CalvinBackup/sd-webui-faceswaplab
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wip, add nsfw option due to perf, still some mypy warnings

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This commit is contained in:
Tran Xen
2023-08-16 01:11:02 +02:00
parent f9fc0bbff1
commit afcfc7d255
20 changed files with 123 additions and 89 deletions
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scripts/faceswaplab.py
+3 -2
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@@ -1,4 +1,5 @@
from scripts.configure import check_configuration
from scripts.faceswaplab_utils.sd_utils import get_sd_option
check_configuration()
@@ -76,7 +77,7 @@ class FaceSwapScript(scripts.Script):
@property
def units_count(self) -> int:
return opts.data.get("faceswaplab_units_count", 3)
return get_sd_option("faceswaplab_units_count", 3)
@property
def enabled(self) -> bool:
@@ -85,7 +86,7 @@ class FaceSwapScript(scripts.Script):
@property
def keep_original_images(self) -> bool:
return opts.data.get("faceswaplab_keep_original", False)
return get_sd_option("faceswaplab_keep_original", False)
@property
def swap_in_generated_units(self) -> List[FaceSwapUnitSettings]:
scripts/faceswaplab_api/faceswaplab_api.py
+1 -1
View File
@@ -18,7 +18,7 @@ from scripts.faceswaplab_postprocessing.postprocessing_options import (
PostProcessingOptions,
)
from client_api import api_utils
from scripts.faceswaplab_utils.face_checkpoints_utils import (
from scripts.faceswaplab_swapping.face_checkpoints import (
build_face_checkpoint_and_save,
)
scripts/faceswaplab_globals.py
-3
View File
@@ -1,6 +1,5 @@
import os
from modules import scripts
from modules.shared import opts
# Defining the absolute path for the 'faceswaplab' directory inside 'models' directory
MODELS_DIR = os.path.abspath(os.path.join("models", "faceswaplab"))
@@ -21,7 +20,5 @@ VERSION_FLAG: str = "v1.2.2"
# Defining the path for 'sd-webui-faceswaplab' inside the 'extensions' directory
EXTENSION_PATH = os.path.join("extensions", "sd-webui-faceswaplab")
# Defining the NSFW score threshold. Any image part with a score above this value will be treated as NSFW (Not Safe For Work)
NSFW_SCORE_THRESHOLD: float = opts.data.get("faceswaplab_nsfw_threshold", 0.7) # type: ignore
# Defining the expected SHA1 hash value for 'INSWAPPER'
EXPECTED_INSWAPPER_SHA1 = "17a64851eaefd55ea597ee41e5c18409754244c5"
scripts/faceswaplab_inpainting/faceswaplab_inpainting.py
+3 -3
View File
@@ -1,5 +1,5 @@
from dataclasses import dataclass
from typing import List
from typing import List, Optional
import gradio as gr
from client_api import api_utils
@@ -15,10 +15,10 @@ class InpaintingOptions:
@staticmethod
def from_gradio(components: List[gr.components.Component]) -> "InpaintingOptions":
return InpaintingOptions(*components)
return InpaintingOptions(*components) # type: ignore
@staticmethod
def from_api_dto(dto: api_utils.InpaintingOptions) -> "InpaintingOptions":
def from_api_dto(dto: Optional[api_utils.InpaintingOptions]) -> "InpaintingOptions":
"""
Converts a InpaintingOptions object from an API DTO (Data Transfer Object).
scripts/faceswaplab_postprocessing/postprocessing_options.py
+4 -3
View File
@@ -1,3 +1,4 @@
from typing import Optional
from modules.face_restoration import FaceRestoration
from modules.upscaler import UpscalerData
from dataclasses import dataclass
@@ -27,17 +28,17 @@ class PostProcessingOptions:
inpainting_when: InpaintingWhen = InpaintingWhen.BEFORE_UPSCALING
# (Don't use optional for this or gradio parsing will fail) :
inpainting_options: InpaintingOptions = None
inpainting_options: InpaintingOptions = None # type: ignore
@property
def upscaler(self) -> UpscalerData:
def upscaler(self) -> Optional[UpscalerData]:
for upscaler in shared.sd_upscalers:
if upscaler.name == self.upscaler_name:
return upscaler
return None
@property
def face_restorer(self) -> FaceRestoration:
def face_restorer(self) -> Optional[FaceRestoration]:
for face_restorer in shared.face_restorers:
if face_restorer.name() == self.face_restorer_name:
return face_restorer
scripts/faceswaplab_postprocessing/upscaling.py
+1 -1
View File
@@ -17,7 +17,7 @@ def upscale_img(image: PILImage, pp_options: PostProcessingOptions) -> PILImage:
pp_options.scale,
)
result_image = pp_options.upscaler.scaler.upscale(
image, pp_options.scale, pp_options.upscaler.data_path
image, pp_options.scale, pp_options.upscaler.data_path # type: ignore
)
# FIXME : Could be better (managing images whose dimensions are not multiples of 16)
scripts/faceswaplab_settings/faceswaplab_settings.py
+10
View File
@@ -46,6 +46,16 @@ def on_ui_settings() -> None:
section=section,
),
)
shared.opts.add_option(
"faceswaplab_nsfw_threshold",
shared.OptionInfo(
0.7,
"NSFW score threshold. Any image part with a score above this value will be treated as NSFW (use extension responsibly !)",
gr.Slider,
{"minimum": 0, "maximum": 1, "step": 0.01},
section=section,
),
)
shared.opts.add_option(
"faceswaplab_det_size",
scripts/faceswaplab_utils/face_checkpoints_utils.py → scripts/faceswaplab_swapping/face_checkpoints.py
+1 -2
View File
@@ -63,7 +63,7 @@ def build_face_checkpoint_and_save(
scripts.basedir(), "extensions", "sd-webui-faceswaplab", "references"
)
reference_preview_img: PILImage = None
reference_preview_img: PILImage
if blended_face:
if blended_face["gender"] == 0:
reference_preview_img = Image.open(
@@ -86,7 +86,6 @@ def build_face_checkpoint_and_save(
)
else:
result = swapper.swap_face(
reference_face=blended_face,
target_faces=[target_face],
source_face=blended_face,
target_img=reference_preview_img,
scripts/faceswaplab_swapping/facemask.py
+1 -1
View File
@@ -83,7 +83,7 @@ def generate_face_mask(face_image: np.ndarray, device: torch.device) -> np.ndarr
convert_bgr_to_rgb=True,
use_float32=True,
)
normalize(face_input, (0.5, 0.5, 0.5), (0.5, 0.5, 0.5), inplace=True)
normalize(face_input, (0.5, 0.5, 0.5), (0.5, 0.5, 0.5), inplace=True) # type: ignore
assert isinstance(face_input, torch.Tensor)
face_input = torch.unsqueeze(face_input, 0).to(device)
scripts/faceswaplab_swapping/swapper.py
+17 -17
View File
@@ -26,7 +26,6 @@ from scripts.faceswaplab_utils.imgutils import (
)
from scripts.faceswaplab_utils.faceswaplab_logging import logger, save_img_debug
from scripts import faceswaplab_globals
from modules.shared import opts
from functools import lru_cache
from scripts.faceswaplab_ui.faceswaplab_unit_settings import FaceSwapUnitSettings
from scripts.faceswaplab_postprocessing.postprocessing import enhance_image
@@ -38,12 +37,13 @@ from scripts.faceswaplab_utils.typing import CV2ImgU8, PILImage, Face
from scripts.faceswaplab_inpainting.i2i_pp import img2img_diffusion
from modules import shared
import onnxruntime
from scripts.faceswaplab_utils.sd_utils import get_sd_option
def use_gpu() -> bool:
return (
getattr(shared.cmd_opts, "faceswaplab_gpu", False)
or opts.data.get("faceswaplab_use_gpu", False)
or get_sd_option("faceswaplab_use_gpu", False)
) and sys.platform != "darwin"
@@ -166,6 +166,7 @@ def batch_process(
if src_images is not None and len(units) > 0:
result_images = []
for src_image in src_images:
path: str = ""
if isinstance(src_image, str):
if save_path:
path = os.path.join(
@@ -182,7 +183,7 @@ def batch_process(
swapped_images = process_images_units(
get_current_swap_model(), images=[(src_image, None)], units=units
)
if len(swapped_images) > 0:
if swapped_images and len(swapped_images) > 0:
current_images += [img for img, _ in swapped_images]
logger.info("%s images generated", len(current_images))
@@ -209,7 +210,7 @@ def extract_faces(
images: List[PILImage],
extract_path: Optional[str],
postprocess_options: PostProcessingOptions,
) -> Optional[List[str]]:
) -> Optional[List[PILImage]]:
"""
Extracts faces from a list of image files.
@@ -232,14 +233,14 @@ def extract_faces(
os.makedirs(extract_path, exist_ok=True)
if images:
result_images = []
result_images: list[PILImage] = []
for img in images:
faces = get_faces(pil_to_cv2(img))
if faces:
face_images = []
for face in faces:
bbox = face.bbox.astype(int)
bbox = face.bbox.astype(int) # type: ignore
x_min, y_min, x_max, y_max = bbox
face_image = img.crop((x_min, y_min, x_max, y_max))
@@ -370,7 +371,7 @@ def getFaceSwapModel(model_path: str) -> upscaled_inswapper.UpscaledINSwapper:
with tqdm(total=1, desc="Loading swap model", unit="model") as pbar:
with capture_stdout() as captured:
model = upscaled_inswapper.UpscaledINSwapper(
insightface.model_zoo.get_model(model_path, providers=providers)
insightface.model_zoo.get_model(model_path, providers=providers) # type: ignore
)
pbar.update(1)
logger.info("%s", pformat(captured.getvalue()))
@@ -402,11 +403,11 @@ def get_faces(
"""
if det_thresh is None:
det_thresh = opts.data.get("faceswaplab_detection_threshold", 0.5)
det_thresh = get_sd_option("faceswaplab_detection_threshold", 0.5)
auto_det_size = opts.data.get("faceswaplab_auto_det_size", True)
auto_det_size = get_sd_option("faceswaplab_auto_det_size", True)
if not auto_det_size:
x = opts.data.get("faceswaplab_det_size", 640)
x = get_sd_option("faceswaplab_det_size", 640)
det_size = (x, x)
face_analyser = getAnalysisModel(det_size, det_thresh)
@@ -433,7 +434,7 @@ def get_faces(
try:
# Sort the detected faces based on their x-coordinate of the bounding box
return sorted(faces, key=lambda x: x.bbox[0])
return sorted(faces, key=lambda x: x.bbox[0]) # type: ignore
except Exception as e:
logger.error("Failed to get faces %s", e)
traceback.print_exc()
@@ -470,7 +471,7 @@ def filter_faces(
filtered_faces = sorted(
all_faces,
reverse=True,
key=lambda x: (x.bbox[2] - x.bbox[0]) * (x.bbox[3] - x.bbox[1]),
key=lambda x: (x.bbox[2] - x.bbox[0]) * (x.bbox[3] - x.bbox[1]), # type: ignore
)
if filtering_options.source_gender is not None:
@@ -566,7 +567,7 @@ def blend_faces(faces: List[Face]) -> Optional[Face]:
ValueError: If the embeddings have different shapes.
"""
embeddings = [face.embedding for face in faces]
embeddings: list[Any] = [face.embedding for face in faces]
if len(embeddings) > 0:
embedding_shape = embeddings[0].shape
@@ -592,7 +593,6 @@ def blend_faces(faces: List[Face]) -> Optional[Face]:
def swap_face(
reference_face: CV2ImgU8,
source_face: Face,
target_img: PILImage,
target_faces: List[Face],
@@ -604,7 +604,6 @@ def swap_face(
Swaps faces in the target image with the source face.
Args:
reference_face (CV2ImgU8): The reference face used for similarity comparison.
source_face (CV2ImgU8): The source face to be swapped.
target_img (PILImage): The target image to swap faces in.
model (str): Path to the face swap model.
@@ -614,7 +613,9 @@ def swap_face(
"""
return_result = ImageResult(target_img, {}, {})
target_img_cv2: CV2ImgU8 = cv2.cvtColor(np.array(target_img), cv2.COLOR_RGB2BGR)
target_img_cv2: CV2ImgU8 = cv2.cvtColor(
np.array(target_img), cv2.COLOR_RGB2BGR
).astype("uint8")
try:
gender = source_face["gender"]
logger.info("Source Gender %s", gender)
@@ -732,7 +733,6 @@ def process_image_unit(
save_img_debug(image, "Before swap")
result: ImageResult = swap_face(
reference_face=reference_face,
source_face=src_face,
target_img=current_image,
target_faces=target_faces,
scripts/faceswaplab_swapping/upcaled_inswapper_options.py
+4 -3
View File
@@ -1,20 +1,21 @@
from dataclasses import *
from typing import Optional
from client_api import api_utils
@dataclass
class InswappperOptions:
face_restorer_name: str = None
face_restorer_name: Optional[str] = None
restorer_visibility: float = 1
codeformer_weight: float = 1
upscaler_name: str = None
upscaler_name: Optional[str] = None
improved_mask: bool = False
color_corrections: bool = False
sharpen: bool = False
erosion_factor: float = 1.0
@staticmethod
def from_api_dto(dto: api_utils.InswappperOptions) -> "InswappperOptions":
def from_api_dto(dto: Optional[api_utils.InswappperOptions]) -> "InswappperOptions":
"""
Converts a InpaintingOptions object from an API DTO (Data Transfer Object).
scripts/faceswaplab_swapping/upscaled_inswapper.py
+15 -8
View File
@@ -1,10 +1,9 @@
from typing import Any, Tuple, Union
from typing import Any, Optional, Tuple, Union
import cv2
import numpy as np
from insightface.model_zoo.inswapper import INSwapper
from insightface.utils import face_align
from modules import processing, shared
from modules.shared import opts
from modules.upscaler import UpscalerData
from scripts.faceswaplab_postprocessing import upscaling
@@ -14,13 +13,14 @@ from scripts.faceswaplab_postprocessing.postprocessing_options import (
from scripts.faceswaplab_swapping.facemask import generate_face_mask
from scripts.faceswaplab_swapping.upcaled_inswapper_options import InswappperOptions
from scripts.faceswaplab_utils.imgutils import cv2_to_pil, pil_to_cv2
from scripts.faceswaplab_utils.sd_utils import get_sd_option
from scripts.faceswaplab_utils.typing import CV2ImgU8, Face
from scripts.faceswaplab_utils.faceswaplab_logging import logger
def get_upscaler() -> UpscalerData:
def get_upscaler() -> Optional[UpscalerData]:
for upscaler in shared.sd_upscalers:
if upscaler.name == opts.data.get(
if upscaler.name == get_sd_option(
"faceswaplab_upscaled_swapper_upscaler", "LDSR"
):
return upscaler
@@ -130,8 +130,14 @@ class UpscaledINSwapper(INSwapper):
self.__dict__.update(inswapper.__dict__)
def upscale_and_restore(
self, img: CV2ImgU8, k: int = 2, inswapper_options: InswappperOptions = None
self,
img: CV2ImgU8,
k: int = 2,
inswapper_options: Optional[InswappperOptions] = None,
) -> CV2ImgU8:
if inswapper_options is None:
return img
pil_img = cv2_to_pil(img)
pp_options = PostProcessingOptions(
upscaler_name=inswapper_options.upscaler_name,
@@ -156,7 +162,7 @@ class UpscaledINSwapper(INSwapper):
target_face: Face,
source_face: Face,
paste_back: bool = True,
options: InswappperOptions = None,
options: Optional[InswappperOptions] = None,
) -> Union[CV2ImgU8, Tuple[CV2ImgU8, Any]]:
aimg, M = face_align.norm_crop2(img, target_face.kps, self.input_size[0])
blob = cv2.dnn.blobFromImage(
@@ -166,9 +172,10 @@ class UpscaledINSwapper(INSwapper):
(self.input_mean, self.input_mean, self.input_mean),
swapRB=True,
)
latent = source_face.normed_embedding.reshape((1, -1))
latent = source_face.normed_embedding.reshape((1, -1)) # type: ignore
latent = np.dot(latent, self.emap)
latent /= np.linalg.norm(latent)
assert self.session is not None
pred = self.session.run(
self.output_names, {self.input_names[0]: blob, self.input_names[1]: latent}
)[0]
@@ -274,7 +281,7 @@ class UpscaledINSwapper(INSwapper):
mask_h = np.max(mask_h_inds) - np.min(mask_h_inds)
mask_w = np.max(mask_w_inds) - np.min(mask_w_inds)
mask_size = int(np.sqrt(mask_h * mask_w))
erosion_factor = options.erosion_factor
erosion_factor = options.erosion_factor if options else 1
k = max(int(mask_size // 10 * erosion_factor), int(10 * erosion_factor))
scripts/faceswaplab_ui/faceswaplab_inpainting_ui.py
+3 -3
View File
@@ -1,7 +1,7 @@
from typing import List
import gradio as gr
from modules.shared import opts
from modules import sd_models, sd_samplers
from scripts.faceswaplab_utils.sd_utils import get_sd_option
def face_inpainting_ui(
@@ -19,14 +19,14 @@ def face_inpainting_ui(
)
inpainting_denoising_prompt = gr.Textbox(
opts.data.get(
get_sd_option(
"faceswaplab_pp_default_inpainting_prompt", "Portrait of a [gender]"
),
elem_id=f"{id_prefix}_pp_inpainting_denoising_prompt",
label="Inpainting prompt use [gender] instead of men or woman",
)
inpainting_denoising_negative_prompt = gr.Textbox(
opts.data.get(
get_sd_option(
"faceswaplab_pp_default_inpainting_negative_prompt", "blurry"
),
elem_id=f"{id_prefix}_pp_inpainting_denoising_neg_prompt",
scripts/faceswaplab_ui/faceswaplab_postprocessing_ui.py
+9 -9
View File
@@ -2,8 +2,8 @@ from typing import List
import gradio as gr
import modules
from modules import shared, sd_models
from modules.shared import opts
from scripts.faceswaplab_postprocessing.postprocessing_options import InpaintingWhen
from scripts.faceswaplab_utils.sd_utils import get_sd_option
def postprocessing_ui() -> List[gr.components.Component]:
@@ -15,7 +15,7 @@ def postprocessing_ui() -> List[gr.components.Component]:
face_restorer_name = gr.Radio(
label="Restore Face",
choices=["None"] + [x.name() for x in shared.face_restorers],
value=lambda: opts.data.get(
value=lambda: get_sd_option(
"faceswaplab_pp_default_face_restorer",
shared.face_restorers[0].name(),
),
@@ -26,7 +26,7 @@ def postprocessing_ui() -> List[gr.components.Component]:
face_restorer_visibility = gr.Slider(
0,
1,
value=lambda: opts.data.get(
value=lambda: get_sd_option(
"faceswaplab_pp_default_face_restorer_visibility", 1
),
step=0.001,
@@ -36,7 +36,7 @@ def postprocessing_ui() -> List[gr.components.Component]:
codeformer_weight = gr.Slider(
0,
1,
value=lambda: opts.data.get(
value=lambda: get_sd_option(
"faceswaplab_pp_default_face_restorer_weight", 1
),
step=0.001,
@@ -45,7 +45,7 @@ def postprocessing_ui() -> List[gr.components.Component]:
)
upscaler_name = gr.Dropdown(
choices=[upscaler.name for upscaler in shared.sd_upscalers],
value=lambda: opts.data.get("faceswaplab_pp_default_upscaler", "None"),
value=lambda: get_sd_option("faceswaplab_pp_default_upscaler", "None"),
label="Upscaler",
elem_id="faceswaplab_pp_upscaler",
)
@@ -60,7 +60,7 @@ def postprocessing_ui() -> List[gr.components.Component]:
upscaler_visibility = gr.Slider(
0,
1,
value=lambda: opts.data.get(
value=lambda: get_sd_option(
"faceswaplab_pp_default_upscaler_visibility", 1
),
step=0.1,
@@ -87,21 +87,21 @@ def postprocessing_ui() -> List[gr.components.Component]:
)
inpainting_denoising_prompt = gr.Textbox(
opts.data.get(
get_sd_option(
"faceswaplab_pp_default_inpainting_prompt", "Portrait of a [gender]"
),
elem_id="faceswaplab_pp_inpainting_denoising_prompt",
label="Inpainting prompt use [gender] instead of men or woman",
)
inpainting_denoising_negative_prompt = gr.Textbox(
opts.data.get(
get_sd_option(
"faceswaplab_pp_default_inpainting_negative_prompt", "blurry"
),
elem_id="faceswaplab_pp_inpainting_denoising_neg_prompt",
label="Inpainting negative prompt use [gender] instead of men or woman",
)
with gr.Row():
samplers_names = [s.name for s in modules.sd_samplers.all_samplers]
samplers_names = [s.name for s in modules.sd_samplers.all_samplers] # type: ignore
inpainting_sampler = gr.Dropdown(
choices=samplers_names,
value=[samplers_names[0]],
scripts/faceswaplab_ui/faceswaplab_tab.py
+23 -19
View File
@@ -1,11 +1,12 @@
import traceback
from pprint import pformat
from typing import *
from scripts.faceswaplab_swapping import face_checkpoints
from scripts.faceswaplab_utils.sd_utils import get_sd_option
from scripts.faceswaplab_utils.typing import *
import gradio as gr
import onnx
import pandas as pd
from modules.shared import opts
from PIL import Image
import scripts.faceswaplab_swapping.swapper as swapper
@@ -15,7 +16,7 @@ from scripts.faceswaplab_postprocessing.postprocessing_options import (
from scripts.faceswaplab_ui.faceswaplab_postprocessing_ui import postprocessing_ui
from scripts.faceswaplab_ui.faceswaplab_unit_settings import FaceSwapUnitSettings
from scripts.faceswaplab_ui.faceswaplab_unit_ui import faceswap_unit_ui
from scripts.faceswaplab_utils import face_checkpoints_utils, imgutils
from scripts.faceswaplab_utils import imgutils
from scripts.faceswaplab_utils.faceswaplab_logging import logger
from scripts.faceswaplab_utils.models_utils import get_swap_models
from scripts.faceswaplab_utils.ui_utils import dataclasses_from_flat_list
@@ -74,7 +75,7 @@ def extract_faces(
[PostProcessingOptions], components
).pop()
images = [
Image.open(file.name) for file in files
Image.open(file.name) for file in files # type: ignore
] # potentially greedy but Image.open is supposed to be lazy
result_images = swapper.extract_faces(
images, extract_path=extract_path, postprocess_options=postprocess_options
@@ -136,7 +137,7 @@ def analyse_faces(image: PILImage, det_threshold: float = 0.5) -> Optional[str]:
def build_face_checkpoint_and_save(
batch_files: gr.File, name: str, overwrite: bool
batch_files: List[gr.File], name: str, overwrite: bool
) -> PILImage:
"""
Builds a face checkpoint using the provided image files, performs face swapping,
@@ -154,16 +155,16 @@ def build_face_checkpoint_and_save(
try:
if not batch_files:
logger.error("No face found")
return None
images = [Image.open(file.name) for file in batch_files]
preview_image = face_checkpoints_utils.build_face_checkpoint_and_save(
return None # type: ignore (Optional not really supported by old gradio)
images = [Image.open(file.name) for file in batch_files] # type: ignore
preview_image = face_checkpoints.build_face_checkpoint_and_save(
images, name, overwrite=overwrite
)
except Exception as e:
logger.error("Failed to build checkpoint %s", e)
traceback.print_exc()
return None
return None # type: ignore
return preview_image
@@ -197,7 +198,7 @@ def explore_onnx_faceswap_model(model_path: str) -> pd.DataFrame:
logger.error("Failed to explore model %s", e)
traceback.print_exc()
return None
return None # type: ignore
return df
@@ -205,7 +206,7 @@ def batch_process(
files: List[gr.File], save_path: str, *components: Tuple[Any, ...]
) -> List[PILImage]:
try:
units_count = opts.data.get("faceswaplab_units_count", 3)
units_count = get_sd_option("faceswaplab_units_count", 3)
classes: List[Any] = dataclasses_from_flat_list(
[FaceSwapUnitSettings] * units_count + [PostProcessingOptions],
@@ -216,13 +217,16 @@ def batch_process(
]
postprocess_options = classes[-1]
images_paths = [file.name for file in files]
images_paths = [file.name for file in files] # type: ignore
return swapper.batch_process(
images_paths,
save_path=save_path,
units=units,
postprocess_options=postprocess_options,
return (
swapper.batch_process(
images_paths,
save_path=save_path,
units=units,
postprocess_options=postprocess_options,
)
or []
)
except Exception as e:
logger.error("Batch Process error : %s", e)
@@ -304,7 +308,7 @@ def tools_ui() -> None:
label="Extracted faces",
show_label=False,
elem_id="faceswaplab_extract_results",
).style(columns=[2], rows=[2])
)
extract_save_path = gr.Textbox(
label="Destination Directory",
value="",
@@ -360,7 +364,7 @@ def tools_ui() -> None:
label="Batch result",
show_label=False,
elem_id="faceswaplab_batch_results",
).style(columns=[2], rows=[2])
)
batch_save_path = gr.Textbox(
label="Destination Directory",
value="outputs/faceswap/",
@@ -370,7 +374,7 @@ def tools_ui() -> None:
"Process & Save", elem_id="faceswaplab_extract_btn"
)
unit_components = []
for i in range(1, opts.data.get("faceswaplab_units_count", 3) + 1):
for i in range(1, get_sd_option("faceswaplab_units_count", 3) + 1):
unit_components += faceswap_unit_ui(False, i, id_prefix="faceswaplab_tab")
upscale_options = postprocessing_ui()
scripts/faceswaplab_ui/faceswaplab_unit_settings.py
+3 -3
View File
@@ -9,7 +9,7 @@ from PIL import Image
from scripts.faceswaplab_swapping.upcaled_inswapper_options import InswappperOptions
from scripts.faceswaplab_utils.imgutils import pil_to_cv2
from scripts.faceswaplab_utils.faceswaplab_logging import logger
from scripts.faceswaplab_utils import face_checkpoints_utils
from scripts.faceswaplab_swapping import face_checkpoints
from scripts.faceswaplab_inpainting.faceswaplab_inpainting import InpaintingOptions
from client_api import api_utils
@@ -124,7 +124,7 @@ class FaceSwapUnitSettings:
if self.source_face and self.source_face != "None":
try:
logger.info(f"loading face {self.source_face}")
face = face_checkpoints_utils.load_face(self.source_face)
face = face_checkpoints.load_face(self.source_face)
self._reference_face = face
except Exception as e:
logger.error("Failed to load checkpoint : %s", e)
@@ -169,7 +169,7 @@ class FaceSwapUnitSettings:
if isinstance(file, Image.Image):
img = file
else:
img = Image.open(file.name)
img = Image.open(file.name) # type: ignore
face = swapper.get_or_default(
swapper.get_faces(pil_to_cv2(img)), 0, None
scripts/faceswaplab_ui/faceswaplab_unit_ui.py
+10 -10
View File
@@ -1,9 +1,9 @@
from typing import List
from scripts.faceswaplab_ui.faceswaplab_inpainting_ui import face_inpainting_ui
from scripts.faceswaplab_utils.face_checkpoints_utils import get_face_checkpoints
from scripts.faceswaplab_swapping.face_checkpoints import get_face_checkpoints
import gradio as gr
from modules.shared import opts
from modules import shared
from scripts.faceswaplab_utils.sd_utils import get_sd_option
def faceswap_unit_advanced_options(
@@ -17,7 +17,7 @@ def faceswap_unit_advanced_options(
face_restorer_name = gr.Radio(
label="Restore Face",
choices=["None"] + [x.name() for x in shared.face_restorers],
value=lambda: opts.data.get(
value=lambda: get_sd_option(
"faceswaplab_default_upscaled_swapper_face_restorer",
"None",
),
@@ -28,7 +28,7 @@ def faceswap_unit_advanced_options(
face_restorer_visibility = gr.Slider(
0,
1,
value=lambda: opts.data.get(
value=lambda: get_sd_option(
"faceswaplab_default_upscaled_swapper_face_restorer_visibility",
1.0,
),
@@ -39,7 +39,7 @@ def faceswap_unit_advanced_options(
codeformer_weight = gr.Slider(
0,
1,
value=lambda: opts.data.get(
value=lambda: get_sd_option(
"faceswaplab_default_upscaled_swapper_face_restorer_weight", 1.0
),
step=0.001,
@@ -48,7 +48,7 @@ def faceswap_unit_advanced_options(
)
upscaler_name = gr.Dropdown(
choices=[upscaler.name for upscaler in shared.sd_upscalers],
value=lambda: opts.data.get(
value=lambda: get_sd_option(
"faceswaplab_default_upscaled_swapper_upscaler", ""
),
label="Upscaler",
@@ -56,7 +56,7 @@ def faceswap_unit_advanced_options(
)
improved_mask = gr.Checkbox(
lambda: opts.data.get(
lambda: get_sd_option(
"faceswaplab_default_upscaled_swapper_improved_mask", False
),
interactive=True,
@@ -64,7 +64,7 @@ def faceswap_unit_advanced_options(
elem_id=f"{id_prefix}_face{unit_num}_improved_mask",
)
color_corrections = gr.Checkbox(
lambda: opts.data.get(
lambda: get_sd_option(
"faceswaplab_default_upscaled_swapper_fixcolor", False
),
interactive=True,
@@ -72,7 +72,7 @@ def faceswap_unit_advanced_options(
elem_id=f"{id_prefix}_face{unit_num}_color_corrections",
)
sharpen_face = gr.Checkbox(
lambda: opts.data.get(
lambda: get_sd_option(
"faceswaplab_default_upscaled_swapper_sharpen", False
),
interactive=True,
@@ -82,7 +82,7 @@ def faceswap_unit_advanced_options(
erosion_factor = gr.Slider(
0.0,
10.0,
lambda: opts.data.get("faceswaplab_default_upscaled_swapper_erosion", 1.0),
lambda: get_sd_option("faceswaplab_default_upscaled_swapper_erosion", 1.0),
step=0.01,
label="Upscaled swapper mask erosion factor, 1 = default behaviour.",
elem_id=f"{id_prefix}_face{unit_num}_erosion_factor",
scripts/faceswaplab_utils/imgutils.py
+7 -1
View File
@@ -6,10 +6,10 @@ import numpy as np
from math import isqrt, ceil
import torch
from ifnude import detect
from scripts.faceswaplab_globals import NSFW_SCORE_THRESHOLD
from modules import processing
import base64
from collections import Counter
from scripts.faceswaplab_utils.sd_utils import get_sd_option
from scripts.faceswaplab_utils.typing import BoxCoords, CV2ImgU8, PILImage
from scripts.faceswaplab_utils.faceswaplab_logging import logger
@@ -25,6 +25,12 @@ def check_against_nsfw(img: PILImage) -> bool:
bool: True if any part of the image is considered NSFW, False otherwise.
"""
NSFW_SCORE_THRESHOLD = get_sd_option("faceswaplab_nsfw_threshold", 0.7)
# For testing purpose :
if NSFW_SCORE_THRESHOLD >= 1:
return False
shapes: List[bool] = []
chunks: List[Dict[str, Union[int, float]]] = detect(img)
scripts/faceswaplab_utils/models_utils.py
+1
View File
@@ -77,4 +77,5 @@ def get_current_swap_model() -> str:
raise FileNotFoundError(
"No faceswap model found. Please add it to the faceswaplab directory."
)
assert model is not None
return model
scripts/faceswaplab_utils/sd_utils.py
+7
View File
@@ -0,0 +1,7 @@
from typing import Any
from modules.shared import opts
def get_sd_option(name: str, default: Any) -> Any:
assert opts.data is not None
return opts.data.get(name, default)