AltDiffusion / ui_functions.py
root
add img choice
9267c91
raw
history blame
9.59 kB
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(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)
return tab_update,processed_image, processed_image
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