Configure the NSFW checker at install time with default on

docs/features/NSFW.md

@@ -0,0 +1,89 @@
+---
+title: The NSFW Checker
+---
+
+# :material-image-off: NSFW Checker
+
+## The NSFW ("Safety") Checker
+
+The Stable Diffusion image generation models will produce sexual
+imagery if deliberately prompted, and will occasionally produce such
+images when this is not intended. Such images are colloquially known
+as "Not Safe for Work" (NSFW). This behavior is due to the nature of
+the training set that Stable Diffusion was trained on, which culled
+millions of "aesthetic" images from the Internet.
+
+You may not wish to be exposed to these images, and in some
+jurisdictions it may be illegal to publicly distribute such imagery,
+including mounting a publicly-available server that provides
+unfiltered images to the public. Furthermore, the [Stable Diffusion
+weights
+License](https://github.com/invoke-ai/InvokeAI/blob/main/LICENSE-ModelWeights.txt)
+forbids the model from being used to "exploit any of the
+vulnerabilities of a specific group of persons."
+
+For these reasons Stable Diffusion offers a "safety checker," a
+machine learning model trained to recognize potentially disturbing
+imagery. When a potentially NSFW image is detected, the checker will
+blur the image and paste a warning icon on top. The checker can be
+turned on and off on the command line using `--nsfw_checker` and
+`--no-nsfw_checker`.
+
+At installation time, InvokeAI will ask whether the checker should be
+activated by default (neither argument given on the command line). The
+response is stored in the InvokeAI initialization file (usually
+`.invokeai` in your home directory). You can change the default at any
+time by opening this file in a text editor and commenting or
+uncommenting the line `--nsfw_checker`.
+
+## Caveats
+
+There are a number of caveats that you need to be aware of.
+
+### Accuracy
+
+The checker is [not perfect](https://arxiv.org/abs/2210.04610).It will
+occasionally flag innocuous images (false positives), and will
+frequently miss violent and gory imagery (false negatives). It rarely
+fails to flag sexual imagery, but this has been known to happen. For
+these reasons, the InvokeAI team prefers to refer to the software as a
+"NSFW Checker" rather than "safety checker."
+
+### Memory Usage and Performance
+
+The NSFW checker consumes an additional 1.2G of GPU VRAM on top of the
+3.4G of VRAM used by Stable Diffusion v1.5 (this is with
+half-precision arithmetic). This means that the checker will not run
+successfully on GPU cards with less than 6GB VRAM, and will reduce the
+size of the images that you can produce.
+
+The checker also introduces a slight performance penalty. Images will
+take ~1 second longer to generate when the checker is
+activated. Generally this is not noticeable.
+
+### Intermediate Images in the Web UI
+
+The checker only operates on the final image produced by the Stable
+Diffusion algorithm. If you are using the Web UI and have enabled the
+display of intermediate images, you will briefly be exposed to a
+low-resolution (mosaicized) version of the final image before it is
+flagged by the checker and replaced by a fully blurred version. You
+are encouraged to turn **off** intermediate image rendering when you
+are using the checker. Future versions of InvokeAI will apply
+additional blurring to intermediate images when the checker is active.
+
+### Watermarking
+
+InvokeAI does not apply any sort of watermark to images it
+generates. However, it does write metadata into the PNG data area,
+including the prompt used to generate the image and relevant parameter
+settings. These fields can be examined using the `sd-metadata.py`
+script that comes with the InvokeAI package.
+
+Note that several other Stable Diffusion distributions offer
+wavelet-based "invisible" watermarking. We have experimented with the
+library used to generate these watermarks and have reached the
+conclusion that while the watermarking library may be adding
+watermarks to PNG images, the currently available version is unable to
+retrieve them successfully. If and when a functioning version of the
+library becomes available, we will offer this feature as well.

ldm/invoke/args.py

@@ -468,7 +468,7 @@ def _create_arg_parser(self):
             action=argparse.BooleanOptionalAction,
             dest='safety_checker',
             default=False,
-            help='Check for and blur potentially NSFW images.',
+            help='Check for and blur potentially NSFW images. Use --no-nsfw_checker to disable.',
         )
         model_group.add_argument(
             '--patchmatch',

ldm/invoke/generator/base.py

@@ -6,6 +6,7 @@
 import numpy as  np
 import random
 import os
+import os.path as osp
 import traceback
 from tqdm import tqdm, trange
 from PIL import Image, ImageFilter, ImageChops
@@ -32,6 +33,7 @@ def __init__(self, model, precision):
         self.with_variations = []
         self.use_mps_noise = False
         self.free_gpu_mem = None
+        self.caution_img = None
 
     # this is going to be overridden in img2img.py, txt2img.py and inpaint.py
     def get_make_image(self,prompt,**kwargs):
@@ -290,13 +292,29 @@ def safety_check(self,image:Image.Image):
     def blur(self,input):
         blurry = input.filter(filter=ImageFilter.GaussianBlur(radius=32))
         try:
-            caution = Image.open(CAUTION_IMG)
-            caution = caution.resize((caution.width // 2, caution.height //2))
-            blurry.paste(caution,(0,0),caution)
+            caution = self.get_caution_img()
+            if caution:
+                blurry.paste(caution,(0,0),caution)
         except FileNotFoundError:
             pass
         return blurry
 
+    def get_caution_img(self):
+        if self.caution_img:
+            return self.caution_img
+        # Find the caution image. If we are installed in the package directory it will
+        # be six levels up. If we are in the repo directory it will be three levels up.
+        for dots in ('../../..','../../../../../..'):
+            caution_path = osp.join(osp.dirname(__file__),dots,CAUTION_IMG)
+            if osp.exists(caution_path):
+                path = caution_path
+                break
+        if not path:
+            return
+        caution = Image.open(path)
+        self.caution_img = caution.resize((caution.width // 2, caution.height //2))
+        return self.caution_img
+
     # this is a handy routine for debugging use. Given a generated sample,
     # convert it into a PNG image and store it at the indicated path
     def save_sample(self, sample, filepath):

scripts/configure_invokeai.py

@@ -70,10 +70,10 @@ def postscript():
 Command-line version:
    python scripts/invoke.py
 
-Remember to activate that 'invokeai' environment before running invoke.py.
-
-Or, if you used one of the automated installers, execute "invoke.sh" (Linux/Mac) 
-or "invoke.bat" (Windows) to start the script.
+If you installed manually, remember to activate the 'invokeai'
+environment before running invoke.py. If you installed using the
+automated installation script, execute "invoke.sh" (Linux/Mac) or
+"invoke.bat" (Windows) to start InvokeAI.
 
 Have fun!
 '''
@@ -243,10 +243,10 @@ def download_weight_datasets(models:dict, access_token:str):
     for mod in models.keys():
         repo_id = Datasets[mod]['repo_id']
         filename = Datasets[mod]['file']
-        print(os.path.join(Globals.root,Model_dir,Weights_dir), file=sys.stderr)
+        dest = os.path.join(Globals.root,Model_dir,Weights_dir)
         success = hf_download_with_resume(
             repo_id=repo_id,
-            model_dir=os.path.join(Globals.root,Model_dir,Weights_dir),
+            model_dir=dest,
             model_name=filename,
             access_token=access_token
         )
@@ -494,12 +494,12 @@ def download_clipseg():
 
 #-------------------------------------
 def download_safety_checker():
-    print('Installing safety model for NSFW content detection...',file=sys.stderr)
+    print('Installing model for NSFW content detection...',file=sys.stderr)
     try:
         from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
         from transformers import AutoFeatureExtractor
     except ModuleNotFoundError:
-        print('Error installing safety checker model:')
+        print('Error installing NSFW checker model:')
         print(traceback.format_exc())
         return
     safety_model_id = "CompVis/stable-diffusion-safety-checker"
@@ -520,6 +520,7 @@ def download_weights(opt:dict):
             return
         else:
             print('** Cannot download models because no Hugging Face access token could be found. Please re-run without --yes')
+            return
     else:
         choice = user_wants_to_download_weights()
 
@@ -584,7 +585,7 @@ def select_outputs(root:str,yes_to_all:bool=False):
 
 #-------------------------------------
 def initialize_rootdir(root:str,yes_to_all:bool=False):
-    assert os.path.exists('./configs'),'Run this script from within the top level of the InvokeAI source code directory, "InvokeAI"'
+    assert os.path.exists('./configs'),'Run this script from within the InvokeAI source code directory, "InvokeAI" or the runtime directory "invokeai".'
 
     print(f'** INITIALIZING INVOKEAI RUNTIME DIRECTORY **')
     root_selected = False
@@ -603,19 +604,50 @@ def initialize_rootdir(root:str,yes_to_all:bool=False):
     print(f'\nYou may change the chosen directories at any time by editing the --root and --outdir options in "{Globals.initfile}",')
     print(f'You may also change the runtime directory by setting the environment variable INVOKEAI_ROOT.\n')
 
+    enable_safety_checker = True
+    default_sampler = 'k_heun'
+    default_steps = '20'  # deliberately a string - see test below
+
+    sampler_choices =['ddim','k_dpm_2_a','k_dpm_2','k_euler_a','k_euler','k_heun','k_lms','plms']
+
+    if not yes_to_all:
+        print('The NSFW (not safe for work) checker blurs out images that potentially contain sexual imagery.')
+        print('It can be selectively enabled at run time with --nsfw_checker, and disabled with --no-nsfw_checker.')
+        print('The following option will set whether the checker is enabled by default. Like other options, you can')
+        print(f'change this setting later by editing the file {Globals.initfile}.')
+        enable_safety_checker = yes_or_no('Enable the NSFW checker by default?',enable_safety_checker)
+
+        print('\nThe next choice selects the sampler to use by default. Samplers have different speed/performance')
+        print('tradeoffs. If you are not sure what to select, accept the default.')
+        sampler = None
+        while sampler not in sampler_choices:
+            sampler = input(f'Default sampler to use? ({", ".join(sampler_choices)}) [{default_sampler}]:') or default_sampler
+
+        print('\nThe number of denoising steps affects both the speed and quality of the images generated.')
+        print('Higher steps often (but not always) increases the quality of the image, but increases image')
+        print('generation time. This can be changed at run time. Accept the default if you are unsure.')
+        steps = ''
+        while not steps.isnumeric():
+            steps = input(f'Default number of steps to use during generation? [{default_steps}]:') or default_steps
+    else:
+        sampler = default_sampler
+        steps = default_steps
+
+    safety_checker = '--nsfw_checker' if enable_safety_checker else '--no-nsfw_checker'
+
     for name in ('models','configs','embeddings'):
         os.makedirs(os.path.join(root,name), exist_ok=True)
     for src in (['configs']):
         dest = os.path.join(root,src)
         if not os.path.samefile(src,dest):
             shutil.copytree(src,dest,dirs_exist_ok=True)
-    os.makedirs(outputs, exist_ok=True)
+        os.makedirs(outputs, exist_ok=True)
 
     init_file = os.path.expanduser(Globals.initfile)
-    if not os.path.exists(init_file):
-        print(f'Creating the initialization file at "{init_file}".\n')
-        with open(init_file,'w') as f:
-            f.write(f'''# InvokeAI initialization file
+
+    print(f'Creating the initialization file at "{init_file}".\n')
+    with open(init_file,'w') as f:
+        f.write(f'''# InvokeAI initialization file
 # This is the InvokeAI initialization file, which contains command-line default values.
 # Feel free to edit. If anything goes wrong, you can re-initialize this file by deleting
 # or renaming it and then running configure_invokeai.py again.
@@ -626,23 +658,18 @@ def initialize_rootdir(root:str,yes_to_all:bool=False):
 # the --outdir option controls the default location of image files.
 --outdir="{outputs}"
 
+# generation arguments
+{safety_checker}
+--sampler={sampler}
+--steps={steps}
+
 # You may place other  frequently-used startup commands here, one or more per line.
 # Examples:
 # --web --host=0.0.0.0
 # --steps=20
 # -Ak_euler_a -C10.0
 #
-'''
-            )
-    else:
-        print(f'Updating the initialization file at "{init_file}".\n')
-        with open(init_file,'r') as infile, open(f'{init_file}.tmp','w') as outfile:
-            for line in infile.readlines():
-                if not line.startswith('--root') and not line.startswith('--outdir'):
-                    outfile.write(line)
-            outfile.write(f'--root="{root}"\n')
-            outfile.write(f'--outdir="{outputs}"\n')
-        os.replace(f'{init_file}.tmp',init_file)
+''')
 
 #-------------------------------------
 class ProgressBar():

setup.py

@@ -81,6 +81,7 @@ def list_files(directory):
                'scripts/preload_models.py', 'scripts/images2prompt.py','scripts/merge_embeddings.py'
     ],
     data_files=[('frontend/dist',list_files('frontend/dist')),
-                ('frontend/dist/assets',list_files('frontend/dist/assets'))
+                ('frontend/dist/assets',list_files('frontend/dist/assets')),
+                ('assets',['assets/caution.png']),
     ],
 )