nodes/ZHO-ZHO-ZHO-ComfyUI-InstantID
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ZHO-ZHO-ZHO
2024-01-23 16:16:43 +08:00
committed by GitHub
parent 35d4379d8b
commit 2c481a5f4a
1 changed files with 129 additions and 57 deletions
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InstantIDNode.py
+129 -57
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@@ -1,6 +1,7 @@
import diffusers
from diffusers.utils import load_image
from diffusers.models import ControlNetModel
from .isid_style_template import styles
import os
import cv2
@@ -14,8 +15,15 @@ from insightface.app import FaceAnalysis
from .pipeline_stable_diffusion_xl_instantid import StableDiffusionXLInstantIDPipeline, draw_kps
current_directory = os.path.dirname(os.path.abspath(__file__))
device = "cuda" if torch.cuda.is_available() else "cpu"
STYLE_NAMES = list(styles.keys())
DEFAULT_STYLE_NAME = "Neon"
def apply_style(style_name: str, positive: str, negative: str = "") -> tuple[str, str]:
p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME])
return p.replace("{prompt}", positive), n + ' ' + negative
def resize_img(input_image, max_side=1280, min_side=1024, size=None,
@@ -50,8 +58,6 @@ class InsightFaceLoader_Node_Zho:
def INPUT_TYPES(s):
return {
"required": {
"insight_face_path": ("STRING", {"default": "enter path"}),
"filename": ("STRING", {"default": "buffalo_l"}),
"provider": (["CUDA", "CPU"], ),
},
}
@@ -60,14 +66,104 @@ class InsightFaceLoader_Node_Zho:
FUNCTION = "load_insight_face"
CATEGORY = "📷InstantID"
def load_insight_face(self, insight_face_path, filename, provider):
insight_face = os.path.join(insight_face_path, filename)
model = FaceAnalysis(name="buffalo_l", root=insight_face, providers=[provider + 'ExecutionProvider',])
def load_insight_face(self, provider):
model = FaceAnalysis(name="antelopev2", root=current_directory, providers=[provider + 'ExecutionProvider',])
model.prepare(ctx_id=0, det_size=(640, 640))
return (model,)
class IDControlNetLoaderNode_Zho:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"controlnet_path": ("STRING", {"default": "enter your path"}),
}
}
RETURN_TYPES = ("MODEL",)
RETURN_NAMES = ("controlnet",)
FUNCTION = "load_idcontrolnet"
CATEGORY = "📷InstantID"
def load_idcontrolnet(self, controlnet_path):
controlnet = ControlNetModel.from_pretrained(controlnet_path, torch_dtype=torch.float16)
return [controlnet]
class IDBaseModelLoader_fromhub_Node_Zho:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"base_model_path": ("STRING", {"default": "wangqixun/YamerMIX_v8"}),
"controlnet": ("MODEL",)
}
}
RETURN_TYPES = ("MODEL",)
RETURN_NAMES = ("pipe",)
FUNCTION = "load_model"
CATEGORY = "📷InstantID"
def load_model(self, base_model_path, controlnet):
# Code to load the base model
pipe = StableDiffusionXLInstantIDPipeline.from_pretrained(
base_model_path,
controlnet=controlnet,
torch_dtype=torch.float16,
local_dir="./checkpoints"
).to(device)
return [pipe]
class IDBaseModelLoader_local_Node_Zho:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"ckpt_name": (folder_paths.get_filename_list("checkpoints"), ),
"controlnet": ("MODEL",)
}
}
RETURN_TYPES = ("MODEL",)
RETURN_NAMES = ("pipe",)
FUNCTION = "load_model"
CATEGORY = "📷InstantID"
def load_model(self, ckpt_name, controlnet):
# Code to load the base model
if not ckpt_name:
raise ValueError("Please provide the ckpt_name parameter with the name of the checkpoint file.")
ckpt_path = folder_paths.get_full_path("checkpoints", ckpt_name)
if not os.path.exists(ckpt_path):
raise FileNotFoundError(f"Checkpoint file {ckpt_path} not found.")
pipe = StableDiffusionXLInstantIDPipeline.from_single_file(
pretrained_model_link_or_path=ckpt_path,
controlnet=controlnet,
torch_dtype=torch.float16,
use_safetensors=True,
variant="fp16"
).to(device)
return [pipe]
class Ipadapter_instantidLoader_Node_Zho:
def __init__(self):
pass
@@ -96,7 +192,7 @@ class Ipadapter_instantidLoader_Node_Zho:
return [pipe]
class ControlNetLoader_local_Node_Zho:
class ID_Prompt_Style_Zho:
def __init__(self):
pass
@@ -104,52 +200,24 @@ class ControlNetLoader_local_Node_Zho:
def INPUT_TYPES(cls):
return {
"required": {
"controlnet_path": ("STRING", {"default": "enter your path"}),
"prompt": ("STRING", {"default": "analog film photo of a woman. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality", "multiline": True}),
"negative_prompt": ("STRING", {"default": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured", "multiline": True}),
"style_name": (STYLE_NAMES, {"default": DEFAULT_STYLE_NAME})
}
}
RETURN_TYPES = ("MODEL",)
RETURN_NAMES = ("controlnet",)
FUNCTION = "load_controlnet"
RETURN_TYPES = ('STRING','STRING',)
RETURN_NAMES = ('positive_prompt','negative_prompt',)
FUNCTION = "prompt_style"
CATEGORY = "📷InstantID"
def load_controlnet(self, controlnet_path):
controlnet = ControlNetModel.from_pretrained(controlnet_path, torch_dtype=torch.float16)
return [controlnet]
def prompt_style(self, style_name, prompt, negative_prompt):
prompt, negative_prompt = apply_style(style_name, prompt, negative_prompt)
return prompt, negative_prompt
class BaseModelLoader_fromhub_Node_Zho:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"base_model_path": ("STRING", {"default": "wangqixun/YamerMIX_v8"}),
"controlnet": ("MODEL",)
}
}
RETURN_TYPES = ("MODEL",)
RETURN_NAMES = ("pipe",)
FUNCTION = "load_model"
CATEGORY = "📷InstantID"
def load_model(self, base_model_path, controlnet):
# Code to load the base model
pipe = StableDiffusionXLInstantIDPipeline.from_pretrained(
base_model_path,
controlnet=controlnet,
torch_dtype=torch.float16,
local_dir="./checkpoints"
).to(device)
return [pipe]
class GenerationNode_Zho:
class IDGenerationNode_Zho:
def __init__(self):
pass
@@ -160,8 +228,8 @@ class GenerationNode_Zho:
"face_image": ("IMAGE",),
"pipe": ("MODEL",),
"insightface": ("INSIGHTFACE",),
"prompt": ("STRING", {"default": "film noir style, ink sketch|vector, male man, highly detailed, sharp focus, ultra sharpness, monochrome, high contrast, dramatic shadows, 1940s style, mysterious, cinematic", "multiline": True}),
"negative_prompt": ("STRING", {"default": "ugly, deformed, noisy, blurry, low contrast, realism, photorealistic, vibrant, colorful", "multiline": True}),
"positive": ("STRING", {"multiline": True, "forceInput": True}),
"negative": ("STRING", {"multiline": True, "forceInput": True}),
"batch_size": ("INT", {"default": 1, "min": 1, "max": 4, "display": "slider"}),
"ip_adapter_scale": ("FLOAT", {"default": 0.8, "min": 0, "max": 1.0, "display": "slider"}),
"controlnet_conditioning_scale": ("FLOAT", {"default": 0.8, "min": 0, "max": 1.0, "display": "slider"}),
@@ -177,7 +245,7 @@ class GenerationNode_Zho:
FUNCTION = "generate_image"
CATEGORY = "📷InstantID"
def generate_image(self, insightface, prompt, negative_prompt, face_image, pipe, batch_size, ip_adapter_scale, controlnet_conditioning_scale, steps, guidance_scale, width, height, seed):
def generate_image(self, insightface, positive, negative, face_image, pipe, batch_size, ip_adapter_scale, controlnet_conditioning_scale, steps, guidance_scale, width, height, seed):
face_image = resize_img(face_image)
@@ -195,8 +263,8 @@ class GenerationNode_Zho:
pipe.set_ip_adapter_scale(ip_adapter_scale)
output = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
prompt=positive,
negative_prompt=negative,
num_images_per_prompt=batch_size,
image_embeds=face_emb,
image=face_kps,
@@ -242,16 +310,20 @@ class GenerationNode_Zho:
NODE_CLASS_MAPPINGS = {
"InsightFaceLoader": InsightFaceLoader_Node_Zho,
"ControlNetLoader_local": ControlNetLoader_local_Node_Zho,
"BaseModelLoader_fromhub": BaseModelLoader_fromhub_Node_Zho,
"IDControlNetLoader": IDControlNetLoaderNode_Zho,
"IDBaseModelLoader_fromhub": IDBaseModelLoader_fromhub_Node_Zho,
"IDBaseModelLoader_local": IDBaseModelLoader_local_Node_Zho,
"Ipadapter_instantidLoader": Ipadapter_instantidLoader_Node_Zho,
"GenerationNode": GenerationNode_Zho
"ID_Prompt_Styler": ID_Prompt_Style_Zho,
"IDGenerationNode": IDGenerationNode_Zho
}
NODE_DISPLAY_NAME_MAPPINGS = {
"InsightFaceLoader": "📷InsightFace Loader",
"ControlNetLoader_local": "📷ControlNet Loader local",
"BaseModelLoader_fromhub": "📷Base Model Loader fromhub",
"IDControlNetLoader": "📷ID ControlNet Loader",
"IDBaseModelLoader_fromhub": "📷ID Base Model Loader from hub 🤗",
"IDBaseModelLoader_local": "📷ID Base Model Loader locally",
"Ipadapter_instantidLoader": "📷Ipadapter_instantid Loader",
"GenerationNode": "📷InstantID Generation"
"ID_Prompt_Styler": "📷ID Prompt_Styler",
"IDGenerationNode": "📷InstantID Generation"
}