UPDATE: Gender Detection; FIX: install cond ">="
+ VersionUP (beta)
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Gourieff
parent
b0307f6428
commit
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@ -1,4 +1,4 @@
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# ReActor 0.3.0 for StableDiffusion
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# ReActor 0.3.1b for StableDiffusion
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### The Fast and Simple "[roop-based](https://github.com/s0md3v/sd-webui-roop)" FaceSwap Extension with a lot of improvements and without NSFW filter (uncensored, use it on your own [responsibility](#disclaimer))
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> Ex "Roop-GE" (GE - Gourieff Edition, aka "NSFW-Roop"), the extension was renamed with the version 0.3.0<br>
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@ -36,6 +36,8 @@ args=[
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False, #11 Swap in source image
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True, #12 Swap in generated image
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1, #13 Console Log Level (0 - min, 1 - med or 2 - max)
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0, #14 Gender Detection (Source) (0 - No, 1 - Female Only, 2 - Male Only)
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0, #15 Gender Detection (Target) (0 - No, 1 - Female Only, 2 - Male Only)
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]
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# The args for ReActor can be found by
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17
install.py
17
install.py
@ -3,6 +3,7 @@ import os, sys
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import pkg_resources
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from tqdm import tqdm
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import urllib.request
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from packaging import version as pv
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req_file = os.path.join(os.path.dirname(os.path.realpath(__file__)), "requirements.txt")
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@ -16,20 +17,21 @@ def run_pip(*args):
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subprocess.run([sys.executable, "-m", "pip", "install", *args])
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def is_installed (
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package: str, version: str | None = None
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package: str, version: str | None = None, strict: bool = True
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):
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has_package = None
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try:
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has_package = pkg_resources.get_distribution(package)
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if has_package is not None:
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installed_version = has_package.version
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if installed_version != version:
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if (installed_version != version and strict == True) or (pv.parse(installed_version) < pv.parse(version) and strict == False):
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return False
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else:
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return True
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else:
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return False
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except:
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except Exception as e:
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print(f"Error: {e}")
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return False
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def download(url, path):
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@ -44,16 +46,20 @@ if not os.path.exists(models_dir):
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if not os.path.exists(model_path):
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download(model_url, model_path)
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print("Checking ReActor (ex Roop-GE) requirements...", end=' ')
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print("Checking ReActor requirements...", end=' ')
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with open(req_file) as file:
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install_count = 0
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strict = True
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for package in file:
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package_version = None
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try:
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package = package.strip()
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if "==" in package:
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package_version = package.split('==')[1]
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if not is_installed(package,package_version):
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elif ">=" in package:
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package_version = package.split('>=')[1]
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strict = False
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if not is_installed(package,package_version,strict):
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install_count += 1
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run_pip(package)
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except Exception as e:
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@ -61,6 +67,7 @@ with open(req_file) as file:
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print(f"\nERROR: Failed to install {package} - ReActor won't start")
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raise e
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if install_count > 0:
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print(f'install_count={install_count}')
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print(f'\n--- PLEASE, RESTART the Server! ---\n')
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else:
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print('Ok')
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@ -1,4 +1,4 @@
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insightface==0.7.3
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onnx==1.14.0
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onnxruntime==1.15.0
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opencv-python==4.7.0.72
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opencv-python>=4.7.0.72
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@ -42,21 +42,39 @@ class FaceSwapScript(scripts.Script):
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return scripts.AlwaysVisible
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def ui(self, is_img2img):
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with gr.Accordion(f"{app_title} (ex Roop-GE)", open=False):
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with gr.Accordion(f"{app_title}", open=False):
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with gr.Column():
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img = gr.inputs.Image(type="pil")
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enable = gr.Checkbox(False, label="Enable", info=f"The Fast and Simple \"roop-based\" FaceSwap Extension - {version_flag}")
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gr.Markdown("---")
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gr.Markdown("Source Image (above):")
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with gr.Row():
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source_faces_index = gr.Textbox(
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value="0",
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placeholder="Which face(s) to use as source (comma separated)",
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label="Comma separated face number(s) from swap-source image (above); Example: 0,2,1",
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placeholder="Which face(s) to use as Source (comma separated)",
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label="Comma separated face number(s); Example: 0,2,1",
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)
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gender_source = gr.Radio(
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["No", "Female Only", "Male Only"],
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value="No",
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label="Gender Detection (Source)",
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type="index",
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)
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gr.Markdown("---")
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gr.Markdown("Target Image (result):")
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with gr.Row():
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faces_index = gr.Textbox(
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value="0",
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placeholder="Which face to swap (comma separated)",
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label="Comma separated face number(s) for target image (result); Example: 1,0,2",
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placeholder="Which face(s) to Swap into Target (comma separated)",
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label="Comma separated face number(s); Example: 1,0,2",
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)
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gender_target = gr.Radio(
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["No", "Female Only", "Male Only"],
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value="No",
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label="Gender Detection (Target)",
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type="index",
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)
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gr.Markdown("---")
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with gr.Row():
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face_restorer_name = gr.Radio(
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label="Restore Face",
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@ -81,7 +99,7 @@ class FaceSwapScript(scripts.Script):
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upscaler_visibility = gr.Slider(
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0, 1, 1, step=0.1, label="Upscaler Visibility (if scale = 1)"
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)
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gr.Markdown("---")
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swap_in_source = gr.Checkbox(
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False,
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label="Swap in source image",
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@ -113,6 +131,7 @@ class FaceSwapScript(scripts.Script):
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label="Console Log Level",
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type="index",
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)
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gr.Markdown("---")
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return [
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img,
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@ -128,7 +147,9 @@ class FaceSwapScript(scripts.Script):
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upscaler_visibility,
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swap_in_source,
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swap_in_generated,
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console_logging_level
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console_logging_level,
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gender_source,
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gender_target,
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]
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@ -174,6 +195,8 @@ class FaceSwapScript(scripts.Script):
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swap_in_source,
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swap_in_generated,
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console_logging_level,
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gender_source,
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gender_target,
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):
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global MODELS_PATH
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self.source = img
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@ -187,6 +210,8 @@ class FaceSwapScript(scripts.Script):
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self.swap_in_generated = swap_in_generated
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self.model = os.path.join(MODELS_PATH,model)
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self.console_logging_level = console_logging_level
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self.gender_source = gender_source
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self.gender_target = gender_target
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self.source_faces_index = [
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int(x) for x in source_faces_index.strip(",").split(",") if x.isnumeric()
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]
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@ -212,6 +237,8 @@ class FaceSwapScript(scripts.Script):
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faces_index=self.faces_index,
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model=self.model,
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upscale_options=self.upscale_options,
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gender_source=self.gender_source,
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gender_target=self.gender_target,
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)
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p.init_images[i] = result
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else:
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@ -233,6 +260,8 @@ class FaceSwapScript(scripts.Script):
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faces_index=self.faces_index,
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model=self.model,
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upscale_options=self.upscale_options,
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gender_source=self.gender_source,
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gender_target=self.gender_target,
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)
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try:
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pp = scripts_postprocessing.PostprocessedImage(result)
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@ -60,7 +60,7 @@ def getAnalysisModel():
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global ANALYSIS_MODEL
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if ANALYSIS_MODEL is None:
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ANALYSIS_MODEL = insightface.app.FaceAnalysis(
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name="buffalo_l", providers=providers
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name="buffalo_l", providers=providers # note: allowed_modules=['detection', 'genderage']
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)
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return ANALYSIS_MODEL
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@ -129,19 +129,57 @@ def upscale_image(image: Image, upscale_options: UpscaleOptions):
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return result_image
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def get_face_single(img_data: np.ndarray, face_index=0, det_size=(640, 640)):
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def get_face_gender(
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face,
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face_index,
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gender_condition,
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operated: str
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):
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gender = [
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x.sex
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for x in face
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]
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gender.reverse()
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face_gender = gender[face_index]
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logger.info("%s Face %s: Detected Gender -%s-", operated, face_index, face_gender)
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if (gender_condition == 1 and face_gender == "F") or (gender_condition == 2 and face_gender == "M"):
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logger.info("OK - Detected Gender matches Condition")
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try:
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return sorted(face, key=lambda x: x.bbox[0])[face_index], 0
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except IndexError:
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return None, 0
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else:
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logger.info("WRONG - Detected Gender doesn't match Condition")
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return sorted(face, key=lambda x: x.bbox[0])[face_index], 1
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def reget_face_single(img_data, det_size, face_index):
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det_size_half = (det_size[0] // 2, det_size[1] // 2)
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return get_face_single(img_data, face_index=face_index, det_size=det_size_half)
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def get_face_single(img_data: np.ndarray, face_index=0, det_size=(640, 640), gender_source=0, gender_target=0):
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face_analyser = copy.deepcopy(getAnalysisModel())
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face_analyser.prepare(ctx_id=0, det_size=det_size)
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face = face_analyser.get(img_data)
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if gender_source != 0:
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if len(face) == 0 and det_size[0] > 320 and det_size[1] > 320:
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return reget_face_single(img_data, det_size, face_index)
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return get_face_gender(face,face_index,gender_source,"Source")
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if gender_target != 0:
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if len(face) == 0 and det_size[0] > 320 and det_size[1] > 320:
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return reget_face_single(img_data, det_size, face_index)
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return get_face_gender(face,face_index,gender_target,"Target")
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if len(face) == 0 and det_size[0] > 320 and det_size[1] > 320:
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det_size_half = (det_size[0] // 2, det_size[1] // 2)
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return get_face_single(img_data, face_index=face_index, det_size=det_size_half)
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return reget_face_single(img_data, det_size, face_index)
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try:
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return sorted(face, key=lambda x: x.bbox[0])[face_index]
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return sorted(face, key=lambda x: x.bbox[0])[face_index], 0
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except IndexError:
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return None
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return None, 0
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def swap_face(
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@ -151,6 +189,8 @@ def swap_face(
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source_faces_index: List[int] = [0],
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faces_index: List[int] = [0],
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upscale_options: Union[UpscaleOptions, None] = None,
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gender_source: int = 0,
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gender_target: int = 0,
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):
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result_image = target_img
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if model is not None:
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@ -170,9 +210,11 @@ def swap_face(
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source_img = cv2.cvtColor(np.array(source_img), cv2.COLOR_RGB2BGR)
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target_img = cv2.cvtColor(np.array(target_img), cv2.COLOR_RGB2BGR)
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source_face = get_face_single(source_img, face_index=source_faces_index[0])
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source_face, wrong_gender = get_face_single(source_img, face_index=source_faces_index[0], gender_source=gender_source)
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if len(source_faces_index) != 0 and len(source_faces_index) != 1 and len(source_faces_index) != len(faces_index):
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logger.info(f'Source Faces must have no entries (default=0), one entry, or same number of entries as target faces.')
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logger.info(f'Source Faces must have no entries (default=0), one entry, or same number of entries as target faces.')
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elif source_face is not None:
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result = target_img
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model_path = os.path.join(os.path.abspath(os.path.dirname(__file__)), model)
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@ -182,15 +224,29 @@ def swap_face(
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for face_num in faces_index:
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if len(source_faces_index) > 1 and source_face_idx > 0:
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source_face = get_face_single(source_img, face_index=source_faces_index[source_face_idx])
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source_face, wrong_gender = get_face_single(source_img, face_index=source_faces_index[source_face_idx], gender_source=gender_source)
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source_face_idx += 1
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if source_face is not None:
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target_face = get_face_single(target_img, face_index=face_num)
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if target_face is not None:
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if source_face is not None and wrong_gender == 0:
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target_face, wrong_gender = get_face_single(target_img, face_index=face_num, gender_target=gender_target)
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if target_face is not None and wrong_gender == 0:
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result = face_swapper.get(result, target_face, source_face)
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elif wrong_gender == 1:
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wrong_gender = 0
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if source_face_idx == len(source_faces_index):
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result_image = Image.fromarray(cv2.cvtColor(result, cv2.COLOR_BGR2RGB))
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if upscale_options is not None:
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result_image = upscale_image(result_image, upscale_options)
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return result_image
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else:
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logger.info(f"No target face found for {face_num}")
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elif wrong_gender == 1:
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wrong_gender = 0
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if source_face_idx == len(source_faces_index):
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result_image = Image.fromarray(cv2.cvtColor(result, cv2.COLOR_BGR2RGB))
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if upscale_options is not None:
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result_image = upscale_image(result_image, upscale_options)
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return result_image
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else:
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logger.info(f"No source face found for face number {source_face_idx}.")
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@ -1,5 +1,5 @@
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app_title = "ReActor"
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version_flag = "v0.3.0"
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version_flag = "v0.3.1b"
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from scripts.logger import logger, get_Run, set_Run
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