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import os, glob
from PIL import Image
import modules.scripts as scripts
# from modules.upscaler import Upscaler, UpscalerData
from modules import scripts, scripts_postprocessing
from modules.processing import (
StableDiffusionProcessing,
StableDiffusionProcessingImg2Img,
)
from modules.shared import state
from scripts.reactor_logger import logger
from scripts.reactor_swapper import (
swap_face,
swap_face_many,
get_current_faces_model,
analyze_faces,
half_det_size,
providers
)
import folder_paths
import comfy.model_management as model_management
def get_models():
swappers = [
"insightface",
"reswapper"
]
models_list = []
for folder in swappers:
models_folder = folder + "/*"
models_path = os.path.join(folder_paths.models_dir,models_folder)
models = glob.glob(models_path)
models = [x for x in models if x.endswith(".onnx") or x.endswith(".pth")]
models_list.extend(models)
return models_list
class FaceSwapScript(scripts.Script):
def process(
self,
p: StableDiffusionProcessing,
img,
enable,
source_faces_index,
faces_index,
model,
swap_in_source,
swap_in_generated,
gender_source,
gender_target,
face_model,
faces_order,
face_boost_enabled,
face_restore_model,
face_restore_visibility,
codeformer_weight,
interpolation,
):
self.enable = enable
if self.enable:
self.source = img
self.swap_in_generated = swap_in_generated
self.gender_source = gender_source
self.gender_target = gender_target
self.model = model
self.face_model = face_model
self.faces_order = faces_order
self.face_boost_enabled = face_boost_enabled
self.face_restore_model = face_restore_model
self.face_restore_visibility = face_restore_visibility
self.codeformer_weight = codeformer_weight
self.interpolation = interpolation
self.source_faces_index = [
int(x) for x in source_faces_index.strip(",").split(",") if x.isnumeric()
]
self.faces_index = [
int(x) for x in faces_index.strip(",").split(",") if x.isnumeric()
]
if len(self.source_faces_index) == 0:
self.source_faces_index = [0]
if len(self.faces_index) == 0:
self.faces_index = [0]
if self.gender_source is None or self.gender_source == "no":
self.gender_source = 0
elif self.gender_source == "female":
self.gender_source = 1
elif self.gender_source == "male":
self.gender_source = 2
if self.gender_target is None or self.gender_target == "no":
self.gender_target = 0
elif self.gender_target == "female":
self.gender_target = 1
elif self.gender_target == "male":
self.gender_target = 2
# if self.source is not None:
if isinstance(p, StableDiffusionProcessingImg2Img) and swap_in_source:
logger.status(f"Working: source face index %s, target face index %s", self.source_faces_index, self.faces_index)
if len(p.init_images) == 1:
result = swap_face(
self.source,
p.init_images[0],
source_faces_index=self.source_faces_index,
faces_index=self.faces_index,
model=self.model,
gender_source=self.gender_source,
gender_target=self.gender_target,
face_model=self.face_model,
faces_order=self.faces_order,
face_boost_enabled=self.face_boost_enabled,
face_restore_model=self.face_restore_model,
face_restore_visibility=self.face_restore_visibility,
codeformer_weight=self.codeformer_weight,
interpolation=self.interpolation,
)
p.init_images[0] = result
# for i in range(len(p.init_images)):
# if state.interrupted or model_management.processing_interrupted():
# logger.status("Interrupted by User")
# break
# if len(p.init_images) > 1:
# logger.status(f"Swap in %s", i)
# result = swap_face(
# self.source,
# p.init_images[i],
# source_faces_index=self.source_faces_index,
# faces_index=self.faces_index,
# model=self.model,
# gender_source=self.gender_source,
# gender_target=self.gender_target,
# face_model=self.face_model,
# )
# p.init_images[i] = result
elif len(p.init_images) > 1:
result = swap_face_many(
self.source,
p.init_images,
source_faces_index=self.source_faces_index,
faces_index=self.faces_index,
model=self.model,
gender_source=self.gender_source,
gender_target=self.gender_target,
face_model=self.face_model,
faces_order=self.faces_order,
face_boost_enabled=self.face_boost_enabled,
face_restore_model=self.face_restore_model,
face_restore_visibility=self.face_restore_visibility,
codeformer_weight=self.codeformer_weight,
interpolation=self.interpolation,
)
p.init_images = result
logger.status("--Done!--")
# else:
# logger.error(f"Please provide a source face")
def postprocess_batch(self, p, *args, **kwargs):
if self.enable:
images = kwargs["images"]
def postprocess_image(self, p, script_pp: scripts.PostprocessImageArgs, *args):
if self.enable and self.swap_in_generated:
if self.source is not None:
logger.status(f"Working: source face index %s, target face index %s", self.source_faces_index, self.faces_index)
image: Image.Image = script_pp.image
result = swap_face(
self.source,
image,
source_faces_index=self.source_faces_index,
faces_index=self.faces_index,
model=self.model,
upscale_options=self.upscale_options,
gender_source=self.gender_source,
gender_target=self.gender_target,
)
try:
pp = scripts_postprocessing.PostprocessedImage(result)
pp.info = {}
p.extra_generation_params.update(pp.info)
script_pp.image = pp.image
except:
logger.error(f"Cannot create a result image")
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