Extras tab script
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w-e-w
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cec1d41dc7
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@ -424,3 +424,226 @@ class FaceSwapScript(scripts.Script):
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# f.writelines(output)
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except:
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logger.error("Cannot create a result image")
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class FaceSwapScriptExtras(scripts_postprocessing.ScriptPostprocessing):
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name = 'ReActor'
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order = 20000
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def ui(self):
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with gr.Accordion(f"{app_title}", open=False):
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with gr.Tab("Main"):
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with gr.Column():
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img = gr.Image(type="pil")
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enable = gr.Checkbox(False, label="Enable", info=f"The Fast and Simple FaceSwap Extension - {version_flag}")
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gr.Markdown("<br>")
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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); 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("<br>")
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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(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("<br>")
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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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choices=["None"] + [x.name() for x in shared.face_restorers],
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value=shared.face_restorers[0].name(),
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type="value",
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)
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with gr.Column():
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face_restorer_visibility = gr.Slider(
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0, 1, 1, step=0.1, label="Restore Face Visibility"
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)
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codeformer_weight = gr.Slider(
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0, 1, 0.5, step=0.1, label="CodeFormer Weight", info="0 = maximum effect, 1 = minimum effect"
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)
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gr.Markdown("<br>")
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with gr.Tab("Upscale"):
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restore_first = gr.Checkbox(
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True,
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label="1. Restore Face -> 2. Upscale (-Uncheck- if you want vice versa)",
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info="Postprocessing Order"
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)
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upscaler_name = gr.Dropdown(
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choices=[upscaler.name for upscaler in shared.sd_upscalers],
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label="Upscaler",
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value="None",
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info="Won't scale if you choose -Swap in Source- via img2img, only 1x-postprocessing will affect (texturing, denoising, restyling etc.)"
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)
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gr.Markdown("<br>")
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with gr.Row():
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upscaler_scale = gr.Slider(1, 8, 1, step=0.1, label="Scale by")
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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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with gr.Tab("Settings"):
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models = get_models()
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with gr.Row():
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if len(models) == 0:
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logger.warning(
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"You should at least have one model in models directory, please read the doc here : https://github.com/Gourieff/sd-webui-reactor/"
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)
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model = gr.Dropdown(
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choices=models,
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label="Model not found, please download one and reload WebUI",
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)
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else:
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model = gr.Dropdown(
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choices=models, label="Model", value=models[0]
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)
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console_logging_level = gr.Radio(
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["No log", "Minimum", "Default"],
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value="Minimum",
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label="Console Log Level",
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type="index",
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)
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gr.Markdown("<br>")
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with gr.Row():
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source_hash_check = gr.Checkbox(
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True,
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label="Source Image Hash Check",
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info="Recommended to keep it ON. Processing is faster when Source Image is the same."
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)
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target_hash_check = gr.Checkbox(
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False,
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label="Target Image Hash Check",
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info="Affects if you use img2img with only 'Swap in source image' option."
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)
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args = {
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'img': img,
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'enable': enable,
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'source_faces_index': source_faces_index,
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'faces_index': faces_index,
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'model': model,
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'face_restorer_name': face_restorer_name,
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'face_restorer_visibility': face_restorer_visibility,
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'restore_first': restore_first,
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'upscaler_name': upscaler_name,
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'upscaler_scale': upscaler_scale,
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'upscaler_visibility': upscaler_visibility,
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'console_logging_level': console_logging_level,
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'gender_source': gender_source,
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'gender_target': gender_target,
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'codeformer_weight': codeformer_weight,
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'source_hash_check': source_hash_check,
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'target_hash_check': target_hash_check,
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}
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return args
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@property
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def upscaler(self) -> UpscalerData:
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for upscaler in shared.sd_upscalers:
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if upscaler.name == self.upscaler_name:
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return upscaler
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return None
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@property
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def face_restorer(self) -> FaceRestoration:
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for face_restorer in shared.face_restorers:
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if face_restorer.name() == self.face_restorer_name:
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return face_restorer
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return None
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@property
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def enhancement_options(self) -> EnhancementOptions:
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return EnhancementOptions(
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do_restore_first=self.restore_first,
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scale=self.upscaler_scale,
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upscaler=self.upscaler,
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face_restorer=self.face_restorer,
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upscale_visibility=self.upscaler_visibility,
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restorer_visibility=self.face_restorer_visibility,
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codeformer_weight=self.codeformer_weight,
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)
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def process(self, pp: scripts_postprocessing.PostprocessedImage, **args):
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if args['enable']:
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reset_messaged()
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if check_process_halt():
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return
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global MODELS_PATH
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self.source = args['img']
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self.face_restorer_name = args['face_restorer_name']
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self.upscaler_scale = args['upscaler_scale']
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self.upscaler_visibility = args['upscaler_visibility']
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self.face_restorer_visibility = args['face_restorer_visibility']
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self.restore_first = args['restore_first']
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self.upscaler_name = args['upscaler_name']
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self.model = os.path.join(MODELS_PATH, args['model'])
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self.console_logging_level = args['console_logging_level']
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self.gender_source = args['gender_source']
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self.gender_target = args['gender_target']
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self.codeformer_weight = args['codeformer_weight']
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self.source_hash_check = args['source_hash_check']
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self.target_hash_check = args['target_hash_check']
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if self.gender_source is None or self.gender_source == "No":
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self.gender_source = 0
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if self.gender_target is None or self.gender_target == "No":
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self.gender_target = 0
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self.source_faces_index = [
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int(x) for x in args['source_faces_index'].strip(",").split(",") if x.isnumeric()
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]
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self.faces_index = [
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int(x) for x in args['faces_index'].strip(",").split(",") if x.isnumeric()
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]
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if len(self.source_faces_index) == 0:
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self.source_faces_index = [0]
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if len(self.faces_index) == 0:
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self.faces_index = [0]
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if self.source_hash_check is None:
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self.source_hash_check = True
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if self.target_hash_check is None:
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self.target_hash_check = False
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current_job_number = shared.state.job_no + 1
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job_count = shared.state.job_count
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if current_job_number == job_count:
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reset_messaged()
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if self.source is not None:
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logger.status("Working: source face index %s, target face index %s", self.source_faces_index, self.faces_index)
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image: Image.Image = pp.image
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result, output, swapped = swap_face(
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self.source,
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image,
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source_faces_index=self.source_faces_index,
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faces_index=self.faces_index,
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model=self.model,
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enhancement_options=self.enhancement_options,
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gender_source=self.gender_source,
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gender_target=self.gender_target,
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source_hash_check=self.source_hash_check,
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target_hash_check=self.target_hash_check,
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)
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try:
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pp.info["ReActor"] = True
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pp.image = result
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except Exception:
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logger.error("Cannot create a result image")
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else:
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logger.error("Please provide a source face")
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