AltDiffusion / ui_functions.py
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import re
import gradio as gr
from PIL import Image, ImageFont, ImageDraw, ImageFilter, ImageOps
from io import BytesIO
import base64
import re
def change_img_choices(sample_size):
choices = []
for i in range(int(sample_size)):
choices.append(
'图片{}(img{})'.format(i+1,i+1)
)
update_choices = gr.update(choices=choices)
return update_choices
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)
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)]
update_image_result = update_image_mask(masked_image["image"] if masked_image is not None else None, resize_mode, width, height)
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)]
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)
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)
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, idx):
try:
# print(img)
# print("=============")
# print("The img type is:{}".format(type(img[0])))
idx_map = {
"图片1(img1)":0,
"图片2(img2)":1,
"图片3(img3)":2,
"图片4(img4)":3,
}
idx = idx_map[idx]
image_data = re.sub('^data:image/.+;base64,', '', img[idx])
processed_image = Image.open(BytesIO(base64.b64decode(image_data)))
tab_update = gr.update(selected='img2img_tab')
img_update = gr.update(value=processed_image)
move_prompt_zh_update = gr.update(visible=True)
move_prompt_en_update = gr.update(visible=True)
prompt_update = gr.update(visible=True)
return tab_update,processed_image, processed_image, move_prompt_zh_update, move_prompt_en_update, prompt_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
* 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
* Click 💾 Save to send your editor changes to the img2img workflow
* Click ❌ Clear to discard your editor changes
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