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from typing import List
import os
import cv2
import numpy as np
import huggingface_hub as hf
from PIL import Image
from modules import processing, shared, devices
debug = shared.log.trace if os.environ.get('SD_FACE_DEBUG', None) is not None else lambda *args, **kwargs: None
insightface_app = None
swapper = None
def face_swap(p: processing.StableDiffusionProcessing, app, input_images: List[Image.Image], source_image: Image.Image, cache: bool):
import insightface.model_zoo
global swapper # pylint: disable=global-statement
if swapper is None:
model_path = hf.hf_hub_download(repo_id='ezioruan/inswapper_128.onnx', filename='inswapper_128.onnx', cache_dir=shared.opts.diffusers_dir)
router: insightface.model_zoo.model_zoo.INSwapper = insightface.model_zoo.model_zoo.ModelRouter(model_path)
swapper = router.get_model()
np_image = cv2.cvtColor(np.array(source_image), cv2.COLOR_RGB2BGR)
faces = app.get(np_image)
source_face = faces[0]
processed_images = []
for image in input_images:
np_image = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
faces = app.get(np_image)
for i, face in enumerate(faces):
debug(f'FaceSwap: face={i} source={source_face.bbox} target={face.bbox}')
np_image = swapper.get(img=np_image, target_face=face, source_face=source_face, paste_back=True) # pylint: disable=unexpected-keyword-arg, no-value-for-parameter
p.extra_generation_params["FaceSwap"] = f'{len(faces)}'
np_image = cv2.cvtColor(np_image, cv2.COLOR_BGR2RGB)
processed_images.append(Image.fromarray(np_image))
if not cache:
swapper = None
devices.torch_gc()
return processed_images
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