAE",),
|
|
"clip": ("CLIP",),
|
|
})
|
|
|
|
base_inputs["optional"].update({
|
|
"openpose_controlnet": ("CONTROL_NET",),
|
|
"depth_controlnet": ("CONTROL_NET",),
|
|
"canny_controlnet": ("CONTROL_NET",),
|
|
"ipadapter_model": ("IPADAPTER",),
|
|
})
|
|
|
|
return base_inputs
|
|
|
|
RETURN_TYPES = ("IMAGE", "IMAGE", "IMAGE", "LATENT")
|
|
RETURN_NAMES = ("output_image", "pose_preview", "depth_preview", "latent")
|
|
FUNCTION = "swap_character_advanced"
|
|
|
|
def swap_character_advanced(self, reference_image, character_face, positive_prompt,
|
|
negative_prompt, pose_strength, depth_strength, face_strength,
|
|
seed, model, vae, clip, canny_strength=0.5,
|
|
openpose_controlnet=None, depth_controlnet=None,
|
|
canny_controlnet=None, ipadapter_model=None):
|
|
"""
|
|
Advanced character swap with full model integration.
|
|
|
|
This version integrates with ComfyUI's native nodes for:
|
|
- ControlNet application
|
|
- IP-Adapter FaceID
|
|
- VAE encoding/decoding
|
|
- CLIP text encoding
|
|
"""
|
|
|
|
print("[CharacterSwap Advanced] Starting full pipeline...")
|
|
|
|
# Get preprocessor outputs
|
|
ref_pil = self.tensor_to_pil(reference_image)
|
|
pose_map = self.extract_openpose(ref_pil)
|
|
depth_map = self.extract_depth(ref_pil)
|
|
|
|
pose_tensor = self.pil_to_tensor(pose_map)
|
|
depth_tensor = self.pil_to_tensor(depth_map)
|
|
|
|
# TODO: Implement full pipeline
|
|
# 1. Encode text prompts with CLIP
|
|
# 2. Apply ControlNets (OpenPose, Depth, Canny)
|
|
# 3. Generate latent with model
|
|
# 4. Apply IP-Adapter FaceID
|
|
# 5. Decode with VAE
|
|
|
|
print("[CharacterSwap Advanced] Full pipeline not yet implemented")
|
|
print("[CharacterSwap Advanced] Use standard ComfyUI workflow for now:")
|
|
print("[CharacterSwap Advanced] 1. Use this node to get pose/depth maps")
|
|
print("[CharacterSwap Advanced] 2. Connect to ControlNet Apply nodes")
|
|
print("[CharacterSwap Advanced] 3. Connect to IPAdapter FaceID")
|
|
print("[CharacterSwap Advanced] 4. Connect to KSampler")
|
|
|
|
# Return previews and empty latent
|
|
empty_latent = {"samples": torch.zeros((1, 4, 64, 64))}
|
|
|
|
return (reference_image, pose_tensor, depth_tensor, empty_latent)
|
|
|
|
|
|
NODE_CLASS_MAPPINGS = {
|
|
"PMACharacterSwap": CharacterSwapNode,
|
|
"PMACharacterSwapAdvanced": CharacterSwapAdvanced,
|
|
}
|
|
|
|
NODE_DISPLAY_NAME_MAPPINGS = {
|
|
"PMACharacterSwap": "PMA Character Swap (Basic)",
|
|
"PMACharacterSwapAdvanced": "PMA Character Swap (Advanced)",
|
|
}
|