remove NSFW filter and its dependency; if you still want it, find it in the extensions section

6 files changed, 23 insertions, 49 deletions

diff --git a/modules/processing.py b/modules/processing.py
index 81400d14..056c9322 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -13,7 +13,7 @@ from skimage import exposure
 from typing import Any, Dict, List, Optional

 

 import modules.sd_hijack

-from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste

+from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, script_callbacks

 from modules.sd_hijack import model_hijack

 from modules.shared import opts, cmd_opts, state

 import modules.shared as shared

@@ -571,9 +571,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
 

             devices.torch_gc()

 

-            if opts.filter_nsfw:

-                import modules.safety as safety

-                x_samples_ddim = modules.safety.censor_batch(x_samples_ddim)

+            if p.scripts is not None:

+                p.scripts.postprocess_batch(p, x_samples_ddim, batch_number=n)

 

             for i, x_sample in enumerate(x_samples_ddim):

                 x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)

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

diff --git a/modules/scripts.py b/modules/scripts.py
index b934d881..23ca195d 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -88,6 +88,17 @@ class Script:
 

         pass

 

+    def postprocess_batch(self, p, *args, **kwargs):

+        """

+        Same as process_batch(), but called for every batch after it has been generated.

+

+        **kwargs will have same items as process_batch, and also:

+          - batch_number - index of current batch, from 0 to number of batches-1

+          - images - torch tensor with all generated images, with values ranging from 0 to 1;

+        """

+

+        pass

+

     def postprocess(self, p, processed, *args):

         """

         This function is called after processing ends for AlwaysVisible scripts.

@@ -347,6 +358,15 @@ class ScriptRunner:
                 print(f"Error running postprocess: {script.filename}", file=sys.stderr)

                 print(traceback.format_exc(), file=sys.stderr)

 

+    def postprocess_batch(self, p, images, **kwargs):

+        for script in self.alwayson_scripts:

+            try:

+                script_args = p.script_args[script.args_from:script.args_to]

+                script.postprocess_batch(p, *script_args, images=images, **kwargs)

+            except Exception:

+                print(f"Error running postprocess_batch: {script.filename}", file=sys.stderr)

+                print(traceback.format_exc(), file=sys.stderr)

+

     def before_component(self, component, **kwargs):

         for script in self.scripts:

             try:

diff --git a/modules/shared.py b/modules/shared.py
index 44922c91..272267c1 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -367,7 +367,6 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."),

     "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),

     "comma_padding_backtrack": OptionInfo(20, "Increase coherency by padding from the last comma within n tokens when using more than 75 tokens", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1 }),

-    "filter_nsfw": OptionInfo(False, "Filter NSFW content"),

     'CLIP_stop_at_last_layers': OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}),

     "random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),

 }))

diff --git a/requirements.txt b/requirements.txt
index 05818aa6..678acb4d 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,6 +1,5 @@
 accelerate

 basicsr

-diffusers

 fairscale==0.4.4

 fonts

 font-roboto

diff --git a/requirements_versions.txt b/requirements_versions.txt
index 035fa82f..185cd066 100644
--- a/requirements_versions.txt
+++ b/requirements_versions.txt
@@ -1,5 +1,4 @@
 transformers==4.19.2

-diffusers==0.3.0

 accelerate==0.12.0

 basicsr==1.4.2

 gfpgan==1.3.8