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UPDATE: Multiple Source Images Support

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Feature Request #143

+VersionUP (0.6.0 alpha1)
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Gourieff 2023-12-06 19:36:40 +07:00
parent 7706d6aa34
commit e62ff09e5c
15 changed files with 859 additions and 660 deletions
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33
README.md
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@ -2,7 +2,7 @@
<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/ReActor_logo_red.png?raw=true" alt="logo" width="180px"/>
![Version](https://img.shields.io/badge/version-0.5.1-brightgreen?style=for-the-badge&labelColor=darkgreen)
![Version](https://img.shields.io/badge/version-0.6.0_alpha1-lightgreen?style=for-the-badge&labelColor=darkgreen)
<a href="https://boosty.to/artgourieff" target="_blank">
<img src="https://lovemet.ru/www/boosty.jpg" width="108" alt="Support Me on Boosty"/>
@ -38,11 +38,20 @@
<a name="latestupdate">
## What's new in the latest update
## What's new in the latest updates
### 0.6.0 <sub><sup>ALPHA1
- UI reworked
- You can now load several source images (with reference faces) or set the path to the folder containing faces images
<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/multiple_source_images_demo_01.png?raw=true" alt="0.6.0-whatsnew-01" width="100%"/>
<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/multiple_source_images_demo_02.png?raw=true" alt="0.6.0-whatsnew-02" width="100%"/>
### 0.5.1
- You can now save face models as "safetensors" files (stored in `<sd-web-ui-folder>\models\reactor\faces`) and load them into ReActor, keeping super lightweight face models of the faces you use;
- You can save face models as "safetensors" files (stored in `<sd-web-ui-folder>\models\reactor\faces`) and load them into ReActor, keeping super lightweight face models of the faces you use;
- "Face Mask Correction" option - if you encounter some pixelation around face contours, this option will be useful;
<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/face_model_demo_01.jpg?raw=true" alt="0.5.0-whatsnew-01" width="100%"/>
@ -59,8 +68,8 @@
- OR only **VS C++ Build Tools** (if you don't need the whole Visual Studio) and select "Desktop Development with C++" under "Workloads -> Desktop & Mobile":
https://visualstudio.microsoft.com/visual-cpp-build-tools/
- OR if you don't want to install VS or VS C++ BT - follow [this steps (sec. VIII)](#insightfacebuild)
2. In web-ui, go to the "Extensions" tab and use this URL `https://github.com/Gourieff/sd-webui-reactor` in the "Install from URL" tab and click "Install"
3. Please, wait for several minutes until the installation process will be finished
2. In web-ui, go to the "Extensions" tab, load "Available" extensions and type "ReActor" in the search field or use this URL `https://github.com/Gourieff/sd-webui-reactor` in the "Install from URL" tab - and click "Install"
3. Please, wait for several minutes until the installation process will be finished (be patient, don't interrupt the process)
4. Check the last message in your SD-WebUI Console:
* If you see the message "--- PLEASE, RESTART the Server! ---" - so, do it, stop the Server (CTRL+C or CMD+C) and start it again - or just go to the "Installed" tab, click "Apply and restart UI"
* If you see the message "Done!", just reload the UI
@ -73,7 +82,7 @@
3. Go to (Windows)`automatic\venv\Scripts` or (MacOS/Linux)`automatic/venv/bin`, run Terminal or Console (cmd) for that folder and type `activate`
4. Run `pip install insightface==0.7.3`
5. Run SD.Next, go to the "Extensions" tab and use this URL `https://github.com/Gourieff/sd-webui-reactor` in the "Install from URL" tab and click "Install"
6. Please, wait for several minutes until the installation process will be finished
6. Please, wait for several minutes until the installation process will be finished (be patient, don't interrupt the process)
7. Check the last message in your SD.Next Console:
* If you see the message "--- PLEASE, RESTART the Server! ---" - stop the Server (CTRL+C or CMD+C) or just close your console
8. Go to the `automatic\extensions\sd-webui-reactor` directory - if you see there `models\insightface` folder with the file `inswapper_128.onnx`, just move the file to the `automatic\models\insightface` folder
@ -81,8 +90,8 @@
<a name="colab">If you use [Cagliostro Colab UI](https://github.com/Linaqruf/sd-notebook-collection):
1. In active WebUI, go to the "Extensions" tab and use this URL `https://github.com/Gourieff/sd-webui-reactor` in the "Install from URL" tab and click "Install"
2. Please, wait for several minutes until the installation process will be finished
1. In active WebUI, go to the "Extensions" tab, load "Available" extensions and type "ReActor" in the search field or use this URL `https://github.com/Gourieff/sd-webui-reactor` in the "Install from URL" tab - and click "Install"
2. Please, wait for several minutes until the installation process will be finished (be patient, don't interrupt the process)
3. When you see the message "--- PLEASE, RESTART the Server! ---" (in your Colab Notebook Start UI section "Start Cagliostro Colab UI") - just go to the "Installed" tab and click "Apply and restart UI"
4. Enjoy!
@ -99,7 +108,7 @@
- Ability to set the **Postprocessing order**
- **100% compatibility** with different **SD WebUIs**: Automatic1111, SD.Next, Cagliostro Colab UI
- **Fast performance** even with CPU, ReActor for SD WebUI is absolutely not picky about how powerful your GPU is
- **CUDA** acceleration support from the version 0.5.0
- **CUDA** acceleration support since version 0.5.0
- **[API](/API.md) support**: both SD WebUI built-in and external (via POST/GET requests)
- **ComfyUI [support](https://github.com/Gourieff/comfyui-reactor-node)**
- **Mac M1/M2 [support](https://github.com/Gourieff/sd-webui-reactor/issues/42)**
@ -191,7 +200,7 @@ Please, check the path where "inswapper_128.onnx" model is stored. It must be in
7. Then one-by-one:
- `pip install insightface==0.7.3`
- `pip install onnx`
- `pip install onnxruntime-gpu>=1.16.1`
- `pip install "onnxruntime-gpu>=1.16.1"`
- `pip install opencv-python`
- `pip install tqdm`
8. Type `deactivate`, you can close your Terminal or Console and start your SD WebUI, ReActor should start OK - if not, welcome to the Issues section.
@ -226,7 +235,7 @@ and put it to the `stable-diffusion-webui\models\insightface` replacing existing
4. Then:
- `python -m pip install -U pip`
- `pip uninstall -y onnxruntime onnxruntime-gpu onnxruntime-silicon onnxruntime-extensions`
- `pip install onnxruntime-gpu>=1.16.1`
- `pip install "onnxruntime-gpu>=1.16.1"`
If it didn't help - it seems that you have another extension reinstalling `onnxruntime` when SD WebUI checks requirements. Please see your extensions list. Some extensions can causes reinstalling of `onnxruntime-gpu` to `onnxruntime<1.16.1` every time SD WebUI runs.<br>ORT 1.16.0 has a bug https://github.com/microsoft/onnxruntime/issues/17631 - don't install it!
@ -239,7 +248,7 @@ If it didn't help - it seems that you have another extension reinstalling `onnxr
5. Then:
- `python -m pip install -U pip`
- `pip uninstall protobuf`
- `pip install protobuf>=3.20.3`
- `pip install "protobuf>=3.20.3"`
If this method doesn't help - there is some other extension that has a wrong version of protobuf dependence and SD WebUI installs it on a startup requirements check

27
README_RU.md
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@ -2,7 +2,7 @@
<img src="https://github.com/Gourieff/Assets/raw/main/sd-webui-reactor/ReActor_logo_red.png?raw=true" alt="logo" width="180px"/>
![Version](https://img.shields.io/badge/версия-0.5.1-brightgreen?style=for-the-badge&labelColor=darkgreen)
![Version](https://img.shields.io/badge/версия-0.6.0_alpha1-lightgreen?style=for-the-badge&labelColor=darkgreen)
<a href="https://boosty.to/artgourieff" target="_blank">
<img src="https://lovemet.ru/www/boosty.jpg" width="108" alt="Поддержать проект на Boosty"/>
@ -37,7 +37,14 @@
<a name="latestupdate">
## Что нового в последнем обновлении
## Что нового в последних обновлениях
### 0.6.0 <sub><sup>ALPHA1
- UI переработан
- Появилась возможность загружать несколько исходных изображений с лицами или задавать путь к папке, содержащей такие изображения
<img src="https://github.com/Gourieff/Assets/blob/main/sd-webui-reactor/multiple_source_images_demo_01.png?raw=true" alt="0.6.0-whatsnew-01" width="100%"/>
### 0.5.1
@ -60,8 +67,8 @@
- ИЛИ только **VS C++ Build Tools** (если вам не нужен весь пакет Visual Studio), выберите "Desktop Development with C++" в разделе "Workloads -> Desktop & Mobile":
https://visualstudio.microsoft.com/visual-cpp-build-tools/
- ИЛИ если же вы не хотите устанавливать что-либо из вышеуказанного - выполните [следующие шаги (пункт VIII)](#insightfacebuild)
2. Внутри SD Web-UI перейдите во вкладку "Extensions" и вставьте ссылку `https://github.com/Gourieff/sd-webui-reactor` в "Install from URL" и нажмите "Install"
3. Пожалуйста, подождите несколько минут, пока процесс установки полностью не завершится
2. Внутри SD Web-UI перейдите во вкладку "Extensions", загрузите список доступных расширений (вкладка "Available") и введите "ReActor" в строке поиска или же вставьте ссылку `https://github.com/Gourieff/sd-webui-reactor` в "Install from URL" - и нажмите "Install"
3. Пожалуйста, подождите несколько минут, пока процесс установки полностью не завершится (наберитесь терпения, не прерывайте процесс)
4. Проверьте последнее сообщение в консоли SD-WebUI:
* Если вы видите "--- PLEASE, RESTART the Server! ---" - остановите Сервер (CTRL+C или CMD+C) и запустите его заново - ИЛИ же перейдите во вкладку "Installed", нажмите "Apply and restart UI"
* Если вы видите "Done!", просто перезагрузите UI, нажав на "Reload UI"
@ -74,7 +81,7 @@
3. Перейдите в (Windows)`automatic\venv\Scripts` или (MacOS/Linux)`automatic/venv/bin`, запустите Терминал или Консоль (cmd) для данной папки и выполните `activate`
4. Выполните `pip install insightface==0.7.3`
5. Запустите SD.Next, перейдите во вкладку "Extensions", вставьте эту ссылку `https://github.com/Gourieff/sd-webui-reactor` в "Install from URL" и нажмите "Install"
6. Пожалуйста, подождите несколько минут, пока процесс установки полностью не завершится
6. Пожалуйста, подождите несколько минут, пока процесс установки полностью не завершится (наберитесь терпения, не прерывайте процесс)
7. Проверьте последнее сообщение в консоли SD.Next:
* Если вы видите "--- PLEASE, RESTART the Server! ---" - остановите Сервер (CTRL+C или CMD+C) или просто закройте консоль
8. Перейдите в директорию `automatic\extensions\sd-webui-reactor` - если вы видите там папку `models\insightface` с файлом `inswapper_128.onnx` внутри, переместите его в папку `automatic\models\insightface`
@ -82,8 +89,8 @@
<a name="colab">Если вы используете [Cagliostro Colab UI](https://github.com/Linaqruf/sd-notebook-collection):
1. В активном WebUI, перейдите во вкладку "Extensions", вставьте ссылку `https://github.com/Gourieff/sd-webui-reactor` в "Install from URL" и нажмите "Install"
2. Пожалуйста, подождите некоторое время, пока процесс установки полностью не завершится
1. В активном WebUI перейдите во вкладку "Extensions", загрузите список доступных расширений (вкладка "Available") и введите "ReActor" в строке поиска или же вставьте ссылку `https://github.com/Gourieff/sd-webui-reactor` в "Install from URL" - и нажмите "Install"
2. Пожалуйста, подождите некоторое время, пока процесс установки полностью не завершится (наберитесь терпения, не прерывайте процесс)
3. Когда вы увидите сообщение "--- PLEASE, RESTART the Server! ---" (в секции "Start UI" вашего ноутбука "Start Cagliostro Colab UI") - перейдите во вкладку "Installed" и нажмите "Apply and restart UI"
4. Готово!
@ -198,7 +205,7 @@ Inpainting также работает, но замена лица происх
7. Далее:
- `pip install insightface==0.7.3`
- `pip install onnx`
- `pip install onnxruntime-gpu>=1.16.1`
- `pip install "onnxruntime-gpu>=1.16.1"`
- `pip install opencv-python`
- `pip install tqdm`
8. Выполните `deactivate`, закройте Терминал или Консоль и запустите SD WebUI, ReActor должен запуститься без к-л проблем - если же нет, добро пожаловать в раздел "Issues".
@ -233,7 +240,7 @@ Inpainting также работает, но замена лица происх
4. Затем:
- `python -m pip install -U pip`
- `pip uninstall -y onnxruntime onnxruntime-gpu onnxruntime-silicon onnxruntime-extensions`
- `pip install onnxruntime-gpu>=1.16.1`
- `pip install "onnxruntime-gpu>=1.16.1"`
Если это не помогло - значит какое-то другое расширение переустанавливает `onnxruntime` всякий раз, когда SD WebUI проверяет требования пакетов. Внимательно посмотрите список активных расширений. Некоторые расширения могут вызывать переустановку `onnxruntime-gpu` на версию `onnxruntime<1.16.1` при каждом запуске SD WebUI.<br>ORT 1.16.0 выкатили с ошибкой https://github.com/microsoft/onnxruntime/issues/17631 - не устанавливайте её!
@ -246,7 +253,7 @@ Inpainting также работает, но замена лица происх
5. Затем:
- `python -m pip install -U pip`
- `pip uninstall protobuf`
- `pip install protobuf>=3.20.3`
- `pip install "protobuf>=3.20.3"`
Если это не помгло - значит, есть к-л другое расширение, которое использует неподходящую версию пакета protobuf, и SD WebUI устанавливает эту версию при каждом запуске.

5
example/api_example.py
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@ -44,8 +44,9 @@ args=[
False, #19 Target Image Hash Check, False - by default
"CUDA", #20 CPU or CUDA (if you have it), CPU - by default
True, #21 Face Mask Correction
1, #22 Select Source, 0 - Image, 1 - Face Model
"elena.safetensors", #23 Filename of the face model (from "models/reactor/faces"), e.g. elena.safetensors
1, #22 Select Source, 0 - Image, 1 - Face Model, 2 - Source Folder
"elena.safetensors", #23 Filename of the face model (from "models/reactor/faces"), e.g. elena.safetensors, don't forger to set #22 to 1
"C:\PATH_TO_FACES_IMAGES", #24 The path to the folder containing source faces images, don't forger to set #22 to 2
]
# The args for ReActor can be found by

0
modules/reactor_mask.py → reactor_modules/reactor_mask.py
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4
reactor_ui/__init__.py Normal file
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@ -0,0 +1,4 @@
import reactor_ui.reactor_upscale_ui as ui_upscale
import reactor_ui.reactor_tools_ui as ui_tools
import reactor_ui.reactor_settings_ui as ui_settings
import reactor_ui.reactor_main_ui as ui_main

182
reactor_ui/reactor_main_ui.py Normal file
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@ -0,0 +1,182 @@
import gradio as gr
from scripts.reactor_helpers import (
get_model_names,
get_facemodels
)
from scripts.reactor_swapper import (
clear_faces_list,
)
from modules import shared
SAVE_ORIGINAL: bool = False
def update_fm_list(selected: str):
return gr.Dropdown.update(
value=selected, choices=get_model_names(get_facemodels)
)
# TAB MAIN
def show(is_img2img: bool, show_br: bool = True, **msgs):
def on_select_source(selected: bool, evt: gr.SelectData):
global SAVE_ORIGINAL
if evt.index == 2:
if SAVE_ORIGINAL != selected:
SAVE_ORIGINAL = selected
return {
control_col_1: gr.Column.update(visible=False),
control_col_2: gr.Column.update(visible=False),
control_col_3: gr.Column.update(visible=True),
save_original: gr.Checkbox.update(value=False,visible=False),
imgs_hash_clear: gr.Button.update(visible=True)
}
if evt.index == 0:
return {
control_col_1: gr.Column.update(visible=True),
control_col_2: gr.Column.update(visible=False),
control_col_3: gr.Column.update(visible=False),
save_original: gr.Checkbox.update(value=SAVE_ORIGINAL,visible=show_br),
imgs_hash_clear: gr.Button.update(visible=False)
}
if evt.index == 1:
return {
control_col_1: gr.Column.update(visible=False),
control_col_2: gr.Column.update(visible=True),
control_col_3: gr.Column.update(visible=False),
save_original: gr.Checkbox.update(value=SAVE_ORIGINAL,visible=show_br),
imgs_hash_clear: gr.Button.update(visible=False)
}
progressbar_area = gr.Markdown("")
with gr.Tab("Main"):
with gr.Column():
with gr.Row():
select_source = gr.Radio(
["Image(s)","Face Model","Folder"],
value="Image(s)",
label="Select Source",
type="index",
scale=1,
)
with gr.Column(visible=False) as control_col_2:
with gr.Row():
face_models = get_model_names(get_facemodels)
face_model = gr.Dropdown(
choices=face_models,
label="Choose Face Model",
value="None",
scale=1,
)
fm_update = gr.Button(
value="🔄",
variant="tool",
)
fm_update.click(
update_fm_list,
inputs=[face_model],
outputs=[face_model],
)
imgs_hash_clear = gr.Button(
value="Clear Source Images Hash",
scale=1,
visible=False,
)
imgs_hash_clear.click(clear_faces_list,None,[progressbar_area])
gr.Markdown("<br>", visible=show_br)
with gr.Column(visible=True) as control_col_1:
gr.Markdown("<center>🔽🔽🔽 Single Image has priority when both Areas in use 🔽🔽🔽</center>")
with gr.Row():
img = gr.Image(
type="pil",
label="Single Source Image",
)
imgs = gr.Files(
label=f"Multiple Source Images{msgs['extra_multiple_source']}",
file_types=["image"],
)
with gr.Column(visible=False) as control_col_3:
gr.Markdown("<span style='display:block;text-align:right;padding-right:3px;margin: -15px 0;font-size:1.1em'><sup>Clear Hash if you see the previous face was swapped instead of the new one</sup></span>")
source_folder = gr.Textbox(
value="",
placeholder="Paste here the path to the folder containing source faces images",
label=f"Source Folder{msgs['extra_multiple_source']}",
)
setattr(face_model, "do_not_save_to_config", True)
if is_img2img:
save_original = gr.Checkbox(
False,
label="Save Original (Swap in generated only)",
info="Save the original image(s) made before swapping (it always saves Original when you use Multiple Images or Folder)"
)
else:
save_original = gr.Checkbox(
False,
label="Save Original",
info="Save the original image(s) made before swapping (it always saves Original when you use Multiple Images or Folder)",
visible=show_br
)
# imgs.upload(on_files_upload_uncheck_so,[save_original],[save_original],show_progress=False)
# imgs.clear(on_files_clear,None,[save_original],show_progress=False)
imgs.clear(clear_faces_list,None,None,show_progress=False)
mask_face = gr.Checkbox(
False,
label="Face Mask Correction",
info="Apply this option if you see some pixelation around face contours"
)
gr.Markdown("<br>", visible=show_br)
gr.Markdown("Source Image (above):")
with gr.Row():
source_faces_index = gr.Textbox(
value="0",
placeholder="Which face(s) to use as Source (comma separated)",
label="Comma separated face number(s); Example: 0,2,1",
)
gender_source = gr.Radio(
["No", "Female Only", "Male Only"],
value="No",
label="Gender Detection (Source)",
type="index",
)
gr.Markdown("<br>", visible=show_br)
gr.Markdown("Target Image (result):")
with gr.Row():
faces_index = gr.Textbox(
value="0",
placeholder="Which face(s) to Swap into Target (comma separated)",
label="Comma separated face number(s); Example: 1,0,2",
)
gender_target = gr.Radio(
["No", "Female Only", "Male Only"],
value="No",
label="Gender Detection (Target)",
type="index",
)
gr.Markdown("<br>", visible=show_br)
with gr.Row():
face_restorer_name = gr.Radio(
label="Restore Face",
choices=["None"] + [x.name() for x in shared.face_restorers],
value=shared.face_restorers[0].name(),
type="value",
)
with gr.Column():
face_restorer_visibility = gr.Slider(
0, 1, 1, step=0.1, label="Restore Face Visibility"
)
codeformer_weight = gr.Slider(
0, 1, 0.5, step=0.1, label="CodeFormer Weight", info="0 = maximum effect, 1 = minimum effect"
)
gr.Markdown("<br>", visible=show_br)
swap_in_source = gr.Checkbox(
False,
label="Swap in source image",
visible=is_img2img,
)
swap_in_generated = gr.Checkbox(
True,
label="Swap in generated image",
visible=is_img2img,
)
select_source.select(on_select_source,[save_original],[control_col_1,control_col_2,control_col_3,save_original,imgs_hash_clear],show_progress=False)
return img, imgs, select_source, face_model, source_folder, save_original, mask_face, source_faces_index, gender_source, faces_index, gender_target, face_restorer_name, face_restorer_visibility, codeformer_weight, swap_in_source, swap_in_generated

77
reactor_ui/reactor_settings_ui.py Normal file
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@ -0,0 +1,77 @@
import gradio as gr
from scripts.reactor_logger import logger
from scripts.reactor_helpers import get_models, set_Device
from scripts.reactor_globals import DEVICE, DEVICE_LIST
try:
import torch.cuda as cuda
EP_is_visible = True if cuda.is_available() else False
except:
EP_is_visible = False
def update_models_list(selected: str):
return gr.Dropdown.update(
value=selected, choices=get_models()
)
def show(hash_check_block: bool = True):
# TAB SETTINGS
with gr.Tab("Settings"):
models = get_models()
with gr.Row(visible=EP_is_visible):
device = gr.Radio(
label="Execution Provider",
choices=DEVICE_LIST,
value=DEVICE,
type="value",
info="If you already run 'Generate' - RESTART is required to apply. Click 'Save', (A1111) Extensions Tab -> 'Apply and restart UI' or (SD.Next) close the Server and start it again",
scale=2,
)
save_device_btn = gr.Button("Save", scale=0)
save = gr.Markdown("", visible=EP_is_visible)
setattr(device, "do_not_save_to_config", True)
save_device_btn.click(
set_Device,
inputs=[device],
outputs=[save],
)
with gr.Row():
if len(models) == 0:
logger.warning(
"You should at least have one model in models directory, please read the doc here: https://github.com/Gourieff/sd-webui-reactor/"
)
model = gr.Dropdown(
choices=models,
label="Model not found, please download one and refresh the list"
)
else:
model = gr.Dropdown(
choices=models, label="Model", value=models[0]
)
models_update = gr.Button(
value="🔄",
variant="tool",
)
models_update.click(
update_models_list,
inputs=[model],
outputs=[model],
)
console_logging_level = gr.Radio(
["No log", "Minimum", "Default"],
value="Minimum",
label="Console Log Level",
type="index"
)
gr.Markdown("<br>", visible=hash_check_block)
with gr.Row(visible=hash_check_block):
source_hash_check = gr.Checkbox(
True,
label="Source Image Hash Check",
info="Recommended to keep it ON. Processing is faster when Source Image is the same."
)
target_hash_check = gr.Checkbox(
False,
label="Target Image Hash Check",
info="Affects if you use Extras tab or img2img with only 'Swap in source image' on."
)
return model, device, console_logging_level, source_hash_check, target_hash_check

25
reactor_ui/reactor_tools_ui.py Normal file
View File

@ -0,0 +1,25 @@
import gradio as gr
from scripts.reactor_swapper import build_face_model
# TAB TOOLS
def show():
with gr.Tab("Tools"):
with gr.Tab("Face Models"):
gr.Markdown("Load an image containing one person, name it and click 'Build and Save'")
img_fm = gr.Image(
type="pil",
label="Load Image to build Face Model",
)
with gr.Row(equal_height=True):
fm_name = gr.Textbox(
value="",
placeholder="Please type any name (e.g. Elena)",
label="Face Model Name",
)
save_fm_btn = gr.Button("Build and Save")
save_fm = gr.Markdown("You can find saved models in 'models/reactor/faces'")
save_fm_btn.click(
build_face_model,
inputs=[img_fm, fm_name],
outputs=[save_fm],
)

39
reactor_ui/reactor_upscale_ui.py Normal file
View File

@ -0,0 +1,39 @@
import gradio as gr
from modules import shared
def update_upscalers_list(selected: str):
return gr.Dropdown.update(
value=selected, choices=[upscaler.name for upscaler in shared.sd_upscalers]
)
# TAB UPSCALE
def show(show_br: bool = True):
with gr.Tab("Upscale"):
restore_first = gr.Checkbox(
True,
label="1. Restore Face -> 2. Upscale (-Uncheck- if you want vice versa)",
info="Postprocessing Order"
)
with gr.Row():
upscaler_name = gr.Dropdown(
choices=[upscaler.name for upscaler in shared.sd_upscalers],
label="Upscaler",
value="None",
info="Won't scale if you choose -Swap in Source- via img2img, only 1x-postprocessing will affect (texturing, denoising, restyling etc.)"
)
upscalers_update = gr.Button(
value="🔄",
variant="tool",
)
upscalers_update.click(
update_upscalers_list,
inputs=[upscaler_name],
outputs=[upscaler_name],
)
gr.Markdown("<br>", visible=show_br)
with gr.Row():
upscaler_scale = gr.Slider(1, 8, 1, step=0.1, label="Scale by")
upscaler_visibility = gr.Slider(
0, 1, 1, step=0.1, label="Upscaler Visibility (if scale = 1)"
)
return restore_first, upscaler_name, upscaler_scale, upscaler_visibility

7
scripts/reactor_api.py
View File

@ -73,8 +73,9 @@ def reactor_api(_: gr.Blocks, app: FastAPI):
result_file_path: str = Body("",title="(if 'save_to_file = 1') Result file path"),
device: str = Body("CPU",title="CPU or CUDA (if you have it)"),
mask_face: int = Body(0,title="Face Mask Correction, 1 - True, 0 - False"),
select_source: int = Body(0,title="Select Source, 0 - Image, 1 - Face Model"),
face_model: str = Body("None",title="Filename of the face model (from 'models/reactor/faces'), e.g. elena.safetensors")
select_source: int = Body(0,title="Select Source, 0 - Image, 1 - Face Model, 2 - Source Folder"),
face_model: str = Body("None",title="Filename of the face model (from 'models/reactor/faces'), e.g. elena.safetensors"),
source_folder: str = Body("",title="The path to the folder containing source faces images")
):
s_image = api.decode_base64_to_image(source_image)
t_image = api.decode_base64_to_image(target_image)
@ -88,7 +89,7 @@ def reactor_api(_: gr.Blocks, app: FastAPI):
use_model = get_full_model(model)
if use_model is None:
Exception("Model not found")
result = swap_face(s_image, t_image, use_model, sf_index, f_index, up_options, gender_s, gender_t, True, True, device, mask_face, select_source, face_model)
result = swap_face(s_image, t_image, use_model, sf_index, f_index, up_options, gender_s, gender_t, True, True, device, mask_face, select_source, face_model, source_folder, None)
if save_to_file == 1:
if result_file_path == "":
result_file_path = default_file_path()

573
scripts/reactor_faceswap.py
View File

@ -1,11 +1,6 @@
import os, glob
import gradio as gr
from PIL import Image
try:
import torch.cuda as cuda
EP_is_visible = True if cuda.is_available() else False
except:
EP_is_visible = False
from typing import List
@ -19,43 +14,22 @@ from modules.processing import (
)
from modules.face_restoration import FaceRestoration
from modules.images import save_image
try:
from modules.paths_internal import models_path
except:
try:
from modules.paths import models_path
except:
model_path = os.path.abspath("models")
from reactor_ui import ui_main, ui_upscale, ui_tools, ui_settings
from scripts.reactor_logger import logger
from scripts.reactor_swapper import (
EnhancementOptions,
swap_face,
check_process_halt,
reset_messaged,
build_face_model
)
from scripts.reactor_version import version_flag, app_title
from scripts.console_log_patch import apply_logging_patch
from scripts.reactor_helpers import make_grid, get_image_path, set_Device, get_model_names, get_facemodels
from scripts.reactor_globals import DEVICE, DEVICE_LIST
MODELS_PATH = None
def get_models():
global MODELS_PATH
models_path_init = os.path.join(models_path, "insightface/*")
models = glob.glob(models_path_init)
models = [x for x in models if x.endswith(".onnx") or x.endswith(".pth")]
models_names = []
for model in models:
model_path = os.path.split(model)
if MODELS_PATH is None:
MODELS_PATH = model_path[0]
model_name = model_path[1]
models_names.append(model_name)
return models_names
from scripts.reactor_helpers import (
make_grid,
set_Device,
)
from scripts.reactor_globals import SWAPPER_MODELS_PATH #, DEVICE, DEVICE_LIST
class FaceSwapScript(scripts.Script):
@ -68,237 +42,33 @@ class FaceSwapScript(scripts.Script):
def ui(self, is_img2img):
with gr.Accordion(f"{app_title}", open=False):
def update_fm_list(selected: str):
return gr.Dropdown.update(
value=selected, choices=get_model_names(get_facemodels)
)
def update_upscalers_list(selected: str):
return gr.Dropdown.update(
value=selected, choices=[upscaler.name for upscaler in shared.sd_upscalers]
)
def update_models_list(selected: str):
return gr.Dropdown.update(
value=selected, choices=get_models()
)
# def on_files_upload_uncheck_so(selected: bool):
# global SAVE_ORIGINAL
# SAVE_ORIGINAL = selected
# return gr.Checkbox.update(value=False,visible=False)
# def on_files_clear():
# clear_faces_list()
# return gr.Checkbox.update(value=SAVE_ORIGINAL,visible=True)
enable = gr.Checkbox(False, label="Enable", info=f"The Fast and Simple FaceSwap Extension - {version_flag}")
gr.Markdown("<br>")
# TAB MAIN
with gr.Tab("Main"):
with gr.Column():
img = gr.Image(
type="pil",
label="Source Image",
)
# face_model = gr.File(
# file_types=[".safetensors"],
# label="Face Model",
# show_label=True,
# )
enable = gr.Checkbox(False, label="Enable", info=f"The Fast and Simple FaceSwap Extension - {version_flag}")
gr.Markdown("<br>")
with gr.Row():
select_source = gr.Radio(
["Image","Face Model"],
value="Image",
label="Select Source",
type="index",
scale=1,
)
face_models = get_model_names(get_facemodels)
face_model = gr.Dropdown(
choices=face_models,
label="Choose Face Model",
value="None",
scale=2,
)
fm_update = gr.Button(
value="🔄",
variant="tool",
)
fm_update.click(
update_fm_list,
inputs=[face_model],
outputs=[face_model],
)
setattr(face_model, "do_not_save_to_config", True)
save_original = gr.Checkbox(
False,
label="Save Original",
info="Save the original image(s) made before swapping; If you use \"img2img\" - this option will affect with \"Swap in generated\" only"
)
mask_face = gr.Checkbox(
False,
label="Face Mask Correction",
info="Apply this option if you see some pixelation around face contours"
)
gr.Markdown("<br>")
gr.Markdown("Source Image (above):")
with gr.Row():
source_faces_index = gr.Textbox(
value="0",
placeholder="Which face(s) to use as Source (comma separated)",
label="Comma separated face number(s); Example: 0,2,1",
)
gender_source = gr.Radio(
["No", "Female Only", "Male Only"],
value="No",
label="Gender Detection (Source)",
type="index",
)
gr.Markdown("<br>")
gr.Markdown("Target Image (result):")
with gr.Row():
faces_index = gr.Textbox(
value="0",
placeholder="Which face(s) to Swap into Target (comma separated)",
label="Comma separated face number(s); Example: 1,0,2",
)
gender_target = gr.Radio(
["No", "Female Only", "Male Only"],
value="No",
label="Gender Detection (Target)",
type="index",
)
gr.Markdown("<br>")
with gr.Row():
face_restorer_name = gr.Radio(
label="Restore Face",
choices=["None"] + [x.name() for x in shared.face_restorers],
value=shared.face_restorers[0].name(),
type="value",
)
with gr.Column():
face_restorer_visibility = gr.Slider(
0, 1, 1, step=0.1, label="Restore Face Visibility"
)
codeformer_weight = gr.Slider(
0, 1, 0.5, step=0.1, label="CodeFormer Weight", info="0 = maximum effect, 1 = minimum effect"
)
gr.Markdown("<br>")
swap_in_source = gr.Checkbox(
False,
label="Swap in source image",
visible=is_img2img,
)
swap_in_generated = gr.Checkbox(
True,
label="Swap in generated image",
visible=is_img2img,
)
msgs: dict = {
"extra_multiple_source": "",
}
img, imgs, select_source, face_model, source_folder, save_original, mask_face, source_faces_index, gender_source, faces_index, gender_target, face_restorer_name, face_restorer_visibility, codeformer_weight, swap_in_source, swap_in_generated = ui_main.show(is_img2img=is_img2img, **msgs)
# TAB UPSCALE
with gr.Tab("Upscale"):
restore_first = gr.Checkbox(
True,
label="1. Restore Face -> 2. Upscale (-Uncheck- if you want vice versa)",
info="Postprocessing Order"
)
with gr.Row():
upscaler_name = gr.Dropdown(
choices=[upscaler.name for upscaler in shared.sd_upscalers],
label="Upscaler",
value="None",
info="Won't scale if you choose -Swap in Source- via img2img, only 1x-postprocessing will affect (texturing, denoising, restyling etc.)"
)
upscalers_update = gr.Button(
value="🔄",
variant="tool",
)
upscalers_update.click(
update_upscalers_list,
inputs=[upscaler_name],
outputs=[upscaler_name],
)
gr.Markdown("<br>")
with gr.Row():
upscaler_scale = gr.Slider(1, 8, 1, step=0.1, label="Scale by")
upscaler_visibility = gr.Slider(
0, 1, 1, step=0.1, label="Upscaler Visibility (if scale = 1)"
)
restore_first, upscaler_name, upscaler_scale, upscaler_visibility = ui_upscale.show()
# TAB TOOLS
with gr.Tab("Tools 🆕"):
with gr.Tab("Face Models"):
gr.Markdown("Load an image containing one person, name it and click 'Build and Save'")
img_fm = gr.Image(
type="pil",
label="Load Image to build Face Model",
)
with gr.Row(equal_height=True):
fm_name = gr.Textbox(
value="",
placeholder="Please type any name (e.g. Elena)",
label="Face Model Name",
)
save_fm_btn = gr.Button("Build and Save")
save_fm = gr.Markdown("You can find saved models in 'models/reactor/faces'")
save_fm_btn.click(
build_face_model,
inputs=[img_fm, fm_name],
outputs=[save_fm],
)
ui_tools.show()
# TAB SETTINGS
with gr.Tab("Settings"):
models = get_models()
with gr.Row(visible=EP_is_visible):
device = gr.Radio(
label="Execution Provider",
choices=DEVICE_LIST,
value=DEVICE,
type="value",
info="If you already run 'Generate' - RESTART is required to apply. Click 'Save', (A1111) Extensions Tab -> 'Apply and restart UI' or (SD.Next) close the Server and start it again",
scale=2,
)
save_device_btn = gr.Button("Save", scale=0)
save = gr.Markdown("", visible=EP_is_visible)
setattr(device, "do_not_save_to_config", True)
save_device_btn.click(
set_Device,
inputs=[device],
outputs=[save],
)
with gr.Row():
if len(models) == 0:
logger.warning(
"You should at least have one model in models directory, please read the doc here: https://github.com/Gourieff/sd-webui-reactor/"
)
model = gr.Dropdown(
choices=models,
label="Model not found, please download one and refresh the list"
)
else:
model = gr.Dropdown(
choices=models, label="Model", value=models[0]
)
models_update = gr.Button(
value="🔄",
variant="tool",
)
models_update.click(
update_models_list,
inputs=[model],
outputs=[model],
)
console_logging_level = gr.Radio(
["No log", "Minimum", "Default"],
value="Minimum",
label="Console Log Level",
type="index"
)
gr.Markdown("<br>")
with gr.Row():
source_hash_check = gr.Checkbox(
True,
label="Source Image Hash Check",
info="Recommended to keep it ON. Processing is faster when Source Image is the same."
)
target_hash_check = gr.Checkbox(
False,
label="Target Image Hash Check",
info="Affects if you use Extras tab or img2img with only 'Swap in source image' on."
)
model, device, console_logging_level, source_hash_check, target_hash_check = ui_settings.show()
gr.Markdown("<span style='display:block;text-align:right;padding:3px;font-size:0.666em'>by Eugene Gourieff</span>")
gr.Markdown("<span style='display:block;text-align:right;padding:3px;font-size:0.666em;margin-bottom:-12px;'>by <a style='font-weight:normal' href='https://github.com/Gourieff' target='_blank'>Eugene Gourieff</a></span>")
return [
img,
@ -325,6 +95,8 @@ class FaceSwapScript(scripts.Script):
mask_face,
select_source,
face_model,
source_folder,
imgs,
]
@ -381,6 +153,8 @@ class FaceSwapScript(scripts.Script):
mask_face,
select_source,
face_model,
source_folder,
imgs,
):
self.enable = enable
if self.enable:
@ -391,7 +165,7 @@ class FaceSwapScript(scripts.Script):
if check_process_halt():
return
global MODELS_PATH
global SWAPPER_MODELS_PATH
self.source = img
self.face_restorer_name = face_restorer_name
self.upscaler_scale = upscaler_scale
@ -401,7 +175,7 @@ class FaceSwapScript(scripts.Script):
self.upscaler_name = upscaler_name
self.swap_in_source = swap_in_source
self.swap_in_generated = swap_in_generated
self.model = os.path.join(MODELS_PATH,model)
self.model = os.path.join(SWAPPER_MODELS_PATH,model)
self.console_logging_level = console_logging_level
self.gender_source = gender_source
self.gender_target = gender_target
@ -413,6 +187,8 @@ class FaceSwapScript(scripts.Script):
self.mask_face = mask_face
self.select_source = select_source
self.face_model = face_model
self.source_folder = source_folder
self.source_imgs = imgs
if self.gender_source is None or self.gender_source == "No":
self.gender_source = 0
if self.gender_target is None or self.gender_target == "No":
@ -439,7 +215,7 @@ class FaceSwapScript(scripts.Script):
logger.debug("*** Set Device")
set_Device(self.device)
if (self.source is not None and self.select_source == 0) or ((self.face_model is not None and self.face_model != "None") and self.select_source == 1):
if ((self.source is not None or self.source_imgs is not None) and self.select_source == 0) or ((self.face_model is not None and self.face_model != "None") and self.select_source == 1) or ((self.source_folder is not None and self.source_folder != "") and self.select_source == 2):
logger.debug("*** Log patch")
apply_logging_patch(console_logging_level)
if isinstance(p, StableDiffusionProcessingImg2Img) and self.swap_in_source:
@ -463,6 +239,8 @@ class FaceSwapScript(scripts.Script):
mask_face=self.mask_face,
select_source=self.select_source,
face_model = self.face_model,
source_folder = None,
source_imgs = None,
)
p.init_images[i] = result
# result_path = get_image_path(p.init_images[i], p.outpath_samples, "", p.all_seeds[i], p.all_prompts[i], "txt", p=p, suffix="-swapped")
@ -486,7 +264,7 @@ class FaceSwapScript(scripts.Script):
if check_process_halt():
return
if self.save_original:
if self.save_original or ((self.select_source == 2 and self.source_folder is not None and self.source_folder != "") or (self.select_source == 0 and self.source_imgs is not None and self.source is None)):
postprocess_run: bool = True
@ -497,8 +275,13 @@ class FaceSwapScript(scripts.Script):
# result_info: List = processed.infotexts
if self.swap_in_generated:
logger.status("Working: source face index %s, target face index %s", self.source_faces_index, self.faces_index)
# if self.source is not None:
if self.source is not None:
# self.source_folder = None
self.source_imgs = None
for i,(img,info) in enumerate(zip(orig_images, orig_infotexts)):
if check_process_halt():
postprocess_run = False
@ -520,16 +303,32 @@ class FaceSwapScript(scripts.Script):
mask_face=self.mask_face,
select_source=self.select_source,
face_model = self.face_model,
source_folder = self.source_folder,
source_imgs = self.source_imgs,
)
if result is not None and swapped > 0:
result_images.append(result)
suffix = "-swapped"
try:
img_path = save_image(result, p.outpath_samples, "", p.all_seeds[0], p.all_prompts[0], "png",info=info, p=p, suffix=suffix)
except:
logger.error("Cannot save a result image - please, check SD WebUI Settings (Saving and Paths)")
elif result is None:
logger.error("Cannot create a result image")
if self.select_source == 2 or (self.select_source == 0 and self.source_imgs is not None and self.source is None):
if len(result) > 0 and swapped > 0:
result_images.extend(result)
suffix = "-swapped"
for i,x in enumerate(result):
try:
img_path = save_image(result[i], p.outpath_samples, "", p.all_seeds[0], p.all_prompts[0], "png",info=info, p=p, suffix=suffix)
except:
logger.error("Cannot save a result image - please, check SD WebUI Settings (Saving and Paths)")
elif len(result) == 0:
logger.error("Cannot create a result image")
else:
if result is not None and swapped > 0:
result_images.append(result)
suffix = "-swapped"
try:
img_path = save_image(result, p.outpath_samples, "", p.all_seeds[0], p.all_prompts[0], "png",info=info, p=p, suffix=suffix)
except:
logger.error("Cannot save a result image - please, check SD WebUI Settings (Saving and Paths)")
elif result is None:
logger.error("Cannot create a result image")
# if len(output) != 0:
# split_fullfn = os.path.splitext(img_path[0])
@ -554,7 +353,7 @@ class FaceSwapScript(scripts.Script):
images = kwargs["images"]
def postprocess_image(self, p, script_pp: scripts.PostprocessImageArgs, *args):
if self.enable and self.swap_in_generated and not self.save_original:
if self.enable and self.swap_in_generated and not self.save_original and ((self.select_source == 0 and self.source is not None) or self.select_source == 1):
logger.debug("*** Check postprocess_image")
@ -583,6 +382,8 @@ class FaceSwapScript(scripts.Script):
mask_face=self.mask_face,
select_source=self.select_source,
face_model = self.face_model,
source_folder = None,
source_imgs = None,
)
try:
pp = scripts_postprocessing.PostprocessedImage(result)
@ -606,197 +407,24 @@ class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
def ui(self):
with gr.Accordion(f"{app_title}", open=False):
def update_fm_list(selected: str):
return gr.Dropdown.update(
value=selected, choices=get_model_names(get_facemodels)
)
def update_upscalers_list(selected: str):
return gr.Dropdown.update(
value=selected, choices=[upscaler.name for upscaler in shared.sd_upscalers]
)
def update_models_list(selected: str):
return gr.Dropdown.update(
value=selected, choices=get_models()
)
enable = gr.Checkbox(False, label="Enable", info=f"The Fast and Simple FaceSwap Extension - {version_flag}")
# TAB MAIN
with gr.Tab("Main"):
with gr.Column():
img = gr.Image(type="pil")
enable = gr.Checkbox(False, label="Enable", info=f"The Fast and Simple FaceSwap Extension - {version_flag}")
# gr.Markdown("<br>")
with gr.Row():
select_source = gr.Radio(
["Image","Face Model"],
value="Image",
label="Select Source",
type="index",
scale=1,
)
face_models = get_model_names(get_facemodels)
face_model = gr.Dropdown(
choices=face_models,
label="Choose Face Model",
value="None",
scale=2,
)
fm_update = gr.Button(
value="🔄",
variant="tool",
)
fm_update.click(
update_fm_list,
inputs=[face_model],
outputs=[face_model],
)
setattr(face_model, "do_not_save_to_config", True)
mask_face = gr.Checkbox(
False,
label="Face Mask Correction",
info="Apply this option if you see some pixelation around face contours"
)
gr.Markdown("Source Image (above):")
with gr.Row():
source_faces_index = gr.Textbox(
value="0",
placeholder="Which face(s) to use as Source (comma separated)",
label="Comma separated face number(s); Example: 0,2,1",
)
gender_source = gr.Radio(
["No", "Female Only", "Male Only"],
value="No",
label="Gender Detection (Source)",
type="index",
)
gr.Markdown("Target Image (result):")
with gr.Row():
faces_index = gr.Textbox(
value="0",
placeholder="Which face(s) to Swap into Target (comma separated)",
label="Comma separated face number(s); Example: 1,0,2",
)
gender_target = gr.Radio(
["No", "Female Only", "Male Only"],
value="No",
label="Gender Detection (Target)",
type="index",
)
with gr.Row():
face_restorer_name = gr.Radio(
label="Restore Face",
choices=["None"] + [x.name() for x in shared.face_restorers],
value=shared.face_restorers[0].name(),
type="value",
)
with gr.Column():
face_restorer_visibility = gr.Slider(
0, 1, 1, step=0.1, label="Restore Face Visibility"
)
codeformer_weight = gr.Slider(
0, 1, 0.5, step=0.1, label="CodeFormer Weight", info="0 = maximum effect, 1 = minimum effect"
)
msgs: dict = {
"extra_multiple_source": " | Сomparison grid as a result",
}
img, imgs, select_source, face_model, source_folder, save_original, mask_face, source_faces_index, gender_source, faces_index, gender_target, face_restorer_name, face_restorer_visibility, codeformer_weight, swap_in_source, swap_in_generated = ui_main.show(is_img2img=False, show_br=False, **msgs)
# TAB UPSCALE
with gr.Tab("Upscale"):
restore_first = gr.Checkbox(
True,
label="1. Restore Face -> 2. Upscale (-Uncheck- if you want vice versa)",
info="Postprocessing Order"
)
with gr.Row():
upscaler_name = gr.Dropdown(
choices=[upscaler.name for upscaler in shared.sd_upscalers],
label="Upscaler",
value="None",
info="Won't scale if you choose -Swap in Source- via img2img, only 1x-postprocessing will affect (texturing, denoising, restyling etc.)"
)
upscalers_update = gr.Button(
value="🔄",
variant="tool",
)
upscalers_update.click(
update_upscalers_list,
inputs=[upscaler_name],
outputs=[upscaler_name],
)
with gr.Row():
upscaler_scale = gr.Slider(1, 8, 1, step=0.1, label="Scale by")
upscaler_visibility = gr.Slider(
0, 1, 1, step=0.1, label="Upscaler Visibility (if scale = 1)"
)
restore_first, upscaler_name, upscaler_scale, upscaler_visibility = ui_upscale.show(show_br=False)
# TAB TOOLS
with gr.Tab("Tools 🆕"):
with gr.Tab("Face Models"):
gr.Markdown("Load an image containing one person, name it and click 'Build and Save'")
img_fm = gr.Image(
type="pil",
label="Load Image to build Face Model",
)
with gr.Row(equal_height=True):
fm_name = gr.Textbox(
value="",
placeholder="Please type any name (e.g. Elena)",
label="Face Model Name",
)
save_fm_btn = gr.Button("Build and Save")
save_fm = gr.Markdown("You can find saved models in 'models/reactor/faces'")
save_fm_btn.click(
build_face_model,
inputs=[img_fm, fm_name],
outputs=[save_fm],
)
ui_tools.show()
# TAB SETTINGS
with gr.Tab("Settings"):
models = get_models()
with gr.Row(visible=EP_is_visible):
device = gr.Radio(
label="Execution Provider",
choices=DEVICE_LIST,
value=DEVICE,
type="value",
info="If you already run 'Generate' - RESTART is required to apply. Click 'Save', (A1111) Extensions Tab -> 'Apply and restart UI' or (SD.Next) close the Server and start it again",
scale=2,
)
save_device_btn = gr.Button("Save", scale=0)
save = gr.Markdown("", visible=EP_is_visible)
setattr(device, "do_not_save_to_config", True)
save_device_btn.click(
set_Device,
inputs=[device],
outputs=[save],
)
with gr.Row():
if len(models) == 0:
logger.warning(
"You should at least have one model in models directory, please read the doc here: https://github.com/Gourieff/sd-webui-reactor/"
)
model = gr.Dropdown(
choices=models,
label="Model not found, please download one and refresh the list",
)
else:
model = gr.Dropdown(
choices=models, label="Model", value=models[0]
)
models_update = gr.Button(
value="🔄",
variant="tool",
)
models_update.click(
update_models_list,
inputs=[model],
outputs=[model],
)
console_logging_level = gr.Radio(
["No log", "Minimum", "Default"],
value="Minimum",
label="Console Log Level",
type="index",
)
model, device, console_logging_level, source_hash_check, target_hash_check = ui_settings.show(hash_check_block=False)
gr.Markdown("<span style='display:block;text-align:right;padding-right:3px;font-size:0.666em;margin: -9px 0'>by Eugene Gourieff</span>")
gr.Markdown("<span style='display:block;text-align:right;padding-right:3px;font-size:0.666em;margin: -9px 0'>by <a style='font-weight:normal' href='https://github.com/Gourieff' target='_blank'>Eugene Gourieff</a></span>")
args = {
'img': img,
@ -818,6 +446,8 @@ class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
'mask_face': mask_face,
'select_source': select_source,
'face_model': face_model,
'source_folder': source_folder,
'imgs': imgs,
}
return args
@ -853,7 +483,7 @@ class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
if check_process_halt():
return
global MODELS_PATH
global SWAPPER_MODELS_PATH
self.source = args['img']
self.face_restorer_name = args['face_restorer_name']
self.upscaler_scale = args['upscaler_scale']
@ -861,7 +491,7 @@ class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
self.face_restorer_visibility = args['face_restorer_visibility']
self.restore_first = args['restore_first']
self.upscaler_name = args['upscaler_name']
self.model = os.path.join(MODELS_PATH, args['model'])
self.model = os.path.join(SWAPPER_MODELS_PATH, args['model'])
self.console_logging_level = args['console_logging_level']
self.gender_source = args['gender_source']
self.gender_target = args['gender_target']
@ -870,6 +500,8 @@ class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
self.mask_face = args['mask_face']
self.select_source = args['select_source']
self.face_model = args['face_model']
self.source_folder = args['source_folder']
self.source_imgs = args['imgs']
if self.gender_source is None or self.gender_source == "No":
self.gender_source = 0
if self.gender_target is None or self.gender_target == "No":
@ -894,9 +526,15 @@ class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
set_Device(self.device)
if (self.source is not None and self.select_source == 0) or ((self.face_model is not None and self.face_model != "None") and self.select_source == 1):
logger.debug("We're here: process() 1")
if (self.source is not None and self.select_source == 0) or ((self.face_model is not None and self.face_model != "None") and self.select_source == 1) or ((self.source_folder is not None and self.source_folder != "") and self.select_source == 2) or ((self.source_imgs is not None and self.source is None) and self.select_source == 0):
logger.debug("We're here: process() 2")
apply_logging_patch(self.console_logging_level)
logger.status("Working: source face index %s, target face index %s", self.source_faces_index, self.faces_index)
# if self.select_source != 2:
image: Image.Image = pp.image
result, output, swapped = swap_face(
self.source,
@ -913,12 +551,27 @@ class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
mask_face=self.mask_face,
select_source=self.select_source,
face_model=self.face_model,
source_folder=self.source_folder,
source_imgs=self.source_imgs,
)
try:
pp.info["ReActor"] = True
pp.image = result
logger.status("---Done!---")
except Exception:
logger.error("Cannot create a result image")
if self.select_source == 2 or (self.select_source == 0 and self.source_imgs is not None and self.source is None):
if len(result) > 0 and swapped > 0:
image = result[0]
if len(result) > 1:
grid = make_grid(result)
result.insert(0, grid)
image = grid
pp.info["ReActor"] = True
pp.image = image
logger.status("---Done!---")
else:
logger.error("Cannot create a result image")
else:
try:
pp.info["ReActor"] = True
pp.image = result
logger.status("---Done!---")
except Exception:
logger.error("Cannot create a result image")
else:
logger.error("Please provide a source face")

3
scripts/reactor_globals.py
View File

@ -14,7 +14,8 @@ BASE_PATH = os.path.join(Path(__file__).parents[1])
DEVICE_LIST: list = ["CPU", "CUDA"]
MODELS_PATH = models_path
REACTOR_MODELS_PATH = os.path.join(models_path, "reactor")
SWAPPER_MODELS_PATH = os.path.join(MODELS_PATH, "insightface")
REACTOR_MODELS_PATH = os.path.join(MODELS_PATH, "reactor")
FACE_MODELS_PATH = os.path.join(REACTOR_MODELS_PATH, "faces")
if not os.path.exists(REACTOR_MODELS_PATH):

32
scripts/reactor_helpers.py
View File

@ -13,6 +13,16 @@ from modules.images import FilenameGenerator, get_next_sequence_number
from modules import shared, script_callbacks
from scripts.reactor_globals import DEVICE, BASE_PATH, FACE_MODELS_PATH
try:
from modules.paths_internal import models_path
except:
try:
from modules.paths import models_path
except:
model_path = os.path.abspath("models")
MODELS_PATH = None
def set_Device(value):
global DEVICE
DEVICE = value
@ -155,6 +165,20 @@ def save_face_model(face: Face, filename: str) -> None:
except Exception as e:
print(f"Error: {e}")
def get_models():
global MODELS_PATH
models_path_init = os.path.join(models_path, "insightface/*")
models = glob.glob(models_path_init)
models = [x for x in models if x.endswith(".onnx") or x.endswith(".pth")]
models_names = []
for model in models:
model_path = os.path.split(model)
if MODELS_PATH is None:
MODELS_PATH = model_path[0]
model_name = model_path[1]
models_names.append(model_name)
return models_names
def load_face_model(filename: str):
face = {}
model_path = os.path.join(FACE_MODELS_PATH, filename)
@ -175,3 +199,11 @@ def get_model_names(get_models):
for x in models:
names.append(os.path.basename(x))
return names
def get_images_from_folder(path: str):
images_path = os.path.join(path, "*")
images = glob.glob(images_path)
return [Image.open(x) for x in images if x.endswith(('jpg', 'png', 'jpeg', 'webp', 'bmp'))]
def get_images_from_list(imgs: List):
return [Image.open(os.path.abspath(x.name)) for x in imgs]

454
scripts/reactor_swapper.py
View File

@ -11,7 +11,14 @@ import insightface
from insightface.app.common import Face
from scripts.reactor_globals import FACE_MODELS_PATH
from scripts.reactor_helpers import get_image_md5hash, get_Device, save_face_model, load_face_model
from scripts.reactor_helpers import (
get_image_md5hash,
get_Device,
save_face_model,
load_face_model,
get_images_from_folder,
get_images_from_list
)
from scripts.console_log_patch import apply_logging_patch
from modules.face_restoration import FaceRestoration
@ -22,7 +29,7 @@ except: # SD.Next
from modules.upscaler import UpscalerData
from modules.shared import state
from scripts.reactor_logger import logger
from modules.reactor_mask import apply_face_mask
from reactor_modules.reactor_mask import apply_face_mask
try:
from modules.paths_internal import models_path
@ -92,6 +99,14 @@ SOURCE_FACES = None
SOURCE_IMAGE_HASH = None
TARGET_FACES = None
TARGET_IMAGE_HASH = None
SOURCE_FACES_LIST = []
SOURCE_IMAGE_LIST_HASH = []
def clear_faces_list():
global SOURCE_FACES_LIST, SOURCE_IMAGE_LIST_HASH
SOURCE_FACES_LIST = []
SOURCE_IMAGE_LIST_HASH = []
logger.status("Source Images Hash has been reset (for Multiple or Folder Source)")
def getAnalysisModel():
@ -315,8 +330,11 @@ def swap_face(
mask_face: bool = False,
select_source: int = 0,
face_model: str = "None",
source_folder: str = "",
source_imgs: Union[List, None] = None,
):
global SOURCE_FACES, SOURCE_IMAGE_HASH, TARGET_FACES, TARGET_IMAGE_HASH, PROVIDERS
global SOURCE_FACES, SOURCE_IMAGE_HASH, TARGET_FACES, TARGET_IMAGE_HASH, PROVIDERS, SOURCE_FACES_LIST, SOURCE_IMAGE_LIST_HASH
result_image = target_img
PROVIDERS = ["CUDAExecutionProvider"] if device == "CUDA" else ["CPUExecutionProvider"]
@ -348,178 +366,228 @@ def swap_face(
output_info: str = ""
swapped = 0
if select_source == 0 and source_img is not None:
# *****************
# SWAP from FOLDER or MULTIPLE images:
source_img = cv2.cvtColor(np.array(source_img), cv2.COLOR_RGB2BGR)
if (select_source == 0 and source_imgs is not None) or (select_source == 2 and (source_folder is not None and source_folder != "")):
if source_hash_check:
result = []
source_image_md5hash = get_image_md5hash(source_img)
source_images = get_images_from_folder(source_folder) if select_source == 2 else get_images_from_list(source_imgs)
if SOURCE_IMAGE_HASH is None:
SOURCE_IMAGE_HASH = source_image_md5hash
source_image_same = False
else:
source_image_same = True if SOURCE_IMAGE_HASH == source_image_md5hash else False
if not source_image_same:
SOURCE_IMAGE_HASH = source_image_md5hash
if len(source_images) > 0:
source_img_ff = []
source_faces_ff = []
for i, source_image in enumerate(source_images):
logger.info("Source Image MD5 Hash = %s", SOURCE_IMAGE_HASH)
logger.info("Source Image the Same? %s", source_image_same)
source_image = cv2.cvtColor(np.array(source_image), cv2.COLOR_RGB2BGR)
source_img_ff.append(source_image)
if SOURCE_FACES is None or not source_image_same:
logger.status("Analyzing Source Image...")
source_faces = analyze_faces(source_img)
SOURCE_FACES = source_faces
elif source_image_same:
logger.status("Using Hashed Source Face(s) Model...")
source_faces = SOURCE_FACES
if source_hash_check:
else:
logger.status("Analyzing Source Image...")
source_faces = analyze_faces(source_img)
source_image_md5hash = get_image_md5hash(source_image)
elif select_source == 1 and (face_model is not None and face_model != "None"):
source_face_model = [load_face_model(face_model)]
if source_face_model is not None:
source_faces_index = [0]
source_faces = source_face_model
logger.status("Using Loaded Source Face Model...")
else:
logger.error(f"Cannot load Face Model File: {face_model}.safetensors")
else:
logger.error("Cannot detect any Source")
if len(SOURCE_IMAGE_LIST_HASH) == 0:
SOURCE_IMAGE_LIST_HASH = [source_image_md5hash]
source_image_same = False
elif len(SOURCE_IMAGE_LIST_HASH) == i:
SOURCE_IMAGE_LIST_HASH.append(source_image_md5hash)
source_image_same = False
else:
source_image_same = True if SOURCE_IMAGE_LIST_HASH[i] == source_image_md5hash else False
if not source_image_same:
SOURCE_IMAGE_LIST_HASH[i] = source_image_md5hash
if source_faces is not None:
logger.info("(Image %s) Source Image MD5 Hash = %s", i, SOURCE_IMAGE_LIST_HASH[i])
logger.info("(Image %s) Source Image the Same? %s", i, source_image_same)
if target_hash_check:
if len(SOURCE_FACES_LIST) == 0:
logger.status(f"Analyzing Source Image {i}...")
source_faces = analyze_faces(source_image)
SOURCE_FACES_LIST = [source_faces]
elif len(SOURCE_FACES_LIST) == i and not source_image_same:
logger.status(f"Analyzing Source Image {i}...")
source_faces = analyze_faces(source_image)
SOURCE_FACES_LIST.append(source_faces)
elif len(SOURCE_FACES_LIST) != i and not source_image_same:
logger.status(f"Analyzing Source Image {i}...")
source_faces = analyze_faces(source_image)
SOURCE_FACES_LIST[i] = source_faces
elif source_image_same:
logger.status("(Image %s) Using Hashed Source Face(s) Model...", i)
source_faces = SOURCE_FACES_LIST[i]
target_image_md5hash = get_image_md5hash(target_img)
else:
logger.status(f"Analyzing Source Image {i}...")
source_faces = analyze_faces(source_image)
if TARGET_IMAGE_HASH is None:
TARGET_IMAGE_HASH = target_image_md5hash
target_image_same = False
else:
target_image_same = True if TARGET_IMAGE_HASH == target_image_md5hash else False
if not target_image_same:
if source_faces is not None:
source_faces_ff.append(source_faces)
if len(source_faces_ff) > 0:
if target_hash_check:
target_image_md5hash = get_image_md5hash(target_img)
if TARGET_IMAGE_HASH is None:
TARGET_IMAGE_HASH = target_image_md5hash
target_image_same = False
else:
target_image_same = True if TARGET_IMAGE_HASH == target_image_md5hash else False
if not target_image_same:
TARGET_IMAGE_HASH = target_image_md5hash
logger.info("Target Image MD5 Hash = %s", TARGET_IMAGE_HASH)
logger.info("Target Image the Same? %s", target_image_same)
logger.info("Target Image MD5 Hash = %s", TARGET_IMAGE_HASH)
logger.info("Target Image the Same? %s", target_image_same)
if TARGET_FACES is None or not target_image_same:
if TARGET_FACES is None or not target_image_same:
logger.status("Analyzing Target Image...")
target_faces = analyze_faces(target_img)
TARGET_FACES = target_faces
elif target_image_same:
logger.status("Using Hashed Target Face(s) Model...")
target_faces = TARGET_FACES
else:
logger.status("Analyzing Target Image...")
target_faces = analyze_faces(target_img)
TARGET_FACES = target_faces
elif target_image_same:
logger.status("Using Hashed Target Face(s) Model...")
target_faces = TARGET_FACES
else:
logger.status("Analyzing Target Image...")
target_faces = analyze_faces(target_img)
for i,source_faces in enumerate(source_faces_ff):
logger.status("Detecting Source Face, Index = %s", source_faces_index[0])
if select_source == 0 and source_img is not None:
source_face, wrong_gender, source_age, source_gender = get_face_single(source_img, source_faces, face_index=source_faces_index[0], gender_source=gender_source)
else:
source_face = sorted(source_faces, key=lambda x: x.bbox[0])[source_faces_index[0]]
wrong_gender = 0
source_age = source_face["age"]
source_gender = "Female" if source_face["gender"] == 0 else "Male"
if source_age != "None" or source_gender != "None":
logger.status("Detected: -%s- y.o. %s", source_age, source_gender)
logger.status("(Image %s) Detecting Source Face, Index = %s", i, source_faces_index[0])
source_face, wrong_gender, source_age, source_gender = get_face_single(source_img_ff[i], source_faces, face_index=source_faces_index[0], gender_source=gender_source)
output_info = f"SourceFaceIndex={source_faces_index[0]};Age={source_age};Gender={source_gender}\n"
output.append(output_info)
if source_age != "None" or source_gender != "None":
logger.status("(Image %s) Detected: -%s- y.o. %s", i, source_age, source_gender)
if len(source_faces_index) != 0 and len(source_faces_index) != 1 and len(source_faces_index) != len(faces_index):
logger.status("Source Faces must have no entries (default=0), one entry, or same number of entries as target faces.")
elif source_face is not None:
if len(source_faces_index) != 0 and len(source_faces_index) != 1 and len(source_faces_index) != len(faces_index):
logger.status("Source Faces must have no entries (default=0), one entry, or same number of entries as target faces.")
result = target_img
face_swapper = getFaceSwapModel(model)
elif source_face is not None:
source_face_idx = 0
result_image, output, swapped = operate(source_img_ff[i],target_img,target_img_orig,model,source_faces_index,faces_index,source_faces,target_faces,gender_source,gender_target,source_face,wrong_gender,source_age,source_gender,output,swapped,mask_face,entire_mask_image,enhancement_options)
for face_num in faces_index:
if check_process_halt():
return result_image, [], 0
if len(source_faces_index) > 1 and source_face_idx > 0:
logger.status("Detecting Source Face, Index = %s", source_faces_index[source_face_idx])
source_face, wrong_gender, source_age, source_gender = get_face_single(source_img, source_faces, face_index=source_faces_index[source_face_idx], gender_source=gender_source)
if source_age != "None" or source_gender != "None":
logger.status("Detected: -%s- y.o. %s", source_age, source_gender)
result.append(result_image)
output_info = f"SourceFaceIndex={source_faces_index[source_face_idx]};Age={source_age};Gender={source_gender}\n"
output.append(output_info)
result = [result_image] if len(result) == 0 else result
source_face_idx += 1
return result, output, swapped
if source_face is not None and wrong_gender == 0:
logger.status("Detecting Target Face, Index = %s", face_num)
target_face, wrong_gender, target_age, target_gender = get_face_single(target_img, target_faces, face_index=face_num, gender_target=gender_target)
if target_age != "None" or target_gender != "None":
logger.status("Detected: -%s- y.o. %s", target_age, target_gender)
# END
# *****************
output_info = f"TargetFaceIndex={face_num};Age={target_age};Gender={target_gender}\n"
output.append(output_info)
# ***********************
# SWAP from IMG or MODEL:
if target_face is not None and wrong_gender == 0:
logger.status("Swapping Source into Target")
swapped_image = face_swapper.get(result, target_face, source_face)
if mask_face:
result = apply_face_mask(swapped_image=swapped_image,target_image=result,target_face=target_face,entire_mask_image=entire_mask_image)
else:
result = swapped_image
swapped += 1
elif wrong_gender == 1:
wrong_gender = 0
if source_face_idx == len(source_faces_index):
result_image = Image.fromarray(cv2.cvtColor(result, cv2.COLOR_BGR2RGB))
if enhancement_options is not None and len(source_faces_index) > 1:
result_image = enhance_image(result_image, enhancement_options)
return result_image, output, swapped
else:
logger.status(f"No target face found for {face_num}")
elif wrong_gender == 1:
wrong_gender = 0
if source_face_idx == len(source_faces_index):
result_image = Image.fromarray(cv2.cvtColor(result, cv2.COLOR_BGR2RGB))
if enhancement_options is not None and len(source_faces_index) > 1:
result_image = enhance_image(result_image, enhancement_options)
return result_image, output, swapped
else:
logger.status(f"No source face found for face number {source_face_idx}.")
result_image = Image.fromarray(cv2.cvtColor(result, cv2.COLOR_BGR2RGB))
if enhancement_options is not None and swapped > 0:
if mask_face and entire_mask_image is not None:
result_image = enhance_image_and_mask(result_image, enhancement_options,Image.fromarray(target_img_orig),Image.fromarray(entire_mask_image).convert("L"))
else:
result_image = enhance_image(result_image, enhancement_options)
elif mask_face and entire_mask_image is not None and swapped > 0:
result_image = Image.composite(result_image,Image.fromarray(target_img_orig),Image.fromarray(entire_mask_image).convert("L"))
else:
logger.status("No source face(s) in the provided Index")
else:
logger.status("No source face(s) found")
return result_image, output, swapped
if select_source == 0 and source_img is not None:
source_img = cv2.cvtColor(np.array(source_img), cv2.COLOR_RGB2BGR)
if source_hash_check:
source_image_md5hash = get_image_md5hash(source_img)
if SOURCE_IMAGE_HASH is None:
SOURCE_IMAGE_HASH = source_image_md5hash
source_image_same = False
else:
source_image_same = True if SOURCE_IMAGE_HASH == source_image_md5hash else False
if not source_image_same:
SOURCE_IMAGE_HASH = source_image_md5hash
logger.info("Source Image MD5 Hash = %s", SOURCE_IMAGE_HASH)
logger.info("Source Image the Same? %s", source_image_same)
if SOURCE_FACES is None or not source_image_same:
logger.status("Analyzing Source Image...")
source_faces = analyze_faces(source_img)
SOURCE_FACES = source_faces
elif source_image_same:
logger.status("Using Hashed Source Face(s) Model...")
source_faces = SOURCE_FACES
else:
logger.status("Analyzing Source Image...")
source_faces = analyze_faces(source_img)
elif select_source == 1 and (face_model is not None and face_model != "None"):
source_face_model = [load_face_model(face_model)]
if source_face_model is not None:
source_faces_index = [0]
source_faces = source_face_model
logger.status("Using Loaded Source Face Model...")
else:
logger.error(f"Cannot load Face Model File: {face_model}.safetensors")
else:
logger.error("Cannot detect any Source")
return result_image, [], 0
if source_faces is not None:
if target_hash_check:
target_image_md5hash = get_image_md5hash(target_img)
if TARGET_IMAGE_HASH is None:
TARGET_IMAGE_HASH = target_image_md5hash
target_image_same = False
else:
target_image_same = True if TARGET_IMAGE_HASH == target_image_md5hash else False
if not target_image_same:
TARGET_IMAGE_HASH = target_image_md5hash
logger.info("Target Image MD5 Hash = %s", TARGET_IMAGE_HASH)
logger.info("Target Image the Same? %s", target_image_same)
if TARGET_FACES is None or not target_image_same:
logger.status("Analyzing Target Image...")
target_faces = analyze_faces(target_img)
TARGET_FACES = target_faces
elif target_image_same:
logger.status("Using Hashed Target Face(s) Model...")
target_faces = TARGET_FACES
else:
logger.status("Analyzing Target Image...")
target_faces = analyze_faces(target_img)
logger.status("Detecting Source Face, Index = %s", source_faces_index[0])
if select_source == 0 and source_img is not None:
source_face, wrong_gender, source_age, source_gender = get_face_single(source_img, source_faces, face_index=source_faces_index[0], gender_source=gender_source)
else:
source_face = sorted(source_faces, key=lambda x: x.bbox[0])[source_faces_index[0]]
wrong_gender = 0
source_age = source_face["age"]
source_gender = "Female" if source_face["gender"] == 0 else "Male"
if source_age != "None" or source_gender != "None":
logger.status("Detected: -%s- y.o. %s", source_age, source_gender)
output_info = f"SourceFaceIndex={source_faces_index[0]};Age={source_age};Gender={source_gender}\n"
output.append(output_info)
if len(source_faces_index) != 0 and len(source_faces_index) != 1 and len(source_faces_index) != len(faces_index):
logger.status("Source Faces must have no entries (default=0), one entry, or same number of entries as target faces.")
elif source_face is not None:
result_image, output, swapped = operate(source_img,target_img,target_img_orig,model,source_faces_index,faces_index,source_faces,target_faces,gender_source,gender_target,source_face,wrong_gender,source_age,source_gender,output,swapped,mask_face,entire_mask_image,enhancement_options)
else:
logger.status("No source face(s) in the provided Index")
else:
logger.status("No source face(s) found")
return result_image, output, swapped
# END
# **********************
return result_image, [], 0
def build_face_model(image: Image.Image, name: str):
if image is None:
@ -545,3 +613,103 @@ def build_face_model(image: Image.Image, name: str):
no_face_msg = "No face found, please try another image"
logger.error(no_face_msg)
return no_face_msg
def operate(
source_img,
target_img,
target_img_orig,
model,
source_faces_index,
faces_index,
source_faces,
target_faces,
gender_source,
gender_target,
source_face,
wrong_gender,
source_age,
source_gender,
output,
swapped,
mask_face,
entire_mask_image,
enhancement_options,
):
result = target_img
face_swapper = getFaceSwapModel(model)
source_face_idx = 0
for face_num in faces_index:
if check_process_halt():
return result_image, [], 0
if len(source_faces_index) > 1 and source_face_idx > 0:
logger.status("Detecting Source Face, Index = %s", source_faces_index[source_face_idx])
source_face, wrong_gender, source_age, source_gender = get_face_single(source_img, source_faces, face_index=source_faces_index[source_face_idx], gender_source=gender_source)
if source_age != "None" or source_gender != "None":
logger.status("Detected: -%s- y.o. %s", source_age, source_gender)
output_info = f"SourceFaceIndex={source_faces_index[source_face_idx]};Age={source_age};Gender={source_gender}\n"
output.append(output_info)
source_face_idx += 1
if source_face is not None and wrong_gender == 0:
logger.status("Detecting Target Face, Index = %s", face_num)
target_face, wrong_gender, target_age, target_gender = get_face_single(target_img, target_faces, face_index=face_num, gender_target=gender_target)
if target_age != "None" or target_gender != "None":
logger.status("Detected: -%s- y.o. %s", target_age, target_gender)
output_info = f"TargetFaceIndex={face_num};Age={target_age};Gender={target_gender}\n"
output.append(output_info)
if target_face is not None and wrong_gender == 0:
logger.status("Swapping Source into Target")
swapped_image = face_swapper.get(result, target_face, source_face)
if mask_face:
result = apply_face_mask(swapped_image=swapped_image,target_image=result,target_face=target_face,entire_mask_image=entire_mask_image)
else:
result = swapped_image
swapped += 1
elif wrong_gender == 1:
wrong_gender = 0
if source_face_idx == len(source_faces_index):
result_image = Image.fromarray(cv2.cvtColor(result, cv2.COLOR_BGR2RGB))
if enhancement_options is not None and len(source_faces_index) > 1:
result_image = enhance_image(result_image, enhancement_options)
return result_image, output, swapped
else:
logger.status(f"No target face found for {face_num}")
elif wrong_gender == 1:
wrong_gender = 0
if source_face_idx == len(source_faces_index):
result_image = Image.fromarray(cv2.cvtColor(result, cv2.COLOR_BGR2RGB))
if enhancement_options is not None and len(source_faces_index) > 1:
result_image = enhance_image(result_image, enhancement_options)
return result_image, output, swapped
else:
logger.status(f"No source face found for face number {source_face_idx}.")
result_image = Image.fromarray(cv2.cvtColor(result, cv2.COLOR_BGR2RGB))
if enhancement_options is not None and swapped > 0:
if mask_face and entire_mask_image is not None:
result_image = enhance_image_and_mask(result_image, enhancement_options,Image.fromarray(target_img_orig),Image.fromarray(entire_mask_image).convert("L"))
else:
result_image = enhance_image(result_image, enhancement_options)
elif mask_face and entire_mask_image is not None and swapped > 0:
result_image = Image.composite(result_image,Image.fromarray(target_img_orig),Image.fromarray(entire_mask_image).convert("L"))
return result_image, output, swapped

2
scripts/reactor_version.py
View File

@ -1,5 +1,5 @@
app_title = "ReActor"
version_flag = "v0.5.1"
version_flag = "v0.6.0-a1"
from scripts.reactor_logger import logger, get_Run, set_Run