【InstantID】AIが本気を出した！マルチバース人物画像を生成できるAIの使い方を徹底解説

!pip install opencv-python transformers accelerate insightface onnxruntime controlnet-aux

!git clone https://github.com/instantX-research/InstantID.git

%cd InstantID

from huggingface_hub import hf_hub_download

hf_hub_download(repo_id="InstantX/InstantID", filename="ControlNetModel/config.json", local_dir="./checkpoints")

hf_hub_download(repo_id="InstantX/InstantID", filename="ControlNetModel/diffusion_pytorch_model.safetensors", local_dir="./checkpoints")

hf_hub_download(repo_id="InstantX/InstantID", filename="ip-adapter.bin", local_dir="./checkpoints")

├── models

  ├── checkpoints

  ├── ip_adapter

  ├── pipeline_stable_diffusion_xl_instantid.py

  └── README.md

import diffusers

from diffusers.utils import load_image

from diffusers.models import ControlNetModel

import cv2

import torch

import numpy as np

from PIL import Image

from insightface.app import FaceAnalysis

from pipeline_stable_diffusion_xl_instantid import StableDiffusionXLInstantIDPipeline, draw_kps

# prepare 'antelopev2' under ./models

app = FaceAnalysis(name='antelopev2', root='./', providers=['CUDAExecutionProvider', 'CPUExecutionProvider'])

app.prepare(ctx_id=0, det_size=(640, 640))

# prepare models under ./checkpoints

face_adapter = f'./checkpoints/ip-adapter.bin'

controlnet_path = f'./checkpoints/ControlNetModel/'

# load IdentityNet

controlnet = ControlNetModel.from_pretrained(controlnet_path, torch_dtype=torch.float16)

base_model = 'wangqixun/YamerMIX_v8'  # from https://civitai.com/models/84040?modelVersionId=196039

pipe = StableDiffusionXLInstantIDPipeline.from_pretrained(

base_model,

controlnet=controlnet,

torch_dtype=torch.float16

)

pipe.cuda()

# load adapter

pipe.load_ip_adapter_instantid(face_adapter)

# load an image

face_image = load_image("./examples/sam_resize.png")

# prepare face emb

face_info = app.get(cv2.cvtColor(np.array(face_image), cv2.COLOR_RGB2BGR))

face_info = sorted(face_info, key=lambda x:(x['bbox'][2]-x['bbox'][0])*x['bbox'][3]-x['bbox'][1])[-1] # only use the maximum face

face_emb = face_info['embedding']

face_kps = draw_kps(face_image, face_info['kps'])

pipe.set_ip_adapter_scale(0.8)

prompt = "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality"

negative_prompt = "(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"

# generate image

image = pipe(

    prompt, image_embeds=face_emb, image=face_kps, controlnet_conditioning_scale=0.8 ,ip_adapter_scale=0.8,).images[0]

display(image)

analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality