Merge branch 'development' into create-invokeai-run-directory

CODE_OF_CONDUCT.md

@@ -0,0 +1,128 @@
+# Contributor Covenant Code of Conduct
+
+## Our Pledge
+
+We as members, contributors, and leaders pledge to make participation in our
+community a harassment-free experience for everyone, regardless of age, body
+size, visible or invisible disability, ethnicity, sex characteristics, gender
+identity and expression, level of experience, education, socio-economic status,
+nationality, personal appearance, race, religion, or sexual identity
+and orientation.
+
+We pledge to act and interact in ways that contribute to an open, welcoming,
+diverse, inclusive, and healthy community.
+
+## Our Standards
+
+Examples of behavior that contributes to a positive environment for our
+community include:
+
+* Demonstrating empathy and kindness toward other people
+* Being respectful of differing opinions, viewpoints, and experiences
+* Giving and gracefully accepting constructive feedback
+* Accepting responsibility and apologizing to those affected by our mistakes,
+  and learning from the experience
+* Focusing on what is best not just for us as individuals, but for the
+  overall community
+
+Examples of unacceptable behavior include:
+
+* The use of sexualized language or imagery, and sexual attention or
+  advances of any kind
+* Trolling, insulting or derogatory comments, and personal or political attacks
+* Public or private harassment
+* Publishing others' private information, such as a physical or email
+  address, without their explicit permission
+* Other conduct which could reasonably be considered inappropriate in a
+  professional setting
+
+## Enforcement Responsibilities
+
+Community leaders are responsible for clarifying and enforcing our standards of
+acceptable behavior and will take appropriate and fair corrective action in
+response to any behavior that they deem inappropriate, threatening, offensive,
+or harmful.
+
+Community leaders have the right and responsibility to remove, edit, or reject
+comments, commits, code, wiki edits, issues, and other contributions that are
+not aligned to this Code of Conduct, and will communicate reasons for moderation
+decisions when appropriate.
+
+## Scope
+
+This Code of Conduct applies within all community spaces, and also applies when
+an individual is officially representing the community in public spaces.
+Examples of representing our community include using an official e-mail address,
+posting via an official social media account, or acting as an appointed
+representative at an online or offline event.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior
+may be reported to the community leaders responsible for enforcement
+at https://github.com/invoke-ai/InvokeAI/issues.  All complaints will
+be reviewed and investigated promptly and fairly.
+
+All community leaders are obligated to respect the privacy and security of the
+reporter of any incident.
+
+## Enforcement Guidelines
+
+Community leaders will follow these Community Impact Guidelines in determining
+the consequences for any action they deem in violation of this Code of Conduct:
+
+### 1. Correction
+
+**Community Impact**: Use of inappropriate language or other behavior deemed
+unprofessional or unwelcome in the community.
+
+**Consequence**: A private, written warning from community leaders, providing
+clarity around the nature of the violation and an explanation of why the
+behavior was inappropriate. A public apology may be requested.
+
+### 2. Warning
+
+**Community Impact**: A violation through a single incident or series
+of actions.
+
+**Consequence**: A warning with consequences for continued behavior. No
+interaction with the people involved, including unsolicited interaction with
+those enforcing the Code of Conduct, for a specified period of time. This
+includes avoiding interactions in community spaces as well as external channels
+like social media. Violating these terms may lead to a temporary or
+permanent ban.
+
+### 3. Temporary Ban
+
+**Community Impact**: A serious violation of community standards, including
+sustained inappropriate behavior.
+
+**Consequence**: A temporary ban from any sort of interaction or public
+communication with the community for a specified period of time. No public or
+private interaction with the people involved, including unsolicited interaction
+with those enforcing the Code of Conduct, is allowed during this period.
+Violating these terms may lead to a permanent ban.
+
+### 4. Permanent Ban
+
+**Community Impact**: Demonstrating a pattern of violation of community
+standards, including sustained inappropriate behavior,  harassment of an
+individual, or aggression toward or disparagement of classes of individuals.
+
+**Consequence**: A permanent ban from any sort of public interaction within
+the community.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage],
+version 2.0, available at
+https://www.contributor-covenant.org/version/2/0/code_of_conduct.html.
+
+Community Impact Guidelines were inspired by [Mozilla's code of conduct
+enforcement ladder](https://github.com/mozilla/diversity).
+
+[homepage]: https://www.contributor-covenant.org
+
+For answers to common questions about this code of conduct, see the FAQ at
+https://www.contributor-covenant.org/faq. Translations are available at
+https://www.contributor-covenant.org/translations.

docs/features/EMBIGGEN.md

@@ -85,7 +85,7 @@ increasing size, every tile after the first in a row or column
 effectively only covers an extra `1 - overlap_ratio` on each axis. If
 the input/`--init_img` is same size as a tile, the ideal (for time)
 scaling factors with the default overlap (0.25) are 1.75, 2.5, 3.25,
-4.0 etc..
+4.0, etc.
 
 `-embiggen_tiles <spaced list of tiles>`
 
@@ -100,6 +100,15 @@ Tiles are numbered starting with one, and left-to-right,
 top-to-bottom.  So, if you are generating a 3x3 tiled image, the
 middle row would be `4 5 6`.
 
+`-embiggen_strength <strength>`
+
+Another advanced option if you want to experiment with the strength parameter
+that embiggen uses when it calls Img2Img. Values range from 0.0 to 1.0
+and lower values preserve more of the character of the initial image.
+Values that are too high will result in a completely different end image,
+while values that are too low will result in an image not dissimilar to one
+you would get with ESRGAN upscaling alone. The default value is 0.4.
+
 ### Examples
 
 !!! example ""

environments-and-requirements/environment-lin-aarch64.yml

@@ -33,6 +33,7 @@ dependencies:
       - dependency_injector==4.40.0
       - getpass_asterisk
       - omegaconf==2.1.1
+      - picklescan
       - pyreadline3
       - realesrgan
       - taming-transformers-rom1504

environments-and-requirements/environment-lin-amd.yml

@@ -23,6 +23,7 @@ dependencies:
     - kornia==0.6.0
     - omegaconf==2.2.3
     - opencv-python==4.5.5.64
+    - picklescan
     - pillow==9.2.0
     - pudb==2019.2
     - pyreadline3

environments-and-requirements/environment-lin-cuda.yml

@@ -26,6 +26,7 @@ dependencies:
     - kornia==0.6.0
     - omegaconf==2.2.3
     - opencv-python==4.5.5.64
+    - picklescan
     - pillow==9.2.0
     - pudb==2019.2
     - pyreadline3

environments-and-requirements/environment-mac.yml

@@ -52,6 +52,7 @@ dependencies:
   - transformers=4.23
   - pip:
       - getpass_asterisk
+      - picklescan
       - taming-transformers-rom1504
       - test-tube==0.7.5
       - git+https://github.com/openai/CLIP.git@main#egg=clip

environments-and-requirements/environment-win-cuda.yml

@@ -27,6 +27,7 @@ dependencies:
     - kornia==0.6.0
     - omegaconf==2.2.3
     - opencv-python==4.5.5.64
+    - picklescan
     - pillow==9.2.0
     - pudb==2019.2
     - pyreadline3

environments-and-requirements/requirements-base.txt

@@ -30,6 +30,7 @@ test-tube>=0.7.5
 torch-fidelity
 torchmetrics
 transformers==4.21.*
+picklescan
 git+https://github.com/openai/CLIP.git@main#egg=clip
 git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k-diffusion
 git+https://github.com/invoke-ai/clipseg.git@relaxed-python-requirement#egg=clipseg

installer/requirements.in

@@ -19,6 +19,7 @@ torch-fidelity
 torchvision==0.13.1 ; platform_system == 'Darwin'
 torchvision==0.13.1+cu116 ; platform_system == 'Linux' or platform_system == 'Windows'
 transformers
+picklescan
 https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip
 https://github.com/TencentARC/GFPGAN/archive/2eac2033893ca7f427f4035d80fe95b92649ac56.zip
 https://github.com/invoke-ai/k-diffusion/archive/7f16b2c33411f26b3eae78d10648d625cb0c1095.zip

ldm/generate.py

@@ -295,8 +295,9 @@ class Generate:
             strength         = None,
             init_color       = None,
             # these are specific to embiggen (which also relies on img2img args)
-            embiggen       =    None,
+            embiggen          = None,
-            embiggen_tiles =    None,
+            embiggen_tiles    = None,
+            embiggen_strength = None,
             # these are specific to GFPGAN/ESRGAN
             gfpgan_strength=    0,
             facetool         = None,
@@ -351,6 +352,7 @@ class Generate:
            perlin                          // optional 0-1 value to add a percentage of perlin noise to the initial noise
            embiggen                        // scale factor relative to the size of the --init_img (-I), followed by ESRGAN upscaling strength (0-1.0), followed by minimum amount of overlap between tiles as a decimal ratio (0 - 1.0) or number of pixels
            embiggen_tiles                  // list of tiles by number in order to process and replace onto the image e.g. `0 2 4`
+           embiggen_strength               // strength for embiggen. 0.0 preserves image exactly, 1.0 replaces it completely
 
         To use the step callback, define a function that receives two arguments:
         - Image GPU data
@@ -492,6 +494,7 @@ class Generate:
                 perlin=perlin,
                 embiggen=embiggen,
                 embiggen_tiles=embiggen_tiles,
+                embiggen_strength=embiggen_strength,
                 inpaint_replace=inpaint_replace,
                 mask_blur_radius=mask_blur_radius,
                 safety_checker=checker,
@@ -640,7 +643,7 @@ class Generate:
         elif tool == 'embiggen':
             # fetch the metadata from the image
             generator = self.select_generator(embiggen=True)
-            opt.strength  = 0.40
+            opt.strength = opt.embiggen_strength or 0.40
             print(f'>> Setting img2img strength to {opt.strength} for happy embiggening')
             generator.generate(
                 prompt,
@@ -656,6 +659,7 @@ class Generate:
                 height      = opt.height,
                 embiggen    = opt.embiggen,
                 embiggen_tiles = opt.embiggen_tiles,
+                embiggen_strength = opt.embiggen_strength,
                 image_callback = callback,
             )
         elif tool == 'outpaint':

ldm/invoke/args.py

@@ -287,6 +287,8 @@ class Args(object):
             switches.append(f'--embiggen {" ".join([str(u) for u in a["embiggen"]])}')
         if a['embiggen_tiles']:
             switches.append(f'--embiggen_tiles {" ".join([str(u) for u in a["embiggen_tiles"]])}')
+        if a['embiggen_strength']:
+            switches.append(f'--embiggen_strength {a["embiggen_strength"]}')
 
         # outpainting parameters
         if a['out_direction']:
@@ -921,6 +923,13 @@ class Args(object):
             help='For embiggen, provide list of tiles to process and replace onto the image e.g. `1 3 5`.',
             default=None,
         )
+        postprocessing_group.add_argument(
+            '--embiggen_strength',
+            '-embiggen_strength',
+            type=float,
+            help='The strength of the embiggen img2img step, defaults to 0.4',
+            default=0.4,
+        )
         special_effects_group.add_argument(
             '--seamless',
             action='store_true',

ldm/invoke/model_cache.py

@@ -12,14 +12,15 @@ import time
 import gc
 import hashlib
 import psutil
+import sys
 import transformers
 import traceback
 import os
-from sys import getrefcount
 from omegaconf import OmegaConf
 from omegaconf.errors import ConfigAttributeError
 from ldm.util import instantiate_from_config
 from ldm.invoke.globals import Globals
+from picklescan.scanner import scan_file_path
 
 DEFAULT_MAX_MODELS=2
 
@@ -203,6 +204,8 @@ class ModelCache(object):
 
         if not os.path.isabs(weights):
             weights = os.path.normpath(os.path.join(Globals.root,weights))
+        # scan model
+        self._scan_model(model_name, weights)
 
         print(f'>> Loading {model_name} from {weights}')
 
@@ -283,6 +286,30 @@ class ModelCache(object):
         gc.collect()
         if self._has_cuda():
             torch.cuda.empty_cache()
+    
+    def _scan_model(self, model_name, checkpoint):
+        # scan model
+        print(f'>> Scanning Model: {model_name}')
+        scan_result = scan_file_path(checkpoint)
+        if scan_result.infected_files != 0:
+            if scan_result.infected_files == 1:
+                print(f'\n### Issues Found In Model: {scan_result.issues_count}')
+                print('### WARNING: The model you are trying to load seems to be infected.')
+                print('### For your safety, InvokeAI will not load this model.')
+                print('### Please use checkpoints from trusted sources.')
+                print("### Exiting InvokeAI")
+                sys.exit()
+            else:
+                print('\n### WARNING: InvokeAI was unable to scan the model you are using.')
+                from ldm.util import ask_user
+                model_safe_check_fail = ask_user('Do you want to to continue loading the model?', ['y', 'n'])
+                if model_safe_check_fail.lower() == 'y':
+                    pass
+                else:
+                    print("### Exiting InvokeAI")
+                    sys.exit()
+        else:
+            print('>> Model Scanned. OK!!')
 
     def _make_cache_room(self):
         num_loaded_models = len(self.models)

ldm/invoke/server.py

@@ -30,6 +30,7 @@ def build_opt(post_data, seed, gfpgan_model_exists):
     # however, this code is here against that eventuality
     setattr(opt, 'embiggen', None)
     setattr(opt, 'embiggen_tiles', None)
+    setattr(opt, 'embiggen_strength', None)
 
     setattr(opt, 'facetool_strength', float(post_data['facetool_strength']) if gfpgan_model_exists else 0)
     setattr(opt, 'upscale', [int(post_data['upscale_level']), float(post_data['upscale_strength'])] if post_data['upscale_level'] != '' else None)

ldm/util.py

@@ -235,3 +235,12 @@ def rand_perlin_2d(shape, res, device, fade = lambda t: 6*t**5 - 15*t**4 + 10*t*
     n11 = dot(tile_grads([1, None], [1, None]), [-1,-1]).to(device)
     t = fade(grid[:shape[0], :shape[1]])
     return math.sqrt(2) * torch.lerp(torch.lerp(n00, n10, t[..., 0]), torch.lerp(n01, n11, t[..., 0]), t[..., 1]).to(device)
+
+def ask_user(question: str, answers: list):
+    from itertools import chain, repeat
+    user_prompt = f'\n>> {question} {answers}: '
+    invalid_answer_msg = 'Invalid answer. Please try again.'
+    pose_question = chain([user_prompt], repeat('\n'.join([invalid_answer_msg, user_prompt])))
+    user_answers = map(input, pose_question)
+    valid_response = next(filter(answers.__contains__, user_answers))
+    return valid_response