CalvinBackup/sd-webui-faceswaplab
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add pre-commit hooks configuration

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This commit is contained in:
Tran Xen
2023-07-28 18:25:28 +02:00
parent 8577d0186d
commit 5d4a29ff1e
33 changed files with 1674 additions and 820 deletions
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scripts/faceswaplab_postprocessing/i2i_pp.py
+38 -28
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@@ -6,26 +6,29 @@ import numpy as np
from modules import shared
from scripts.faceswaplab_utils import imgutils
from modules import shared, processing, codeformer_model
from modules.processing import (StableDiffusionProcessingImg2Img)
from scripts.faceswaplab_postprocessing.postprocessing_options import PostProcessingOptions, InpaintingWhen
from modules.processing import StableDiffusionProcessingImg2Img
from scripts.faceswaplab_postprocessing.postprocessing_options import (
PostProcessingOptions,
InpaintingWhen,
)
from modules import sd_models
from scripts.faceswaplab_swapping import swapper
def img2img_diffusion(img : Image.Image, pp: PostProcessingOptions) -> Image.Image :
if pp.inpainting_denoising_strengh == 0 :
def img2img_diffusion(img: Image.Image, pp: PostProcessingOptions) -> Image.Image:
if pp.inpainting_denoising_strengh == 0:
return img
try :
try:
logger.info(
f"""Inpainting face
f"""Inpainting face
Sampler : {pp.inpainting_sampler}
inpainting_denoising_strength : {pp.inpainting_denoising_strengh}
inpainting_steps : {pp.inpainting_steps}
"""
)
if not isinstance(pp.inpainting_sampler, str) :
)
if not isinstance(pp.inpainting_sampler, str):
pass
logger.info("send faces to image to image")
@@ -33,44 +36,51 @@ inpainting_steps : {pp.inpainting_steps}
faces = swapper.get_faces(imgutils.pil_to_cv2(img))
if faces:
for face in faces:
bbox =face.bbox.astype(int)
bbox = face.bbox.astype(int)
mask = imgutils.create_mask(img, bbox)
prompt = pp.inpainting_prompt.replace("[gender]", "man" if face["gender"] == 1 else "woman")
negative_prompt = pp.inpainting_negative_prompt.replace("[gender]", "man" if face["gender"] == 1 else "woman")
prompt = pp.inpainting_prompt.replace(
"[gender]", "man" if face["gender"] == 1 else "woman"
)
negative_prompt = pp.inpainting_negative_prompt.replace(
"[gender]", "man" if face["gender"] == 1 else "woman"
)
logger.info("Denoising prompt : %s", prompt)
logger.info("Denoising strenght : %s", pp.inpainting_denoising_strengh)
i2i_kwargs = {"sampler_name" :pp.inpainting_sampler,
"do_not_save_samples":True,
"steps" :pp.inpainting_steps,
"width" : img.width,
"inpainting_fill":1,
"inpaint_full_res":True,
"height" : img.height,
"mask": mask,
"prompt" : prompt,
"negative_prompt" :negative_prompt,
"denoising_strength" :pp.inpainting_denoising_strengh}
logger.info("Denoising strenght : %s", pp.inpainting_denoising_strengh)
i2i_kwargs = {
"sampler_name": pp.inpainting_sampler,
"do_not_save_samples": True,
"steps": pp.inpainting_steps,
"width": img.width,
"inpainting_fill": 1,
"inpaint_full_res": True,
"height": img.height,
"mask": mask,
"prompt": prompt,
"negative_prompt": negative_prompt,
"denoising_strength": pp.inpainting_denoising_strengh,
}
current_model_checkpoint = shared.opts.sd_model_checkpoint
if pp.inpainting_model and pp.inpainting_model != "Current" :
if pp.inpainting_model and pp.inpainting_model != "Current":
# Change checkpoint
shared.opts.sd_model_checkpoint = pp.inpainting_model
sd_models.select_checkpoint
sd_models.load_model()
i2i_p = StableDiffusionProcessingImg2Img([img], **i2i_kwargs)
i2i_processed = processing.process_images(i2i_p)
if pp.inpainting_model and pp.inpainting_model != "Current" :
if pp.inpainting_model and pp.inpainting_model != "Current":
# Restore checkpoint
shared.opts.sd_model_checkpoint = current_model_checkpoint
sd_models.select_checkpoint
sd_models.load_model()
images = i2i_processed.images
if len(images) > 0 :
if len(images) > 0:
img = images[0]
return img
except Exception as e :
except Exception as e:
logger.error("Failed to apply img2img to face : %s", e)
import traceback
traceback.print_exc()
raise e
scripts/faceswaplab_postprocessing/postprocessing.py
+12 -9
View File
@@ -1,27 +1,30 @@
from modules.face_restoration import FaceRestoration
from scripts.faceswaplab_utils.faceswaplab_logging import logger
from PIL import Image
from scripts.faceswaplab_postprocessing.postprocessing_options import PostProcessingOptions, InpaintingWhen
from scripts.faceswaplab_postprocessing.postprocessing_options import (
PostProcessingOptions,
InpaintingWhen,
)
from scripts.faceswaplab_postprocessing.i2i_pp import img2img_diffusion
from scripts.faceswaplab_postprocessing.upscaling import upscale_img, restore_face
def enhance_image(image: Image.Image, pp_options: PostProcessingOptions) -> Image.Image:
result_image = image
try :
if pp_options.inpainting_when == InpaintingWhen.BEFORE_UPSCALING.value :
try:
if pp_options.inpainting_when == InpaintingWhen.BEFORE_UPSCALING.value:
result_image = img2img_diffusion(image, pp_options)
result_image = upscale_img(result_image, pp_options)
if pp_options.inpainting_when == InpaintingWhen.BEFORE_RESTORE_FACE.value :
result_image = img2img_diffusion(image,pp_options)
if pp_options.inpainting_when == InpaintingWhen.BEFORE_RESTORE_FACE.value:
result_image = img2img_diffusion(image, pp_options)
result_image = restore_face(result_image, pp_options)
if pp_options.inpainting_when == InpaintingWhen.AFTER_ALL.value :
result_image = img2img_diffusion(image,pp_options)
if pp_options.inpainting_when == InpaintingWhen.AFTER_ALL.value:
result_image = img2img_diffusion(image, pp_options)
except Exception as e:
logger.error("Failed to upscale %s", e)
return result_image
return result_image
scripts/faceswaplab_postprocessing/postprocessing_options.py
+12 -10
View File
@@ -4,12 +4,14 @@ from dataclasses import dataclass
from modules import shared
from enum import Enum
class InpaintingWhen(Enum):
NEVER = "Never"
BEFORE_UPSCALING = "Before Upscaling/all"
BEFORE_RESTORE_FACE = "After Upscaling/Before Restore Face"
AFTER_ALL = "After All"
@dataclass
class PostProcessingOptions:
face_restorer_name: str = ""
@@ -19,15 +21,15 @@ class PostProcessingOptions:
upscaler_name: str = ""
scale: int = 1
upscale_visibility: float = 0.5
inpainting_denoising_strengh : float = 0
inpainting_prompt : str = ""
inpainting_negative_prompt : str = ""
inpainting_steps : int = 20
inpainting_sampler : str = "Euler"
inpainting_when : InpaintingWhen = InpaintingWhen.BEFORE_UPSCALING
inpainting_model : str = "Current"
inpainting_denoising_strengh: float = 0
inpainting_prompt: str = ""
inpainting_negative_prompt: str = ""
inpainting_steps: int = 20
inpainting_sampler: str = "Euler"
inpainting_when: InpaintingWhen = InpaintingWhen.BEFORE_UPSCALING
inpainting_model: str = "Current"
@property
def upscaler(self) -> UpscalerData:
for upscaler in shared.sd_upscalers:
@@ -40,4 +42,4 @@ class PostProcessingOptions:
for face_restorer in shared.face_restorers:
if face_restorer.name() == self.face_restorer_name:
return face_restorer
return None
return None
scripts/faceswaplab_postprocessing/upscaling.py
+14 -9
View File
@@ -1,11 +1,14 @@
from scripts.faceswaplab_postprocessing.postprocessing_options import PostProcessingOptions, InpaintingWhen
from scripts.faceswaplab_postprocessing.postprocessing_options import (
PostProcessingOptions,
InpaintingWhen,
)
from scripts.faceswaplab_utils.faceswaplab_logging import logger
from PIL import Image
import numpy as np
from modules import shared, processing, codeformer_model
def upscale_img(image : Image.Image, pp_options :PostProcessingOptions) -> Image.Image :
def upscale_img(image: Image.Image, pp_options: PostProcessingOptions) -> Image.Image:
if pp_options.upscaler is not None and pp_options.upscaler.name != "None":
original_image = image.copy()
logger.info(
@@ -23,15 +26,17 @@ def upscale_img(image : Image.Image, pp_options :PostProcessingOptions) -> Image
return result_image
return image
def restore_face(image : Image.Image, pp_options : PostProcessingOptions) -> Image.Image :
def restore_face(image: Image.Image, pp_options: PostProcessingOptions) -> Image.Image:
if pp_options.face_restorer is not None:
original_image = image.copy()
logger.info("Restore face with %s", pp_options.face_restorer.name())
numpy_image = np.array(image)
if pp_options.face_restorer_name == "CodeFormer" :
numpy_image = codeformer_model.codeformer.restore(numpy_image, w=pp_options.codeformer_weight)
else :
if pp_options.face_restorer_name == "CodeFormer":
numpy_image = codeformer_model.codeformer.restore(
numpy_image, w=pp_options.codeformer_weight
)
else:
numpy_image = pp_options.face_restorer.restore(numpy_image)
restored_image = Image.fromarray(numpy_image)
@@ -39,4 +44,4 @@ def restore_face(image : Image.Image, pp_options : PostProcessingOptions) -> Ima
original_image, restored_image, pp_options.restorer_visibility
)
return result_image
return image
return image