AP123 multimodalart HF staff commited on
Commit
e266395
1 Parent(s): d1c0879

Native safety checker (#918)

Browse files

- Native safety checker (07822f88cb601e5baa8e97c166607b8af5a7e518)


Co-authored-by: Apolinário from multimodal AI art <multimodalart@users.noreply.huggingface.co>

Files changed (1) hide show
  1. app.py +12 -12
app.py CHANGED
@@ -23,7 +23,7 @@ import user_history
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  from illusion_style import css
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  import os
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  from transformers import CLIPImageProcessor
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- from safety_checker import StableDiffusionSafetyChecker #-> commenting this out to provoke runtime error
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  BASE_MODEL = "SG161222/Realistic_Vision_V5.1_noVAE"
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@@ -49,16 +49,16 @@ main_pipe = StableDiffusionControlNetPipeline.from_pretrained(
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  ).to("cuda")
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  # Function to check NSFW images
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- def check_nsfw_images(images: list[Image.Image]) -> tuple[list[Image.Image], list[bool]]:
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- if SAFETY_CHECKER_ENABLED:
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- safety_checker_input = feature_extractor(images, return_tensors="pt").to("cuda")
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- has_nsfw_concepts = safety_checker(
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- images=[images],
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- clip_input=safety_checker_input.pixel_values.to("cuda")
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- )
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- return images, has_nsfw_concepts
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- else:
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- return images, [False] * len(images)
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  #main_pipe.unet = torch.compile(main_pipe.unet, mode="reduce-overhead", fullgraph=True)
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  #main_pipe.unet.to(memory_format=torch.channels_last)
@@ -284,4 +284,4 @@ with gr.Blocks(css=css) as app_with_history:
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  app_with_history.queue(max_size=20,api_open=False )
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  if __name__ == "__main__":
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- app_with_history.launch(max_threads=400)
 
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  from illusion_style import css
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  import os
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  from transformers import CLIPImageProcessor
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+ from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
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  BASE_MODEL = "SG161222/Realistic_Vision_V5.1_noVAE"
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  ).to("cuda")
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  # Function to check NSFW images
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+ #def check_nsfw_images(images: list[Image.Image]) -> tuple[list[Image.Image], list[bool]]:
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+ # if SAFETY_CHECKER_ENABLED:
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+ # safety_checker_input = feature_extractor(images, return_tensors="pt").to("cuda")
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+ # has_nsfw_concepts = safety_checker(
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+ # images=[images],
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+ # clip_input=safety_checker_input.pixel_values.to("cuda")
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+ # )
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+ # return images, has_nsfw_concepts
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+ # else:
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+ # return images, [False] * len(images)
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  #main_pipe.unet = torch.compile(main_pipe.unet, mode="reduce-overhead", fullgraph=True)
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  #main_pipe.unet.to(memory_format=torch.channels_last)
 
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  app_with_history.queue(max_size=20,api_open=False )
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  if __name__ == "__main__":
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+ app_with_history.launch(max_threads=400)