mirror of
https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
synced 2024-12-21 07:30:02 +08:00
658 lines
25 KiB
Python
658 lines
25 KiB
Python
import datetime
|
|
import sys
|
|
import traceback
|
|
|
|
import pytz
|
|
import io
|
|
import math
|
|
import os
|
|
from collections import namedtuple
|
|
import re
|
|
|
|
import numpy as np
|
|
import piexif
|
|
import piexif.helper
|
|
from PIL import Image, ImageFont, ImageDraw, PngImagePlugin
|
|
from fonts.ttf import Roboto
|
|
import string
|
|
import json
|
|
|
|
from modules import sd_samplers, shared, script_callbacks
|
|
from modules.shared import opts, cmd_opts
|
|
|
|
LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS)
|
|
|
|
|
|
def image_grid(imgs, batch_size=1, rows=None):
|
|
if rows is None:
|
|
if opts.n_rows > 0:
|
|
rows = opts.n_rows
|
|
elif opts.n_rows == 0:
|
|
rows = batch_size
|
|
elif opts.grid_prevent_empty_spots:
|
|
rows = math.floor(math.sqrt(len(imgs)))
|
|
while len(imgs) % rows != 0:
|
|
rows -= 1
|
|
else:
|
|
rows = math.sqrt(len(imgs))
|
|
rows = round(rows)
|
|
|
|
cols = math.ceil(len(imgs) / rows)
|
|
|
|
params = script_callbacks.ImageGridLoopParams(imgs, cols, rows)
|
|
script_callbacks.image_grid_callback(params)
|
|
|
|
w, h = imgs[0].size
|
|
grid = Image.new('RGB', size=(params.cols * w, params.rows * h), color='black')
|
|
|
|
for i, img in enumerate(params.imgs):
|
|
grid.paste(img, box=(i % params.cols * w, i // params.cols * h))
|
|
|
|
return grid
|
|
|
|
|
|
Grid = namedtuple("Grid", ["tiles", "tile_w", "tile_h", "image_w", "image_h", "overlap"])
|
|
|
|
|
|
def split_grid(image, tile_w=512, tile_h=512, overlap=64):
|
|
w = image.width
|
|
h = image.height
|
|
|
|
non_overlap_width = tile_w - overlap
|
|
non_overlap_height = tile_h - overlap
|
|
|
|
cols = math.ceil((w - overlap) / non_overlap_width)
|
|
rows = math.ceil((h - overlap) / non_overlap_height)
|
|
|
|
dx = (w - tile_w) / (cols - 1) if cols > 1 else 0
|
|
dy = (h - tile_h) / (rows - 1) if rows > 1 else 0
|
|
|
|
grid = Grid([], tile_w, tile_h, w, h, overlap)
|
|
for row in range(rows):
|
|
row_images = []
|
|
|
|
y = int(row * dy)
|
|
|
|
if y + tile_h >= h:
|
|
y = h - tile_h
|
|
|
|
for col in range(cols):
|
|
x = int(col * dx)
|
|
|
|
if x + tile_w >= w:
|
|
x = w - tile_w
|
|
|
|
tile = image.crop((x, y, x + tile_w, y + tile_h))
|
|
|
|
row_images.append([x, tile_w, tile])
|
|
|
|
grid.tiles.append([y, tile_h, row_images])
|
|
|
|
return grid
|
|
|
|
|
|
def combine_grid(grid):
|
|
def make_mask_image(r):
|
|
r = r * 255 / grid.overlap
|
|
r = r.astype(np.uint8)
|
|
return Image.fromarray(r, 'L')
|
|
|
|
mask_w = make_mask_image(np.arange(grid.overlap, dtype=np.float32).reshape((1, grid.overlap)).repeat(grid.tile_h, axis=0))
|
|
mask_h = make_mask_image(np.arange(grid.overlap, dtype=np.float32).reshape((grid.overlap, 1)).repeat(grid.image_w, axis=1))
|
|
|
|
combined_image = Image.new("RGB", (grid.image_w, grid.image_h))
|
|
for y, h, row in grid.tiles:
|
|
combined_row = Image.new("RGB", (grid.image_w, h))
|
|
for x, w, tile in row:
|
|
if x == 0:
|
|
combined_row.paste(tile, (0, 0))
|
|
continue
|
|
|
|
combined_row.paste(tile.crop((0, 0, grid.overlap, h)), (x, 0), mask=mask_w)
|
|
combined_row.paste(tile.crop((grid.overlap, 0, w, h)), (x + grid.overlap, 0))
|
|
|
|
if y == 0:
|
|
combined_image.paste(combined_row, (0, 0))
|
|
continue
|
|
|
|
combined_image.paste(combined_row.crop((0, 0, combined_row.width, grid.overlap)), (0, y), mask=mask_h)
|
|
combined_image.paste(combined_row.crop((0, grid.overlap, combined_row.width, h)), (0, y + grid.overlap))
|
|
|
|
return combined_image
|
|
|
|
|
|
class GridAnnotation:
|
|
def __init__(self, text='', is_active=True):
|
|
self.text = text
|
|
self.is_active = is_active
|
|
self.size = None
|
|
|
|
|
|
def draw_grid_annotations(im, width, height, hor_texts, ver_texts):
|
|
def wrap(drawing, text, font, line_length):
|
|
lines = ['']
|
|
for word in text.split():
|
|
line = f'{lines[-1]} {word}'.strip()
|
|
if drawing.textlength(line, font=font) <= line_length:
|
|
lines[-1] = line
|
|
else:
|
|
lines.append(word)
|
|
return lines
|
|
|
|
def get_font(fontsize):
|
|
try:
|
|
return ImageFont.truetype(opts.font or Roboto, fontsize)
|
|
except Exception:
|
|
return ImageFont.truetype(Roboto, fontsize)
|
|
|
|
def draw_texts(drawing, draw_x, draw_y, lines, initial_fnt, initial_fontsize):
|
|
for i, line in enumerate(lines):
|
|
fnt = initial_fnt
|
|
fontsize = initial_fontsize
|
|
while drawing.multiline_textsize(line.text, font=fnt)[0] > line.allowed_width and fontsize > 0:
|
|
fontsize -= 1
|
|
fnt = get_font(fontsize)
|
|
drawing.multiline_text((draw_x, draw_y + line.size[1] / 2), line.text, font=fnt, fill=color_active if line.is_active else color_inactive, anchor="mm", align="center")
|
|
|
|
if not line.is_active:
|
|
drawing.line((draw_x - line.size[0] // 2, draw_y + line.size[1] // 2, draw_x + line.size[0] // 2, draw_y + line.size[1] // 2), fill=color_inactive, width=4)
|
|
|
|
draw_y += line.size[1] + line_spacing
|
|
|
|
fontsize = (width + height) // 25
|
|
line_spacing = fontsize // 2
|
|
|
|
fnt = get_font(fontsize)
|
|
|
|
color_active = (0, 0, 0)
|
|
color_inactive = (153, 153, 153)
|
|
|
|
pad_left = 0 if sum([sum([len(line.text) for line in lines]) for lines in ver_texts]) == 0 else width * 3 // 4
|
|
|
|
cols = im.width // width
|
|
rows = im.height // height
|
|
|
|
assert cols == len(hor_texts), f'bad number of horizontal texts: {len(hor_texts)}; must be {cols}'
|
|
assert rows == len(ver_texts), f'bad number of vertical texts: {len(ver_texts)}; must be {rows}'
|
|
|
|
calc_img = Image.new("RGB", (1, 1), "white")
|
|
calc_d = ImageDraw.Draw(calc_img)
|
|
|
|
for texts, allowed_width in zip(hor_texts + ver_texts, [width] * len(hor_texts) + [pad_left] * len(ver_texts)):
|
|
items = [] + texts
|
|
texts.clear()
|
|
|
|
for line in items:
|
|
wrapped = wrap(calc_d, line.text, fnt, allowed_width)
|
|
texts += [GridAnnotation(x, line.is_active) for x in wrapped]
|
|
|
|
for line in texts:
|
|
bbox = calc_d.multiline_textbbox((0, 0), line.text, font=fnt)
|
|
line.size = (bbox[2] - bbox[0], bbox[3] - bbox[1])
|
|
line.allowed_width = allowed_width
|
|
|
|
hor_text_heights = [sum([line.size[1] + line_spacing for line in lines]) - line_spacing for lines in hor_texts]
|
|
ver_text_heights = [sum([line.size[1] + line_spacing for line in lines]) - line_spacing * len(lines) for lines in
|
|
ver_texts]
|
|
|
|
pad_top = max(hor_text_heights) + line_spacing * 2
|
|
|
|
result = Image.new("RGB", (im.width + pad_left, im.height + pad_top), "white")
|
|
result.paste(im, (pad_left, pad_top))
|
|
|
|
d = ImageDraw.Draw(result)
|
|
|
|
for col in range(cols):
|
|
x = pad_left + width * col + width / 2
|
|
y = pad_top / 2 - hor_text_heights[col] / 2
|
|
|
|
draw_texts(d, x, y, hor_texts[col], fnt, fontsize)
|
|
|
|
for row in range(rows):
|
|
x = pad_left / 2
|
|
y = pad_top + height * row + height / 2 - ver_text_heights[row] / 2
|
|
|
|
draw_texts(d, x, y, ver_texts[row], fnt, fontsize)
|
|
|
|
return result
|
|
|
|
|
|
def draw_prompt_matrix(im, width, height, all_prompts):
|
|
prompts = all_prompts[1:]
|
|
boundary = math.ceil(len(prompts) / 2)
|
|
|
|
prompts_horiz = prompts[:boundary]
|
|
prompts_vert = prompts[boundary:]
|
|
|
|
hor_texts = [[GridAnnotation(x, is_active=pos & (1 << i) != 0) for i, x in enumerate(prompts_horiz)] for pos in range(1 << len(prompts_horiz))]
|
|
ver_texts = [[GridAnnotation(x, is_active=pos & (1 << i) != 0) for i, x in enumerate(prompts_vert)] for pos in range(1 << len(prompts_vert))]
|
|
|
|
return draw_grid_annotations(im, width, height, hor_texts, ver_texts)
|
|
|
|
|
|
def resize_image(resize_mode, im, width, height, upscaler_name=None):
|
|
"""
|
|
Resizes an image with the specified resize_mode, width, and height.
|
|
|
|
Args:
|
|
resize_mode: The mode to use when resizing the image.
|
|
0: Resize the image to the specified width and height.
|
|
1: Resize the image to fill the specified width and height, maintaining the aspect ratio, and then center the image within the dimensions, cropping the excess.
|
|
2: Resize the image to fit within the specified width and height, maintaining the aspect ratio, and then center the image within the dimensions, filling empty with data from image.
|
|
im: The image to resize.
|
|
width: The width to resize the image to.
|
|
height: The height to resize the image to.
|
|
upscaler_name: The name of the upscaler to use. If not provided, defaults to opts.upscaler_for_img2img.
|
|
"""
|
|
|
|
upscaler_name = upscaler_name or opts.upscaler_for_img2img
|
|
|
|
def resize(im, w, h):
|
|
if upscaler_name is None or upscaler_name == "None" or im.mode == 'L':
|
|
return im.resize((w, h), resample=LANCZOS)
|
|
|
|
scale = max(w / im.width, h / im.height)
|
|
|
|
if scale > 1.0:
|
|
upscalers = [x for x in shared.sd_upscalers if x.name == upscaler_name]
|
|
assert len(upscalers) > 0, f"could not find upscaler named {upscaler_name}"
|
|
|
|
upscaler = upscalers[0]
|
|
im = upscaler.scaler.upscale(im, scale, upscaler.data_path)
|
|
|
|
if im.width != w or im.height != h:
|
|
im = im.resize((w, h), resample=LANCZOS)
|
|
|
|
return im
|
|
|
|
if resize_mode == 0:
|
|
res = resize(im, width, height)
|
|
|
|
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 = resize(im, src_w, src_h)
|
|
res = Image.new("RGB", (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 = resize(im, src_w, src_h)
|
|
res = Image.new("RGB", (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
|
|
|
|
|
|
invalid_filename_chars = '<>:"/\\|?*\n'
|
|
invalid_filename_prefix = ' '
|
|
invalid_filename_postfix = ' .'
|
|
re_nonletters = re.compile(r'[\s' + string.punctuation + ']+')
|
|
re_pattern = re.compile(r"(.*?)(?:\[([^\[\]]+)\]|$)")
|
|
re_pattern_arg = re.compile(r"(.*)<([^>]*)>$")
|
|
max_filename_part_length = 128
|
|
|
|
|
|
def sanitize_filename_part(text, replace_spaces=True):
|
|
if text is None:
|
|
return None
|
|
|
|
if replace_spaces:
|
|
text = text.replace(' ', '_')
|
|
|
|
text = text.translate({ord(x): '_' for x in invalid_filename_chars})
|
|
text = text.lstrip(invalid_filename_prefix)[:max_filename_part_length]
|
|
text = text.rstrip(invalid_filename_postfix)
|
|
return text
|
|
|
|
|
|
class FilenameGenerator:
|
|
replacements = {
|
|
'seed': lambda self: self.seed if self.seed is not None else '',
|
|
'steps': lambda self: self.p and self.p.steps,
|
|
'cfg': lambda self: self.p and self.p.cfg_scale,
|
|
'width': lambda self: self.image.width,
|
|
'height': lambda self: self.image.height,
|
|
'styles': lambda self: self.p and sanitize_filename_part(", ".join([style for style in self.p.styles if not style == "None"]) or "None", replace_spaces=False),
|
|
'sampler': lambda self: self.p and sanitize_filename_part(self.p.sampler_name, replace_spaces=False),
|
|
'model_hash': lambda self: getattr(self.p, "sd_model_hash", shared.sd_model.sd_model_hash),
|
|
'model_name': lambda self: sanitize_filename_part(shared.sd_model.sd_checkpoint_info.model_name, replace_spaces=False),
|
|
'date': lambda self: datetime.datetime.now().strftime('%Y-%m-%d'),
|
|
'datetime': lambda self, *args: self.datetime(*args), # accepts formats: [datetime], [datetime<Format>], [datetime<Format><Time Zone>]
|
|
'job_timestamp': lambda self: getattr(self.p, "job_timestamp", shared.state.job_timestamp),
|
|
'prompt': lambda self: sanitize_filename_part(self.prompt),
|
|
'prompt_no_styles': lambda self: self.prompt_no_style(),
|
|
'prompt_spaces': lambda self: sanitize_filename_part(self.prompt, replace_spaces=False),
|
|
'prompt_words': lambda self: self.prompt_words(),
|
|
}
|
|
default_time_format = '%Y%m%d%H%M%S'
|
|
|
|
def __init__(self, p, seed, prompt, image):
|
|
self.p = p
|
|
self.seed = seed
|
|
self.prompt = prompt
|
|
self.image = image
|
|
|
|
def prompt_no_style(self):
|
|
if self.p is None or self.prompt is None:
|
|
return None
|
|
|
|
prompt_no_style = self.prompt
|
|
for style in shared.prompt_styles.get_style_prompts(self.p.styles):
|
|
if len(style) > 0:
|
|
for part in style.split("{prompt}"):
|
|
prompt_no_style = prompt_no_style.replace(part, "").replace(", ,", ",").strip().strip(',')
|
|
|
|
prompt_no_style = prompt_no_style.replace(style, "").strip().strip(',').strip()
|
|
|
|
return sanitize_filename_part(prompt_no_style, replace_spaces=False)
|
|
|
|
def prompt_words(self):
|
|
words = [x for x in re_nonletters.split(self.prompt or "") if len(x) > 0]
|
|
if len(words) == 0:
|
|
words = ["empty"]
|
|
return sanitize_filename_part(" ".join(words[0:opts.directories_max_prompt_words]), replace_spaces=False)
|
|
|
|
def datetime(self, *args):
|
|
time_datetime = datetime.datetime.now()
|
|
|
|
time_format = args[0] if len(args) > 0 and args[0] != "" else self.default_time_format
|
|
try:
|
|
time_zone = pytz.timezone(args[1]) if len(args) > 1 else None
|
|
except pytz.exceptions.UnknownTimeZoneError as _:
|
|
time_zone = None
|
|
|
|
time_zone_time = time_datetime.astimezone(time_zone)
|
|
try:
|
|
formatted_time = time_zone_time.strftime(time_format)
|
|
except (ValueError, TypeError) as _:
|
|
formatted_time = time_zone_time.strftime(self.default_time_format)
|
|
|
|
return sanitize_filename_part(formatted_time, replace_spaces=False)
|
|
|
|
def apply(self, x):
|
|
res = ''
|
|
|
|
for m in re_pattern.finditer(x):
|
|
text, pattern = m.groups()
|
|
res += text
|
|
|
|
if pattern is None:
|
|
continue
|
|
|
|
pattern_args = []
|
|
while True:
|
|
m = re_pattern_arg.match(pattern)
|
|
if m is None:
|
|
break
|
|
|
|
pattern, arg = m.groups()
|
|
pattern_args.insert(0, arg)
|
|
|
|
fun = self.replacements.get(pattern.lower())
|
|
if fun is not None:
|
|
try:
|
|
replacement = fun(self, *pattern_args)
|
|
except Exception:
|
|
replacement = None
|
|
print(f"Error adding [{pattern}] to filename", file=sys.stderr)
|
|
print(traceback.format_exc(), file=sys.stderr)
|
|
|
|
if replacement is not None:
|
|
res += str(replacement)
|
|
continue
|
|
|
|
res += f'[{pattern}]'
|
|
|
|
return res
|
|
|
|
|
|
def get_next_sequence_number(path, basename):
|
|
"""
|
|
Determines and returns the next sequence number to use when saving an image in the specified directory.
|
|
|
|
The sequence starts at 0.
|
|
"""
|
|
result = -1
|
|
if basename != '':
|
|
basename = basename + "-"
|
|
|
|
prefix_length = len(basename)
|
|
for p in os.listdir(path):
|
|
if p.startswith(basename):
|
|
l = os.path.splitext(p[prefix_length:])[0].split('-') # splits the filename (removing the basename first if one is defined, so the sequence number is always the first element)
|
|
try:
|
|
result = max(int(l[0]), result)
|
|
except ValueError:
|
|
pass
|
|
|
|
return result + 1
|
|
|
|
|
|
def save_image(image, path, basename, seed=None, prompt=None, extension='png', info=None, short_filename=False, no_prompt=False, grid=False, pnginfo_section_name='parameters', p=None, existing_info=None, forced_filename=None, suffix="", save_to_dirs=None):
|
|
"""Save an image.
|
|
|
|
Args:
|
|
image (`PIL.Image`):
|
|
The image to be saved.
|
|
path (`str`):
|
|
The directory to save the image. Note, the option `save_to_dirs` will make the image to be saved into a sub directory.
|
|
basename (`str`):
|
|
The base filename which will be applied to `filename pattern`.
|
|
seed, prompt, short_filename,
|
|
extension (`str`):
|
|
Image file extension, default is `png`.
|
|
pngsectionname (`str`):
|
|
Specify the name of the section which `info` will be saved in.
|
|
info (`str` or `PngImagePlugin.iTXt`):
|
|
PNG info chunks.
|
|
existing_info (`dict`):
|
|
Additional PNG info. `existing_info == {pngsectionname: info, ...}`
|
|
no_prompt:
|
|
TODO I don't know its meaning.
|
|
p (`StableDiffusionProcessing`)
|
|
forced_filename (`str`):
|
|
If specified, `basename` and filename pattern will be ignored.
|
|
save_to_dirs (bool):
|
|
If true, the image will be saved into a subdirectory of `path`.
|
|
|
|
Returns: (fullfn, txt_fullfn)
|
|
fullfn (`str`):
|
|
The full path of the saved imaged.
|
|
txt_fullfn (`str` or None):
|
|
If a text file is saved for this image, this will be its full path. Otherwise None.
|
|
"""
|
|
namegen = FilenameGenerator(p, seed, prompt, image)
|
|
|
|
if save_to_dirs is None:
|
|
save_to_dirs = (grid and opts.grid_save_to_dirs) or (not grid and opts.save_to_dirs and not no_prompt)
|
|
|
|
if save_to_dirs:
|
|
dirname = namegen.apply(opts.directories_filename_pattern or "[prompt_words]").lstrip(' ').rstrip('\\ /')
|
|
path = os.path.join(path, dirname)
|
|
|
|
os.makedirs(path, exist_ok=True)
|
|
|
|
if forced_filename is None:
|
|
if short_filename or seed is None:
|
|
file_decoration = ""
|
|
elif opts.save_to_dirs:
|
|
file_decoration = opts.samples_filename_pattern or "[seed]"
|
|
else:
|
|
file_decoration = opts.samples_filename_pattern or "[seed]-[prompt_spaces]"
|
|
|
|
add_number = opts.save_images_add_number or file_decoration == ''
|
|
|
|
if file_decoration != "" and add_number:
|
|
file_decoration = "-" + file_decoration
|
|
|
|
file_decoration = namegen.apply(file_decoration) + suffix
|
|
|
|
if add_number:
|
|
basecount = get_next_sequence_number(path, basename)
|
|
fullfn = None
|
|
for i in range(500):
|
|
fn = f"{basecount + i:05}" if basename == '' else f"{basename}-{basecount + i:04}"
|
|
fullfn = os.path.join(path, f"{fn}{file_decoration}.{extension}")
|
|
if not os.path.exists(fullfn):
|
|
break
|
|
else:
|
|
fullfn = os.path.join(path, f"{file_decoration}.{extension}")
|
|
else:
|
|
fullfn = os.path.join(path, f"{forced_filename}.{extension}")
|
|
|
|
pnginfo = existing_info or {}
|
|
if info is not None:
|
|
pnginfo[pnginfo_section_name] = info
|
|
|
|
params = script_callbacks.ImageSaveParams(image, p, fullfn, pnginfo)
|
|
script_callbacks.before_image_saved_callback(params)
|
|
|
|
image = params.image
|
|
fullfn = params.filename
|
|
info = params.pnginfo.get(pnginfo_section_name, None)
|
|
|
|
def _atomically_save_image(image_to_save, filename_without_extension, extension):
|
|
# save image with .tmp extension to avoid race condition when another process detects new image in the directory
|
|
temp_file_path = filename_without_extension + ".tmp"
|
|
image_format = Image.registered_extensions()[extension]
|
|
|
|
if extension.lower() == '.png':
|
|
pnginfo_data = PngImagePlugin.PngInfo()
|
|
if opts.enable_pnginfo:
|
|
for k, v in params.pnginfo.items():
|
|
pnginfo_data.add_text(k, str(v))
|
|
|
|
image_to_save.save(temp_file_path, format=image_format, quality=opts.jpeg_quality, pnginfo=pnginfo_data)
|
|
|
|
elif extension.lower() in (".jpg", ".jpeg", ".webp"):
|
|
if image_to_save.mode == 'RGBA':
|
|
image_to_save = image_to_save.convert("RGB")
|
|
|
|
image_to_save.save(temp_file_path, format=image_format, quality=opts.jpeg_quality)
|
|
|
|
if opts.enable_pnginfo and info is not None:
|
|
exif_bytes = piexif.dump({
|
|
"Exif": {
|
|
piexif.ExifIFD.UserComment: piexif.helper.UserComment.dump(info or "", encoding="unicode")
|
|
},
|
|
})
|
|
|
|
piexif.insert(exif_bytes, temp_file_path)
|
|
else:
|
|
image_to_save.save(temp_file_path, format=image_format, quality=opts.jpeg_quality)
|
|
|
|
# atomically rename the file with correct extension
|
|
os.replace(temp_file_path, filename_without_extension + extension)
|
|
|
|
fullfn_without_extension, extension = os.path.splitext(params.filename)
|
|
_atomically_save_image(image, fullfn_without_extension, extension)
|
|
|
|
image.already_saved_as = fullfn
|
|
|
|
target_side_length = 4000
|
|
oversize = image.width > target_side_length or image.height > target_side_length
|
|
if opts.export_for_4chan and (oversize or os.stat(fullfn).st_size > 4 * 1024 * 1024):
|
|
ratio = image.width / image.height
|
|
|
|
if oversize and ratio > 1:
|
|
image = image.resize((target_side_length, image.height * target_side_length // image.width), LANCZOS)
|
|
elif oversize:
|
|
image = image.resize((image.width * target_side_length // image.height, target_side_length), LANCZOS)
|
|
|
|
_atomically_save_image(image, fullfn_without_extension, ".jpg")
|
|
|
|
if opts.save_txt and info is not None:
|
|
txt_fullfn = f"{fullfn_without_extension}.txt"
|
|
with open(txt_fullfn, "w", encoding="utf8") as file:
|
|
file.write(info + "\n")
|
|
else:
|
|
txt_fullfn = None
|
|
|
|
script_callbacks.image_saved_callback(params)
|
|
|
|
return fullfn, txt_fullfn
|
|
|
|
|
|
def read_info_from_image(image):
|
|
items = image.info or {}
|
|
|
|
geninfo = items.pop('parameters', None)
|
|
|
|
if "exif" in items:
|
|
exif = piexif.load(items["exif"])
|
|
exif_comment = (exif or {}).get("Exif", {}).get(piexif.ExifIFD.UserComment, b'')
|
|
try:
|
|
exif_comment = piexif.helper.UserComment.load(exif_comment)
|
|
except ValueError:
|
|
exif_comment = exif_comment.decode('utf8', errors="ignore")
|
|
|
|
items['exif comment'] = exif_comment
|
|
geninfo = exif_comment
|
|
|
|
for field in ['jfif', 'jfif_version', 'jfif_unit', 'jfif_density', 'dpi', 'exif',
|
|
'loop', 'background', 'timestamp', 'duration']:
|
|
items.pop(field, None)
|
|
|
|
if items.get("Software", None) == "NovelAI":
|
|
try:
|
|
json_info = json.loads(items["Comment"])
|
|
sampler = sd_samplers.samplers_map.get(json_info["sampler"], "Euler a")
|
|
|
|
geninfo = f"""{items["Description"]}
|
|
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("Error parsing NovelAI image generation parameters:", file=sys.stderr)
|
|
print(traceback.format_exc(), file=sys.stderr)
|
|
|
|
return geninfo, items
|
|
|
|
|
|
def image_data(data):
|
|
try:
|
|
image = Image.open(io.BytesIO(data))
|
|
textinfo, _ = read_info_from_image(image)
|
|
return textinfo, None
|
|
except Exception:
|
|
pass
|
|
|
|
try:
|
|
text = data.decode('utf8')
|
|
assert len(text) < 10000
|
|
return text, None
|
|
|
|
except Exception:
|
|
pass
|
|
|
|
return '', None
|
|
|
|
|
|
def flatten(img, bgcolor):
|
|
"""replaces transparency with bgcolor (example: "#ffffff"), returning an RGB mode image with no transparency"""
|
|
|
|
if img.mode == "RGBA":
|
|
background = Image.new('RGBA', img.size, bgcolor)
|
|
background.paste(img, mask=img)
|
|
img = background
|
|
|
|
return img.convert('RGB')
|