diff options
author | unknown <mcgpapu@gmail.com> | 2022-12-12 09:12:26 -0600 |
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committer | unknown <mcgpapu@gmail.com> | 2022-12-12 09:12:26 -0600 |
commit | d6fdfde9d70f1b86b696240fb0a0c8f2a4d024f6 (patch) | |
tree | 991a5b9c6c5bdd15bb9ff18bb68bd7c0df87bbfc /modules/safety.py | |
parent | 4005cd66e08d262b289d8d4a31fd425f260bcd11 (diff) | |
parent | 685f9631b56ff8bd43bce24ff5ce0f9a0e9af490 (diff) |
Merge branch 'master' of github.com:AUTOMATIC1111/stable-diffusion-webui
Diffstat (limited to 'modules/safety.py')
-rw-r--r-- | modules/safety.py | 42 |
1 files changed, 0 insertions, 42 deletions
diff --git a/modules/safety.py b/modules/safety.py deleted file mode 100644 index cff4b278..00000000 --- a/modules/safety.py +++ /dev/null @@ -1,42 +0,0 @@ -import torch
-from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
-from transformers import AutoFeatureExtractor
-from PIL import Image
-
-import modules.shared as shared
-
-safety_model_id = "CompVis/stable-diffusion-safety-checker"
-safety_feature_extractor = None
-safety_checker = None
-
-def numpy_to_pil(images):
- """
- Convert a numpy image or a batch of images to a PIL image.
- """
- if images.ndim == 3:
- images = images[None, ...]
- images = (images * 255).round().astype("uint8")
- pil_images = [Image.fromarray(image) for image in images]
-
- return pil_images
-
-# check and replace nsfw content
-def check_safety(x_image):
- global safety_feature_extractor, safety_checker
-
- if safety_feature_extractor is None:
- safety_feature_extractor = AutoFeatureExtractor.from_pretrained(safety_model_id)
- safety_checker = StableDiffusionSafetyChecker.from_pretrained(safety_model_id)
-
- safety_checker_input = safety_feature_extractor(numpy_to_pil(x_image), return_tensors="pt")
- x_checked_image, has_nsfw_concept = safety_checker(images=x_image, clip_input=safety_checker_input.pixel_values)
-
- return x_checked_image, has_nsfw_concept
-
-
-def censor_batch(x):
- x_samples_ddim_numpy = x.cpu().permute(0, 2, 3, 1).numpy()
- x_checked_image, has_nsfw_concept = check_safety(x_samples_ddim_numpy)
- x = torch.from_numpy(x_checked_image).permute(0, 3, 1, 2)
-
- return x
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