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Fix various typos

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This commit is contained in:
Jim Hays 2022-12-14 21:01:32 -05:00
parent 685f9631b5
commit c0355caefe
16 changed files with 68 additions and 68 deletions
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2
README.md
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@ -83,7 +83,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
- Estimated completion time in progress bar
- API
- Support for dedicated [inpainting model](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion) by RunwayML.
- via extension: [Aesthetic Gradients](https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-gradients), a way to generate images with a specific aesthetic by using clip images embds (implementation of [https://github.com/vicgalle/stable-diffusion-aesthetic-gradients](https://github.com/vicgalle/stable-diffusion-aesthetic-gradients))
- via extension: [Aesthetic Gradients](https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-gradients), a way to generate images with a specific aesthetic by using clip images embeds (implementation of [https://github.com/vicgalle/stable-diffusion-aesthetic-gradients](https://github.com/vicgalle/stable-diffusion-aesthetic-gradients))
- [Stable Diffusion 2.0](https://github.com/Stability-AI/stablediffusion) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#stable-diffusion-20) for instructions
## Installation and Running

8
javascript/contextMenus.js
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@ -61,15 +61,15 @@ contextMenuInit = function(){
}
function appendContextMenuOption(targetEmementSelector,entryName,entryFunction){
function appendContextMenuOption(targetElementSelector,entryName,entryFunction){
currentItems = menuSpecs.get(targetEmementSelector)
currentItems = menuSpecs.get(targetElementSelector)
if(!currentItems){
currentItems = []
menuSpecs.set(targetEmementSelector,currentItems);
menuSpecs.set(targetElementSelector,currentItems);
}
let newItem = {'id':targetEmementSelector+'_'+uid(),
let newItem = {'id':targetElementSelector+'_'+uid(),
'name':entryName,
'func':entryFunction,
'isNew':true}

2
javascript/progressbar.js
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@ -3,7 +3,7 @@ global_progressbars = {}
galleries = {}
galleryObservers = {}
// this tracks laumnches of window.setTimeout for progressbar to prevent starting a new timeout when the previous is still running
// this tracks launches of window.setTimeout for progressbar to prevent starting a new timeout when the previous is still running
timeoutIds = {}
function check_progressbar(id_part, id_progressbar, id_progressbar_span, id_skip, id_interrupt, id_preview, id_gallery){

2
javascript/ui.js
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@ -100,7 +100,7 @@ function create_submit_args(args){
// As it is currently, txt2img and img2img send back the previous output args (txt2img_gallery, generation_info, html_info) whenever you generate a new image.
// This can lead to uploading a huge gallery of previously generated images, which leads to an unnecessary delay between submitting and beginning to generate.
// I don't know why gradio is seding outputs along with inputs, but we can prevent sending the image gallery here, which seems to be an issue for some.
// I don't know why gradio is sending outputs along with inputs, but we can prevent sending the image gallery here, which seems to be an issue for some.
// If gradio at some point stops sending outputs, this may break something
if(Array.isArray(res[res.length - 3])){
res[res.length - 3] = null

14
modules/api/api.py
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@ -67,10 +67,10 @@ def encode_pil_to_base64(image):
class Api:
def __init__(self, app: FastAPI, queue_lock: Lock):
if shared.cmd_opts.api_auth:
self.credenticals = dict()
self.credentials = dict()
for auth in shared.cmd_opts.api_auth.split(","):
user, password = auth.split(":")
self.credenticals[user] = password
self.credentials[user] = password
self.router = APIRouter()
self.app = app
@ -93,7 +93,7 @@ class Api:
self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=List[HypernetworkItem])
self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[FaceRestorerItem])
self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[RealesrganItem])
self.add_api_route("/sdapi/v1/prompt-styles", self.get_promp_styles, methods=["GET"], response_model=List[PromptStyleItem])
self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=List[PromptStyleItem])
self.add_api_route("/sdapi/v1/artist-categories", self.get_artists_categories, methods=["GET"], response_model=List[str])
self.add_api_route("/sdapi/v1/artists", self.get_artists, methods=["GET"], response_model=List[ArtistItem])
@ -102,9 +102,9 @@ class Api:
return self.app.add_api_route(path, endpoint, dependencies=[Depends(self.auth)], **kwargs)
return self.app.add_api_route(path, endpoint, **kwargs)
def auth(self, credenticals: HTTPBasicCredentials = Depends(HTTPBasic())):
if credenticals.username in self.credenticals:
if compare_digest(credenticals.password, self.credenticals[credenticals.username]):
def auth(self, credentials: HTTPBasicCredentials = Depends(HTTPBasic())):
if credentials.username in self.credentials:
if compare_digest(credentials.password, self.credentials[credentials.username]):
return True
raise HTTPException(status_code=401, detail="Incorrect username or password", headers={"WWW-Authenticate": "Basic"})
@ -308,7 +308,7 @@ class Api:
def get_realesrgan_models(self):
return [{"name":x.name,"path":x.data_path, "scale":x.scale} for x in get_realesrgan_models(None)]
def get_promp_styles(self):
def get_prompt_styles(self):
styleList = []
for k in shared.prompt_styles.styles:
style = shared.prompt_styles.styles[k]

2
modules/api/models.py
View file

@ -128,7 +128,7 @@ class ExtrasBaseRequest(BaseModel):
upscaling_resize: float = Field(default=2, title="Upscaling Factor", ge=1, le=4, description="By how much to upscale the image, only used when resize_mode=0.")
upscaling_resize_w: int = Field(default=512, title="Target Width", ge=1, description="Target width for the upscaler to hit. Only used when resize_mode=1.")
upscaling_resize_h: int = Field(default=512, title="Target Height", ge=1, description="Target height for the upscaler to hit. Only used when resize_mode=1.")
upscaling_crop: bool = Field(default=True, title="Crop to fit", description="Should the upscaler crop the image to fit in the choosen size?")
upscaling_crop: bool = Field(default=True, title="Crop to fit", description="Should the upscaler crop the image to fit in the chosen size?")
upscaler_1: str = Field(default="None", title="Main upscaler", description=f"The name of the main upscaler to use, it has to be one of this list: {' , '.join([x.name for x in sd_upscalers])}")
upscaler_2: str = Field(default="None", title="Secondary upscaler", description=f"The name of the secondary upscaler to use, it has to be one of this list: {' , '.join([x.name for x in sd_upscalers])}")
extras_upscaler_2_visibility: float = Field(default=0, title="Secondary upscaler visibility", ge=0, le=1, allow_inf_nan=False, description="Sets the visibility of secondary upscaler, values should be between 0 and 1.")

2
modules/images.py
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@ -590,7 +590,7 @@ def read_info_from_image(image):
Negative prompt: {json_info["uc"]}
Steps: {json_info["steps"]}, Sampler: {sampler}, CFG scale: {json_info["scale"]}, Seed: {json_info["seed"]}, Size: {image.width}x{image.height}, Clip skip: 2, ENSD: 31337"""
except Exception:
print(f"Error parsing NovelAI iamge generation parameters:", file=sys.stderr)
print(f"Error parsing NovelAI image generation parameters:", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
return geninfo, items

2
modules/processing.py
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@ -704,7 +704,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
samples = samples[:, :, self.truncate_y//2:samples.shape[2]-self.truncate_y//2, self.truncate_x//2:samples.shape[3]-self.truncate_x//2]
"""saves image before applying hires fix, if enabled in options; takes as an arguyment either an image or batch with latent space images"""
"""saves image before applying hires fix, if enabled in options; takes as an argument either an image or batch with latent space images"""
def save_intermediate(image, index):
if not opts.save or self.do_not_save_samples or not opts.save_images_before_highres_fix:
return

2
modules/safe.py
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@ -108,7 +108,7 @@ def load(filename, *args, **kwargs):
def load_with_extra(filename, extra_handler=None, *args, **kwargs):
"""
this functon is intended to be used by extensions that want to load models with
this function is intended to be used by extensions that want to load models with
some extra classes in them that the usual unpickler would find suspicious.
Use the extra_handler argument to specify a function that takes module and field name as text,

4
modules/scripts.py
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@ -36,7 +36,7 @@ class Script:
def ui(self, is_img2img):
"""this function should create gradio UI elements. See https://gradio.app/docs/#components
The return value should be an array of all components that are used in processing.
Values of those returned componenbts will be passed to run() and process() functions.
Values of those returned components will be passed to run() and process() functions.
"""
pass
@ -47,7 +47,7 @@ class Script:
This function should return:
- False if the script should not be shown in UI at all
- True if the script should be shown in UI if it's scelected in the scripts drowpdown
- True if the script should be shown in UI if it's selected in the scripts dropdown
- script.AlwaysVisible if the script should be shown in UI at all times
"""

2
modules/sd_hijack_inpainting.py
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@ -326,7 +326,7 @@ def do_inpainting_hijack():
# most of this stuff seems to no longer be needed because it is already included into SD2.0
# LatentInpaintDiffusion remains because SD2.0's LatentInpaintDiffusion can't be loaded without specifying a checkpoint
# p_sample_plms is needed because PLMS can't work with dicts as conditionings
# this file should be cleaned up later if weverything tuens out to work fine
# this file should be cleaned up later if everything turns out to work fine
# ldm.models.diffusion.ddpm.get_unconditional_conditioning = get_unconditional_conditioning
ldm.models.diffusion.ddpm.LatentInpaintDiffusion = LatentInpaintDiffusion

2
modules/sd_hijack_unet.py
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@ -4,7 +4,7 @@ import torch
class TorchHijackForUnet:
"""
This is torch, but with cat that resizes tensors to appropriate dimensions if they do not match;
this makes it possible to create pictures with dimensions that are muliples of 8 rather than 64
this makes it possible to create pictures with dimensions that are multiples of 8 rather than 64
"""
def __getattr__(self, item):

2
modules/textual_inversion/dataset.py
View file

@ -57,7 +57,7 @@ class PersonalizedBase(Dataset):
print("Preparing dataset...")
for path in tqdm.tqdm(self.image_paths):
if shared.state.interrupted:
raise Exception("inturrupted")
raise Exception("interrupted")
try:
image = Image.open(path).convert('RGB').resize((self.width, self.height), PIL.Image.BICUBIC)
except Exception:

2
modules/textual_inversion/textual_inversion.py
View file

@ -133,7 +133,7 @@ class EmbeddingDatabase:
process_file(fullfn, fn)
except Exception:
print(f"Error loading emedding {fn}:", file=sys.stderr)
print(f"Error loading embedding {fn}:", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
continue

10
scripts/prompt_matrix.py
View file

@ -18,7 +18,7 @@ def draw_xy_grid(xs, ys, x_label, y_label, cell):
ver_texts = [[images.GridAnnotation(y_label(y))] for y in ys]
hor_texts = [[images.GridAnnotation(x_label(x))] for x in xs]
first_pocessed = None
first_processed = None
state.job_count = len(xs) * len(ys)
@ -27,17 +27,17 @@ def draw_xy_grid(xs, ys, x_label, y_label, cell):
state.job = f"{ix + iy * len(xs) + 1} out of {len(xs) * len(ys)}"
processed = cell(x, y)
if first_pocessed is None:
first_pocessed = processed
if first_processed is None:
first_processed = processed
res.append(processed.images[0])
grid = images.image_grid(res, rows=len(ys))
grid = images.draw_grid_annotations(grid, res[0].width, res[0].height, hor_texts, ver_texts)
first_pocessed.images = [grid]
first_processed.images = [grid]
return first_pocessed
return first_processed
class Script(scripts.Script):

4
webui.py
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@ -153,8 +153,8 @@ def webui():
# gradio uses a very open CORS policy via app.user_middleware, which makes it possible for
# an attacker to trick the user into opening a malicious HTML page, which makes a request to the
# running web ui and do whatever the attcker wants, including installing an extension and
# runnnig its code. We disable this here. Suggested by RyotaK.
# running web ui and do whatever the attacker wants, including installing an extension and
# running its code. We disable this here. Suggested by RyotaK.
app.user_middleware = [x for x in app.user_middleware if x.cls.__name__ != 'CORSMiddleware']
setup_cors(app)