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import os |
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import gradio as gr |
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import modules.scripts as scripts |
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from modules.upscaler import Upscaler, UpscalerData |
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from modules import scripts, shared, images, scripts_postprocessing |
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from modules.processing import ( |
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StableDiffusionProcessing, |
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StableDiffusionProcessingImg2Img, |
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) |
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from modules.shared import cmd_opts, opts, state |
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from PIL import Image |
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import glob |
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from modules.face_restoration import FaceRestoration |
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from scripts.roop_logging import logger |
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from scripts.swapper import UpscaleOptions, swap_face, ImageResult |
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from scripts.roop_version import version_flag |
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import os |
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def get_models(): |
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models_path = os.path.join(scripts.basedir(), "models" + os.path.sep + "roop" + os.path.sep + "*") |
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models = glob.glob(models_path) |
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models = [x for x in models if x.endswith(".onnx") or x.endswith(".pth")] |
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return models |
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class FaceSwapScript(scripts.Script): |
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def title(self): |
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return f"roop" |
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def show(self, is_img2img): |
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return scripts.AlwaysVisible |
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def ui(self, is_img2img): |
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with gr.Accordion(f"roop {version_flag}", 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, placeholder="enable", label="Enable") |
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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), start from 0", |
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label="Comma separated face number(s)", |
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) |
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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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face_restorer_visibility = gr.Slider( |
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0, 1, 1, step=0.1, label="Restore visibility" |
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) |
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upscaler_name = gr.inputs.Dropdown( |
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choices=[upscaler.name for upscaler in shared.sd_upscalers], |
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label="Upscaler", |
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) |
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upscaler_scale = gr.Slider(1, 8, 1, step=0.1, label="Upscaler scale") |
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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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models = get_models() |
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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/s0md3v/sd-webui-roop/" |
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) |
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model = gr.inputs.Dropdown( |
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choices=models, |
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label="Model not found, please download one and reload automatic 1111", |
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) |
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else: |
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model = gr.inputs.Dropdown( |
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choices=models, label="Model", default=models[0] |
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) |
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swap_in_source = gr.Checkbox( |
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False, |
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placeholder="Swap face in source image", |
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label="Swap in source image", |
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visible=is_img2img, |
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) |
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swap_in_generated = gr.Checkbox( |
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True, |
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placeholder="Swap face in generated image", |
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label="Swap in generated image", |
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visible=is_img2img, |
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) |
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return [ |
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img, |
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enable, |
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faces_index, |
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model, |
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face_restorer_name, |
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face_restorer_visibility, |
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upscaler_name, |
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upscaler_scale, |
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upscaler_visibility, |
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swap_in_source, |
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swap_in_generated, |
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] |
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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 upscale_options(self) -> UpscaleOptions: |
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return UpscaleOptions( |
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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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) |
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def process( |
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self, |
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p: StableDiffusionProcessing, |
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img, |
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enable, |
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faces_index, |
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model, |
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face_restorer_name, |
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face_restorer_visibility, |
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upscaler_name, |
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upscaler_scale, |
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upscaler_visibility, |
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swap_in_source, |
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swap_in_generated, |
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): |
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self.source = img |
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self.face_restorer_name = face_restorer_name |
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self.upscaler_scale = upscaler_scale |
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self.upscaler_visibility = upscaler_visibility |
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self.face_restorer_visibility = face_restorer_visibility |
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self.enable = enable |
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self.upscaler_name = upscaler_name |
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self.swap_in_generated = swap_in_generated |
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self.model = model |
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self.faces_index = { |
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int(x) for x in faces_index.strip(",").split(",") if x.isnumeric() |
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} |
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if len(self.faces_index) == 0: |
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self.faces_index = {0} |
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if self.enable: |
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if self.source is not None: |
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if isinstance(p, StableDiffusionProcessingImg2Img) and swap_in_source: |
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logger.info(f"roop enabled, face index %s", self.faces_index) |
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for i in range(len(p.init_images)): |
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logger.info(f"Swap in source %s", i) |
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result = swap_face( |
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self.source, |
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p.init_images[i], |
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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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) |
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p.init_images[i] = result.image() |
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else: |
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logger.error(f"Please provide a source face") |
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def postprocess_batch(self, *args, **kwargs): |
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if self.enable: |
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return images |
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def postprocess_image(self, p, script_pp: scripts.PostprocessImageArgs, *args): |
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if self.enable and self.swap_in_generated: |
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if self.source is not None: |
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image: Image.Image = script_pp.image |
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result: ImageResult = swap_face( |
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self.source, |
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image, |
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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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) |
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pp = scripts_postprocessing.PostprocessedImage(result.image()) |
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pp.info = {} |
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p.extra_generation_params.update(pp.info) |
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script_pp.image = pp.image |
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