stable-diffusion-webui/frontend/ui_functions.py

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2022-09-26 16:02:48 +03:00
# This file is part of stable-diffusion-webui (https://github.com/sd-webui/stable-diffusion-webui/).
# Copyright 2022 sd-webui team.
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import re
import gradio as gr
from PIL import Image, ImageFont, ImageDraw, ImageFilter, ImageOps
from io import BytesIO
import base64
import re
def change_image_editor_mode(choice, cropped_image, masked_image, resize_mode, width, height):
if choice == "Mask":
update_image_result = update_image_mask(cropped_image, resize_mode, width, height)
Add mask_restore to restore images based on mask, fixing #665 (#898) * Add mask_restore option to give users the option to restore images based on mask, fixing #665. Before commit c73fdd78 (Implement masking during sampling to improve blending, #308) image mask was applied after sampling, resulting in masked parts that are not regenerated to actually stay the same. Since c73fdd78 the masked img2img will change the whole image, even in masked areas. It gives better looking results at first glance, but will result in image degredation when applied a few times. See issue #665. In the workflow of using repeated masked img2img, users may want to use this options to keep the parts of image they actually want to keep without image degradation. A final masked img2img or whole image img2img with mask_restore disabled will give the better blending of "Implement masking during sampling". * revert changes of a7be43ba in change_image_editor_mode * fix ui_functions.change_image_editor_mode by adding gr.update to the end of the list it returns * revert inserted newlines and whitespaces to match format of previous code * improve caption of new option mask_restore "Only modify regenerated parts of image" * fix ui_functions.change_image_editor_mode by adding gr.update to the end of the list it returns an old copy of the function exists in webui.py, this superflous function mistakenly was changed by the earlier commit b6a9e16b * remove unused functions that are near duplicates of functions in ui_functions.py
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return [gr.update(visible=False), update_image_result, gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)]
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update_image_result = update_image_mask(masked_image["image"] if masked_image is not None else None, resize_mode, width, height)
Add mask_restore to restore images based on mask, fixing #665 (#898) * Add mask_restore option to give users the option to restore images based on mask, fixing #665. Before commit c73fdd78 (Implement masking during sampling to improve blending, #308) image mask was applied after sampling, resulting in masked parts that are not regenerated to actually stay the same. Since c73fdd78 the masked img2img will change the whole image, even in masked areas. It gives better looking results at first glance, but will result in image degredation when applied a few times. See issue #665. In the workflow of using repeated masked img2img, users may want to use this options to keep the parts of image they actually want to keep without image degradation. A final masked img2img or whole image img2img with mask_restore disabled will give the better blending of "Implement masking during sampling". * revert changes of a7be43ba in change_image_editor_mode * fix ui_functions.change_image_editor_mode by adding gr.update to the end of the list it returns * revert inserted newlines and whitespaces to match format of previous code * improve caption of new option mask_restore "Only modify regenerated parts of image" * fix ui_functions.change_image_editor_mode by adding gr.update to the end of the list it returns an old copy of the function exists in webui.py, this superflous function mistakenly was changed by the earlier commit b6a9e16b * remove unused functions that are near duplicates of functions in ui_functions.py
2022-09-10 00:07:14 +03:00
return [update_image_result, gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)]
def update_image_mask(cropped_image, resize_mode, width, height):
resized_cropped_image = resize_image(resize_mode, cropped_image, width, height) if cropped_image else None
return gr.update(value=resized_cropped_image, visible=True)
[Various Changes] GoBig fixes, model loading unloading and more (#553) * added image lab * first release model loading/unloading and save procedure added, commented out unused code from frontend * bug fixes Changed the image output to a gallery to display multiple items Fixed results not showing up in output Fixed RealESRGAN 2x mode not working and hard coded the default value for the reload. * added GoBig model check * added LDSR load check * removed global statements, added model loader/unloader function * fixed optimized mode * update * update Added send to lab button Added a print out if latent-diffusion folder isn't found * brought back the fix faces and upscale in generation tab * uncommenting img lab flag * added LDSR instructions * default imgProcessorTask set to false * exposed LDSR settings to lab users need to reclone the LDSR repo to use them. * Update frontend.py moving some stuff around to make them more coherent * restored upscale and fix faces to img2img * added notice section * fixed gfpgan/upscaled pictures not showing in 2img interfaces * send to lab button now sends info as well * uncommented dimension info update * added increment buttons to sampler for that k_euler_a action * image lab settings toggle on and off with selection * removed wip settings panel * better model loading handling and removed increment buttons * explaining * disabled SD unloading in image lab upscaling with realesgan and face fix * fixed a conflict with image lab Co-authored-by: dr3amer <91037083+dr3am37@users.noreply.github.com> Co-authored-by: hlky <106811348+hlky@users.noreply.github.com>
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def toggle_options_gfpgan(selection):
if 0 in selection:
return gr.update(visible=True)
else:
return gr.update(visible=False)
def toggle_options_upscalers(selection):
if 1 in selection:
return gr.update(visible=True)
else:
return gr.update(visible=False)
def toggle_options_realesrgan(selection):
if selection == 0 or selection == 1 or selection == 3:
return gr.update(visible=True)
else:
return gr.update(visible=False)
def toggle_options_gobig(selection):
if selection == 1:
#print(selection)
return gr.update(visible=True)
if selection == 3:
return gr.update(visible=True)
else:
return gr.update(visible=False)
def toggle_options_ldsr(selection):
if selection == 2 or selection == 3:
return gr.update(visible=True)
else:
return gr.update(visible=False)
def increment_down(value):
return value - 1
def increment_up(value):
return value + 1
def copy_img_to_lab(img):
try:
image_data = re.sub('^data:image/.+;base64,', '', img)
processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
tab_update = gr.update(selected='imgproc_tab')
img_update = gr.update(value=processed_image)
[Various Changes] GoBig fixes, model loading unloading and more (#553) * added image lab * first release model loading/unloading and save procedure added, commented out unused code from frontend * bug fixes Changed the image output to a gallery to display multiple items Fixed results not showing up in output Fixed RealESRGAN 2x mode not working and hard coded the default value for the reload. * added GoBig model check * added LDSR load check * removed global statements, added model loader/unloader function * fixed optimized mode * update * update Added send to lab button Added a print out if latent-diffusion folder isn't found * brought back the fix faces and upscale in generation tab * uncommenting img lab flag * added LDSR instructions * default imgProcessorTask set to false * exposed LDSR settings to lab users need to reclone the LDSR repo to use them. * Update frontend.py moving some stuff around to make them more coherent * restored upscale and fix faces to img2img * added notice section * fixed gfpgan/upscaled pictures not showing in 2img interfaces * send to lab button now sends info as well * uncommented dimension info update * added increment buttons to sampler for that k_euler_a action * image lab settings toggle on and off with selection * removed wip settings panel * better model loading handling and removed increment buttons * explaining * disabled SD unloading in image lab upscaling with realesgan and face fix * fixed a conflict with image lab Co-authored-by: dr3amer <91037083+dr3am37@users.noreply.github.com> Co-authored-by: hlky <106811348+hlky@users.noreply.github.com>
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return processed_image, tab_update,
except IndexError:
return [None, None]
def copy_img_params_to_lab(params):
try:
prompt = params[0][0].replace('\n', ' ').replace('\r', '')
seed = int(params[1][1])
steps = int(params[7][1])
cfg_scale = float(params[9][1])
sampler = params[11][1]
return prompt,seed,steps,cfg_scale,sampler
except IndexError:
return [None, None]
def copy_img_to_input(img):
try:
image_data = re.sub('^data:image/.+;base64,', '', img)
processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
tab_update = gr.update(selected='img2img_tab')
img_update = gr.update(value=processed_image)
return processed_image, processed_image , tab_update
except IndexError:
return [None, None]
def copy_img_to_edit(img):
try:
image_data = re.sub('^data:image/.+;base64,', '', img)
processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
tab_update = gr.update(selected='img2img_tab')
img_update = gr.update(value=processed_image)
mode_update = gr.update(value='Crop')
return processed_image, tab_update, mode_update
except IndexError:
return [None, None]
def copy_img_to_mask(img):
try:
image_data = re.sub('^data:image/.+;base64,', '', img)
processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
tab_update = gr.update(selected='img2img_tab')
img_update = gr.update(value=processed_image)
mode_update = gr.update(value='Mask')
return processed_image, tab_update, mode_update
except IndexError:
return [None, None]
def copy_img_to_upscale_esrgan(img):
tabs_update = gr.update(selected='realesrgan_tab')
image_data = re.sub('^data:image/.+;base64,', '', img)
processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
return processed_image, tabs_update
help_text = """
## Mask/Crop
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* Masking is not inpainting. You will probably get better results manually masking your images in photoshop instead.
* Built-in masking/cropping is very temperamental.
* It may take some time for the image to show when switching from Crop to Mask.
* If the image doesn't appear after switching to Mask, switch back to Crop and then back again to Mask
* If the mask appears distorted (the brush is weirdly shaped instead of round), switch back to Crop and then back again to Mask.
## Advanced Editor
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* Click 💾 Save to send your editor changes to the img2img workflow
* Click Clear to discard your editor changes
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If anything breaks, try switching modes again, switch tabs, clear the image, or reload.
"""
def resize_image(resize_mode, im, width, height):
LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS)
if resize_mode == 0:
res = im.resize((width, height), resample=LANCZOS)
elif resize_mode == 1:
ratio = width / height
src_ratio = im.width / im.height
src_w = width if ratio > src_ratio else im.width * height // im.height
src_h = height if ratio <= src_ratio else im.height * width // im.width
resized = im.resize((src_w, src_h), resample=LANCZOS)
res = Image.new("RGBA", (width, height))
res.paste(resized, box=(width // 2 - src_w // 2, height // 2 - src_h // 2))
else:
ratio = width / height
src_ratio = im.width / im.height
src_w = width if ratio < src_ratio else im.width * height // im.height
src_h = height if ratio >= src_ratio else im.height * width // im.width
resized = im.resize((src_w, src_h), resample=LANCZOS)
res = Image.new("RGBA", (width, height))
res.paste(resized, box=(width // 2 - src_w // 2, height // 2 - src_h // 2))
if ratio < src_ratio:
fill_height = height // 2 - src_h // 2
res.paste(resized.resize((width, fill_height), box=(0, 0, width, 0)), box=(0, 0))
res.paste(resized.resize((width, fill_height), box=(0, resized.height, width, resized.height)), box=(0, fill_height + src_h))
elif ratio > src_ratio:
fill_width = width // 2 - src_w // 2
res.paste(resized.resize((fill_width, height), box=(0, 0, 0, height)), box=(0, 0))
res.paste(resized.resize((fill_width, height), box=(resized.width, 0, resized.width, height)), box=(fill_width + src_w, 0))
return res
def update_dimensions_info(width, height):
pixel_count_formated = "{:,.0f}".format(width * height)
return f"Aspect ratio: {round(width / height, 5)}\nTotal pixel count: {pixel_count_formated}"
def get_png_nfo( image: Image ):
info_text = ""
visible = bool(image and any(image.info))
if visible:
for key,value in image.info.items():
info_text += f"{key}: {value}\n"
info_text = info_text.rstrip('\n')
return gr.Textbox.update(value=info_text, visible=visible)
def load_settings(*values):
new_settings, key_names, checkboxgroup_info = values[-3:]
values = list(values[:-3])
if new_settings:
if type(new_settings) is str:
if os.path.exists(new_settings):
with open(new_settings, "r", encoding="utf8") as f:
new_settings = yaml.safe_load(f)
elif new_settings.startswith("file://") and os.path.exists(new_settings[7:]):
with open(new_settings[7:], "r", encoding="utf8") as f:
new_settings = yaml.safe_load(f)
else:
new_settings = yaml.safe_load(new_settings)
if type(new_settings) is not dict:
new_settings = {"prompt": new_settings}
if "txt2img" in new_settings:
new_settings = new_settings["txt2img"]
target = new_settings.pop("target", "txt2img")
if target != "txt2img":
print(f"Warning: applying settings to txt2img even though {target} is specified as target.", file=sys.stderr)
skipped_settings = {}
for key in new_settings.keys():
if key in key_names:
values[key_names.index(key)] = new_settings[key]
else:
skipped_settings[key] = new_settings[key]
if skipped_settings:
print(f"Settings could not be applied: {skipped_settings}", file=sys.stderr)
# Convert lists of checkbox indices to lists of checkbox labels:
for (cbg_index, cbg_choices) in checkboxgroup_info:
values[cbg_index] = [cbg_choices[i] for i in values[cbg_index]]
return values