Merge from master

This commit is contained in:
Robin Fernandes 2022-09-23 00:54:32 +00:00
commit 03738668c0
10 changed files with 218 additions and 101 deletions

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@ -76,6 +76,10 @@ sudo pacman -S wget git python3
bash <(wget -qO- https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh)
```
### Installation on Apple Silicon
Find the instructions [here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Installation-on-Apple-Silicon).
## Documentation
The documentation was moved from this README over to the project's [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki).

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@ -18,9 +18,9 @@ function dimensionChange(e,dimname){
return;
}
var img2imgMode = gradioApp().querySelector("input[name=radio-img2img_mode]:checked")
var img2imgMode = gradioApp().querySelector('#mode_img2img.tabs > div > button.rounded-t-lg.border-gray-200')
if(img2imgMode){
img2imgMode=img2imgMode.value
img2imgMode=img2imgMode.innerText
}else{
return;
}
@ -30,12 +30,10 @@ function dimensionChange(e,dimname){
var targetElement = null;
if(img2imgMode=='Redraw whole image' && redrawImage){
if(img2imgMode=='img2img' && redrawImage){
targetElement = redrawImage;
}else if(img2imgMode=='Inpaint a part of image' && inpaintImage){
}else if(img2imgMode=='Inpaint' && inpaintImage){
targetElement = inpaintImage;
}else if(img2imgMode=='SD upscale' && redrawImage){
targetElement = redrawImage;
}
if(targetElement){
@ -119,6 +117,3 @@ onUiUpdate(function(){
})
}
});

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@ -59,6 +59,7 @@ titles = {
"Images filename pattern": "Use following tags to define how filenames for images are chosen: [steps], [cfg], [prompt], [prompt_spaces], [width], [height], [sampler], [seed], [model_hash], [prompt_words], [date]; leave empty for default.",
"Directory name pattern": "Use following tags to define how subdirectories for images and grids are chosen: [steps], [cfg], [prompt], [prompt_spaces], [width], [height], [sampler], [seed], [model_hash], [prompt_words], [date]; leave empty for default.",
"Max prompt words": "Set the maximum number of words to be used in the [prompt_words] option; ATTENTION: If the words are too long, they may exceed the maximum length of the file path that the system can handle",
"Loopback": "Process an image, use it as an input, repeat.",
"Loops": "How many times to repeat processing an image and using it as input for the next iteration",

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@ -0,0 +1,45 @@
/**
* temporary fix for https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/668
* @see https://github.com/gradio-app/gradio/issues/1721
*/
window.addEventListener( 'resize', () => imageMaskResize());
function imageMaskResize() {
const canvases = gradioApp().querySelectorAll('#img2maskimg .touch-none canvas');
if ( ! canvases.length ) {
canvases_fixed = false;
window.removeEventListener( 'resize', imageMaskResize );
return;
}
const wrapper = canvases[0].closest('.touch-none');
const previewImage = wrapper.previousElementSibling;
if ( ! previewImage.complete ) {
previewImage.addEventListener( 'load', () => imageMaskResize());
return;
}
const w = previewImage.width;
const h = previewImage.height;
const nw = previewImage.naturalWidth;
const nh = previewImage.naturalHeight;
const portrait = nh > nw;
const factor = portrait;
const wW = Math.min(w, portrait ? h/nh*nw : w/nw*nw);
const wH = Math.min(h, portrait ? h/nh*nh : w/nw*nh);
wrapper.style.width = `${wW}px`;
wrapper.style.height = `${wH}px`;
wrapper.style.left = `${(w-wW)/2}px`;
wrapper.style.top = `${(h-wH)/2}px`;
canvases.forEach( c => {
c.style.width = c.style.height = '';
c.style.maxWidth = '100%';
c.style.maxHeight = '100%';
c.style.objectFit = 'contain';
});
}
onUiUpdate(() => imageMaskResize());

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@ -249,7 +249,6 @@ invalid_filename_prefix = ' '
invalid_filename_postfix = ' .'
re_nonletters = re.compile(r'[\s'+string.punctuation+']+')
max_filename_part_length = 128
max_prompt_words = 8
def sanitize_filename_part(text, replace_spaces=True):
@ -263,6 +262,8 @@ def sanitize_filename_part(text, replace_spaces=True):
def apply_filename_pattern(x, p, seed, prompt):
max_prompt_words = opts.directories_max_prompt_words
if seed is not None:
x = x.replace("[seed]", str(seed))

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@ -118,4 +118,8 @@ def img2img(mode: int, prompt: str, negative_prompt: str, prompt_style: str, pro
shared.total_tqdm.clear()
return processed.images, processed.js(), plaintext_to_html(processed.info)
generation_info_js = processed.js()
if opts.samples_log_stdout:
print(generation_info_js)
return processed.images, generation_info_js, plaintext_to_html(processed.info)

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@ -100,23 +100,49 @@ def realesrgan_models_names():
return [x.name for x in modules.realesrgan_model.get_realesrgan_models()]
class Options:
class OptionInfo:
class OptionInfo:
def __init__(self, default=None, label="", component=None, component_args=None, onchange=None):
self.default = default
self.label = label
self.component = component
self.component_args = component_args
self.onchange = onchange
self.section = None
data = None
hide_dirs = {"visible": False} if cmd_opts.hide_ui_dir_config else None
data_labels = {
def options_section(section_identifer, options_dict):
for k, v in options_dict.items():
v.section = section_identifer
return options_dict
hide_dirs = {"visible": False} if cmd_opts.hide_ui_dir_config else None
options_templates = {}
options_templates.update(options_section(('saving-images', "Saving images/grids"), {
"samples_save": OptionInfo(True, "Always save all generated images"),
"samples_format": OptionInfo('png', 'File format for images'),
"samples_filename_pattern": OptionInfo("", "Images filename pattern"),
"save_to_dirs": OptionInfo(False, "Save images to a subdirectory"),
"grid_save_to_dirs": OptionInfo(False, "Save grids to subdirectory"),
"directories_filename_pattern": OptionInfo("", "Directory name pattern"),
"outdir_samples": OptionInfo("", "Output directory for images; if empty, defaults to two directories below", component_args=hide_dirs),
"grid_save": OptionInfo(True, "Always save all generated image grids"),
"grid_format": OptionInfo('png', 'File format for grids'),
"grid_extended_filename": OptionInfo(False, "Add extended info (seed, prompt) to filename when saving grid"),
"grid_only_if_multiple": OptionInfo(True, "Do not save grids consisting of one picture"),
"n_rows": OptionInfo(-1, "Grid row count; use -1 for autodetect and 0 for it to be same as batch size", gr.Slider, {"minimum": -1, "maximum": 16, "step": 1}),
"enable_pnginfo": OptionInfo(True, "Save text information about generation parameters as chunks to png files"),
"save_txt": OptionInfo(False, "Create a text file next to every image with generation parameters."),
"save_images_before_face_restoration": OptionInfo(False, "Save a copy of image before doing face restoration."),
"jpeg_quality": OptionInfo(80, "Quality for saved jpeg images", gr.Slider, {"minimum": 1, "maximum": 100, "step": 1}),
"export_for_4chan": OptionInfo(True, "If PNG image is larger than 4MB or any dimension is larger than 4000, downscale and save copy as JPG"),
"use_original_name_batch": OptionInfo(False, "Use original name for output filename during batch process in extras tab"),
}))
options_templates.update(options_section(('saving-paths', "Paths for saving"), {
"outdir_samples": OptionInfo("", "Output directory for images; if empty, defaults to three directories below", component_args=hide_dirs),
"outdir_txt2img_samples": OptionInfo("outputs/txt2img-images", 'Output directory for txt2img images', component_args=hide_dirs),
"outdir_img2img_samples": OptionInfo("outputs/img2img-images", 'Output directory for img2img images', component_args=hide_dirs),
"outdir_extras_samples": OptionInfo("outputs/extras-images", 'Output directory for images from extras tab', component_args=hide_dirs),
@ -124,57 +150,76 @@ class Options:
"outdir_txt2img_grids": OptionInfo("outputs/txt2img-grids", 'Output directory for txt2img grids', component_args=hide_dirs),
"outdir_img2img_grids": OptionInfo("outputs/img2img-grids", 'Output directory for img2img grids', component_args=hide_dirs),
"outdir_save": OptionInfo("log/images", "Directory for saving images using the Save button", component_args=hide_dirs),
"samples_save": OptionInfo(True, "Always save all generated images"),
"save_selected_only": OptionInfo(False, "When using 'Save' button, only save a single selected image"),
"samples_format": OptionInfo('png', 'File format for individual samples'),
"filter_nsfw": OptionInfo(False, "Filter NSFW content"),
"grid_save": OptionInfo(True, "Always save all generated image grids"),
"return_grid": OptionInfo(True, "Show grid in results for web"),
"grid_format": OptionInfo('png', 'File format for grids'),
"grid_extended_filename": OptionInfo(False, "Add extended info (seed, prompt) to filename when saving grid"),
"grid_only_if_multiple": OptionInfo(True, "Do not save grids consisting of one picture"),
"n_rows": OptionInfo(-1, "Grid row count; use -1 for autodetect and 0 for it to be same as batch size", gr.Slider, {"minimum": -1, "maximum": 16, "step": 1}),
"jpeg_quality": OptionInfo(80, "Quality for saved jpeg images", gr.Slider, {"minimum": 1, "maximum": 100, "step": 1}),
"export_for_4chan": OptionInfo(True, "If PNG image is larger than 4MB or any dimension is larger than 4000, downscale and save copy as JPG"),
"enable_pnginfo": OptionInfo(True, "Save text information about generation parameters as chunks to png files"),
"add_model_hash_to_info": OptionInfo(False, "Add model hash to generation information"),
"img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."),
"save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"),
"img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies (normally you'd do less with less denoising)."),
"enable_quantization": OptionInfo(False, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds. Requires restart to apply."),
"font": OptionInfo("", "Font for image grids that have text"),
"enable_emphasis": OptionInfo(True, "Use (text) to make model pay more attention to text and [text] to make it pay less attention"),
"enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
"save_txt": OptionInfo(False, "Create a text file next to every image with generation parameters."),
}))
options_templates.update(options_section(('saving-to-dirs', "Saving to a directory"), {
"save_to_dirs": OptionInfo(False, "Save images to a subdirectory"),
"grid_save_to_dirs": OptionInfo(False, "Save grids to subdirectory"),
"directories_filename_pattern": OptionInfo("", "Directory name pattern"),
"directories_max_prompt_words": OptionInfo(8, "Max prompt words", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1}),
}))
options_templates.update(options_section(('upscaling', "Upscaling"), {
"ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers. 0 = no tiling.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}),
"ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for ESRGAN upscalers. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}),
"realesrgan_enabled_models": OptionInfo(["Real-ESRGAN 4x plus", "Real-ESRGAN 4x plus anime 6B"], "Select which RealESRGAN models to show in the web UI. (Requires restart)", gr.CheckboxGroup, lambda: {"choices": realesrgan_models_names()}),
"SWIN_tile": OptionInfo(192, "Tile size for all SwinIR.", gr.Slider, {"minimum": 16, "maximum": 512, "step": 16}),
"SWIN_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for SwinIR. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}),
"ldsr_steps": OptionInfo(100, "LDSR processing steps. Lower = faster", gr.Slider, {"minimum": 1, "maximum": 200, "step": 1}),
"ldsr_pre_down":OptionInfo(1, "LDSR Pre-process downssample scale. 1 = no down-sampling, 4 = 1/4 scale.", gr.Slider, {"minimum": 1, "maximum": 4, "step": 1}),
"ldsr_post_down":OptionInfo(1, "LDSR Post-process down-sample scale. 1 = no down-sampling, 4 = 1/4 scale.", gr.Slider, {"minimum": 1, "maximum": 4, "step": 1}),
"random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),
"ldsr_pre_down": OptionInfo(1, "LDSR Pre-process downssample scale. 1 = no down-sampling, 4 = 1/4 scale.", gr.Slider, {"minimum": 1, "maximum": 4, "step": 1}),
"ldsr_post_down": OptionInfo(1, "LDSR Post-process down-sample scale. 1 = no down-sampling, 4 = 1/4 scale.", gr.Slider, {"minimum": 1, "maximum": 4, "step": 1}),
"upscaler_for_hires_fix": OptionInfo(None, "Upscaler for highres. fix", gr.Radio, lambda: {"choices": [x.name for x in sd_upscalers]}),
"show_progressbar": OptionInfo(True, "Show progressbar"),
"show_progress_every_n_steps": OptionInfo(0, "Show show image creation progress every N sampling steps. Set 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}),
"multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job. Broken in PyCharm console."),
"memmon_poll_rate": OptionInfo(8, "VRAM usage polls per second during generation. Set to 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 40, "step":1}),
}))
options_templates.update(options_section(('face-restoration', "Face restoration"), {
"face_restoration_model": OptionInfo(None, "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in face_restorers]}),
"code_former_weight": OptionInfo(0.5, "CodeFormer weight parameter; 0 = maximum effect; 1 = minimum effect", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
"save_images_before_face_restoration": OptionInfo(False, "Save a copy of image before doing face restoration."),
"face_restoration_unload": OptionInfo(False, "Move face restoration model from VRAM into RAM after processing"),
"save_selected_only": OptionInfo(False, "When using 'Save' button, only save a single selected image"),
}))
options_templates.update(options_section(('system', "System"), {
"memmon_poll_rate": OptionInfo(8, "VRAM usage polls per second during generation. Set to 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}),
"samples_log_stdout": OptionInfo(False, "Always print all generation info to standard output"),
"multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job. Broken in PyCharm console."),
}))
options_templates.update(options_section(('sd', "Stable Diffusion"), {
"sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Radio, lambda: {"choices": [x.title for x in modules.sd_models.checkpoints_list.values()]}),
"img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."),
"save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"),
"img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies (normally you'd do less with less denoising)."),
"enable_quantization": OptionInfo(False, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds. Requires restart to apply."),
"enable_emphasis": OptionInfo(True, "Use (text) to make model pay more attention to text and [text] to make it pay less attention"),
"enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
"filter_nsfw": OptionInfo(False, "Filter NSFW content"),
"random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),
}))
options_templates.update(options_section(('interrogate', "Interrogate Options"), {
"interrogate_keep_models_in_memory": OptionInfo(False, "Interrogate: keep models in VRAM"),
"interrogate_use_builtin_artists": OptionInfo(True, "Interrogate: use artists from artists.csv"),
"interrogate_clip_num_beams": OptionInfo(1, "Interrogate: num_beams for BLIP", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}),
"interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}),
"interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}),
"interrogate_clip_dict_limit": OptionInfo(1500, "Interrogate: maximum number of lines in text file (0 = No limit)"),
"sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Radio, lambda: {"choices": [x.title for x in modules.sd_models.checkpoints_list.values()]}),
}))
options_templates.update(options_section(('ui', "User interface"), {
"show_progressbar": OptionInfo(True, "Show progressbar"),
"show_progress_every_n_steps": OptionInfo(0, "Show show image creation progress every N sampling steps. Set 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}),
"return_grid": OptionInfo(True, "Show grid in results for web"),
"add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
"font": OptionInfo("", "Font for image grids that have text"),
"js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
"js_modal_lightbox_initialy_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
"use_original_name_batch": OptionInfo(False, "Use original name for output filename during batch process"),
}
}))
class Options:
data = None
data_labels = options_templates
def __init__(self):
self.data = {k: v.default for k, v in self.data_labels.items()}

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@ -44,5 +44,9 @@ def txt2img(prompt: str, negative_prompt: str, prompt_style: str, prompt_style2:
shared.total_tqdm.clear()
return processed.images, processed.js(), plaintext_to_html(processed.info)
generation_info_js = processed.js()
if opts.samples_log_stdout:
print(generation_info_js)
return processed.images, generation_info_js, plaintext_to_html(processed.info)

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@ -22,7 +22,6 @@ from modules.paths import script_path
from modules.shared import opts, cmd_opts
import modules.shared as shared
from modules.sd_samplers import samplers, samplers_for_img2img
import modules.realesrgan_model as realesrgan
import modules.ldsr_model
import modules.scripts
import modules.gfpgan_model
@ -814,9 +813,6 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
return comp(label=info.label, value=fun, **(args or {}))
components = []
keys = list(opts.data_labels.keys())
settings_cols = 3
items_per_col = math.ceil(len(keys) / settings_cols)
def run_settings(*args):
up = []
@ -842,20 +838,33 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
settings_submit = gr.Button(value="Apply settings", variant='primary')
result = gr.HTML()
settings_cols = 3
items_per_col = int(len(opts.data_labels) * 0.9 / settings_cols)
cols_displayed = 0
items_displayed = 0
previous_section = None
column = None
with gr.Row(elem_id="settings").style(equal_height=False):
for colno in range(settings_cols):
with gr.Column(variant='panel'):
for rowno in range(items_per_col):
index = rowno + colno * items_per_col
for i, (k, item) in enumerate(opts.data_labels.items()):
if index < len(keys):
components.append(create_setting_component(keys[index]))
if previous_section != item.section:
if cols_displayed < settings_cols and (items_displayed >= items_per_col or previous_section is None):
if column is not None:
column.__exit__()
settings_submit.click(
fn=run_settings,
inputs=components,
outputs=[result]
)
column = gr.Column(variant='panel')
column.__enter__()
items_displayed = 0
cols_displayed += 1
previous_section = item.section
gr.HTML(elem_id="settings_header_text_{}".format(item.section[0]), value='<h1 class="gr-button-lg">{}</h1>'.format(item.section[1]))
components.append(create_setting_component(k))
items_displayed += 1
request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")
request_notifications.click(
@ -865,6 +874,15 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
_js='function(){}'
)
if column is not None:
column.__exit__()
settings_submit.click(
fn=run_settings,
inputs=components,
outputs=[result]
)
interfaces = [
(txt2img_interface, "txt2img", "txt2img"),
(img2img_interface, "img2img", "img2img"),

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@ -11,7 +11,7 @@ from modules import images, processing, devices
from modules.processing import Processed, process_images
from modules.shared import opts, cmd_opts, state
# https://github.com/parlance-zz/g-diffuser-bot
def expand(x, dir, amount, power=0.75):
is_left = dir == 3
is_right = dir == 1