| from __future__ import annotations |
|
|
| import datetime |
|
|
| 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, ImageColor, PngImagePlugin |
| import string |
| import json |
| import hashlib |
|
|
| from modules import sd_samplers, shared, script_callbacks, errors |
| from modules.paths_internal import roboto_ttf_file |
| from modules.shared import opts |
|
|
| LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS) |
|
|
|
|
| def get_font(fontsize: int): |
| try: |
| return ImageFont.truetype(opts.font or roboto_ttf_file, fontsize) |
| except Exception: |
| return ImageFont.truetype(roboto_ttf_file, fontsize) |
|
|
|
|
| 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) |
| if rows > len(imgs): |
| rows = len(imgs) |
|
|
| 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, margin=0): |
|
|
| color_active = ImageColor.getcolor(opts.grid_text_active_color, 'RGB') |
| color_inactive = ImageColor.getcolor(opts.grid_text_inactive_color, 'RGB') |
| color_background = ImageColor.getcolor(opts.grid_background_color, 'RGB') |
|
|
| 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 draw_texts(drawing, draw_x, draw_y, lines, initial_fnt, initial_fontsize): |
| for line in 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) |
|
|
| 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), color_background) |
| 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 = 0 if sum(hor_text_heights) == 0 else max(hor_text_heights) + line_spacing * 2 |
|
|
| result = Image.new("RGB", (im.width + pad_left + margin * (cols-1), im.height + pad_top + margin * (rows-1)), color_background) |
|
|
| for row in range(rows): |
| for col in range(cols): |
| cell = im.crop((width * col, height * row, width * (col+1), height * (row+1))) |
| result.paste(cell, (pad_left + (width + margin) * col, pad_top + (height + margin) * row)) |
|
|
| d = ImageDraw.Draw(result) |
|
|
| for col in range(cols): |
| x = pad_left + (width + margin) * 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 + margin) * 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, margin=0): |
| 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, margin) |
|
|
|
|
| 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] |
| if len(upscalers) == 0: |
| upscaler = shared.sd_upscalers[0] |
| print(f"could not find upscaler named {upscaler_name or '<empty string>'}, using {upscaler.name} as a fallback") |
| else: |
| 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 |
| if fill_height > 0: |
| 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 |
| if fill_width > 0: |
| 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\r\t' |
| 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 |
| NOTHING_AND_SKIP_PREVIOUS_TEXT = object() |
|
|
|
|
| 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 '', |
| 'seed_first': lambda self: self.seed if self.p.batch_size == 1 else self.p.all_seeds[0], |
| 'seed_last': lambda self: NOTHING_AND_SKIP_PREVIOUS_TEXT if self.p.batch_size == 1 else self.p.all_seeds[-1], |
| '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.name_for_extra, replace_spaces=False), |
| 'date': lambda self: datetime.datetime.now().strftime('%Y-%m-%d'), |
| 'datetime': lambda self, *args: self.datetime(*args), |
| 'job_timestamp': lambda self: getattr(self.p, "job_timestamp", shared.state.job_timestamp), |
| 'prompt_hash': lambda self, *args: self.string_hash(self.prompt, *args), |
| 'negative_prompt_hash': lambda self, *args: self.string_hash(self.p.negative_prompt, *args), |
| 'full_prompt_hash': lambda self, *args: self.string_hash(f"{self.p.prompt} {self.p.negative_prompt}", *args), |
| '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(), |
| 'batch_number': lambda self: NOTHING_AND_SKIP_PREVIOUS_TEXT if self.p.batch_size == 1 or self.zip else self.p.batch_index + 1, |
| 'batch_size': lambda self: self.p.batch_size, |
| 'generation_number': lambda self: NOTHING_AND_SKIP_PREVIOUS_TEXT if (self.p.n_iter == 1 and self.p.batch_size == 1) or self.zip else self.p.iteration * self.p.batch_size + self.p.batch_index + 1, |
| 'hasprompt': lambda self, *args: self.hasprompt(*args), |
| 'clip_skip': lambda self: opts.data["CLIP_stop_at_last_layers"], |
| 'denoising': lambda self: self.p.denoising_strength if self.p and self.p.denoising_strength else NOTHING_AND_SKIP_PREVIOUS_TEXT, |
| 'user': lambda self: self.p.user, |
| 'vae_filename': lambda self: self.get_vae_filename(), |
| 'none': lambda self: '', |
| 'image_hash': lambda self, *args: self.image_hash(*args) |
| } |
| default_time_format = '%Y%m%d%H%M%S' |
|
|
| def __init__(self, p, seed, prompt, image, zip=False): |
| self.p = p |
| self.seed = seed |
| self.prompt = prompt |
| self.image = image |
| self.zip = zip |
|
|
| def get_vae_filename(self): |
| """Get the name of the VAE file.""" |
|
|
| import modules.sd_vae as sd_vae |
|
|
| if sd_vae.loaded_vae_file is None: |
| return "NoneType" |
|
|
| file_name = os.path.basename(sd_vae.loaded_vae_file) |
| split_file_name = file_name.split('.') |
| if len(split_file_name) > 1 and split_file_name[0] == '': |
| return split_file_name[1] |
| else: |
| return split_file_name[0] |
|
|
|
|
| def hasprompt(self, *args): |
| lower = self.prompt.lower() |
| if self.p is None or self.prompt is None: |
| return None |
| outres = "" |
| for arg in args: |
| if arg != "": |
| division = arg.split("|") |
| expected = division[0].lower() |
| default = division[1] if len(division) > 1 else "" |
| if lower.find(expected) >= 0: |
| outres = f'{outres}{expected}' |
| else: |
| outres = outres if default == "" else f'{outres}{default}' |
| return sanitize_filename_part(outres) |
|
|
| 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 style: |
| 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 x] |
| 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 (args 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: |
| time_zone = None |
|
|
| time_zone_time = time_datetime.astimezone(time_zone) |
| try: |
| formatted_time = time_zone_time.strftime(time_format) |
| except (ValueError, TypeError): |
| formatted_time = time_zone_time.strftime(self.default_time_format) |
|
|
| return sanitize_filename_part(formatted_time, replace_spaces=False) |
|
|
| def image_hash(self, *args): |
| length = int(args[0]) if (args and args[0] != "") else None |
| return hashlib.sha256(self.image.tobytes()).hexdigest()[0:length] |
|
|
| def string_hash(self, text, *args): |
| length = int(args[0]) if (args and args[0] != "") else 8 |
| return hashlib.sha256(text.encode()).hexdigest()[0:length] |
|
|
| def apply(self, x): |
| res = '' |
|
|
| for m in re_pattern.finditer(x): |
| text, pattern = m.groups() |
|
|
| if pattern is None: |
| res += text |
| 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 |
| errors.report(f"Error adding [{pattern}] to filename", exc_info=True) |
|
|
| if replacement == NOTHING_AND_SKIP_PREVIOUS_TEXT: |
| continue |
| elif replacement is not None: |
| res += text + str(replacement) |
| continue |
|
|
| res += f'{text}[{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 = f"{basename}-" |
|
|
| prefix_length = len(basename) |
| for p in os.listdir(path): |
| if p.startswith(basename): |
| parts = os.path.splitext(p[prefix_length:])[0].split('-') |
| try: |
| result = max(int(parts[0]), result) |
| except ValueError: |
| pass |
|
|
| return result + 1 |
|
|
|
|
| def save_image_with_geninfo(image, geninfo, filename, extension=None, existing_pnginfo=None, pnginfo_section_name='parameters'): |
| """ |
| Saves image to filename, including geninfo as text information for generation info. |
| For PNG images, geninfo is added to existing pnginfo dictionary using the pnginfo_section_name argument as key. |
| For JPG images, there's no dictionary and geninfo just replaces the EXIF description. |
| """ |
|
|
| if extension is None: |
| extension = os.path.splitext(filename)[1] |
|
|
| image_format = Image.registered_extensions()[extension] |
|
|
| if extension.lower() == '.png': |
| existing_pnginfo = existing_pnginfo or {} |
| if opts.enable_pnginfo: |
| existing_pnginfo[pnginfo_section_name] = geninfo |
|
|
| if opts.enable_pnginfo: |
| pnginfo_data = PngImagePlugin.PngInfo() |
| for k, v in (existing_pnginfo or {}).items(): |
| pnginfo_data.add_text(k, str(v)) |
| else: |
| pnginfo_data = None |
|
|
| image.save(filename, format=image_format, quality=opts.jpeg_quality, pnginfo=pnginfo_data) |
|
|
| elif extension.lower() in (".jpg", ".jpeg", ".webp"): |
| if image.mode == 'RGBA': |
| image = image.convert("RGB") |
| elif image.mode == 'I;16': |
| image = image.point(lambda p: p * 0.0038910505836576).convert("RGB" if extension.lower() == ".webp" else "L") |
|
|
| image.save(filename, format=image_format, quality=opts.jpeg_quality, lossless=opts.webp_lossless) |
|
|
| if opts.enable_pnginfo and geninfo is not None: |
| exif_bytes = piexif.dump({ |
| "Exif": { |
| piexif.ExifIFD.UserComment: piexif.helper.UserComment.dump(geninfo or "", encoding="unicode") |
| }, |
| }) |
|
|
| piexif.insert(exif_bytes, filename) |
| else: |
| image.save(filename, format=image_format, quality=opts.jpeg_quality) |
|
|
|
|
| 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 (image.height > 65535 or image.width > 65535) and extension.lower() in ("jpg", "jpeg") or (image.height > 16383 or image.width > 16383) and extension.lower() == "webp": |
| print('Image dimensions too large; saving as PNG') |
| extension = ".png" |
|
|
| 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]" |
|
|
| file_decoration = namegen.apply(file_decoration) + suffix |
|
|
| add_number = opts.save_images_add_number or file_decoration == '' |
|
|
| if file_decoration != "" and add_number: |
| file_decoration = f"-{file_decoration}" |
|
|
| 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 = f"{filename_without_extension}.tmp" |
|
|
| save_image_with_geninfo(image_to_save, info, temp_file_path, extension, existing_pnginfo=params.pnginfo, pnginfo_section_name=pnginfo_section_name) |
|
|
| os.replace(temp_file_path, filename_without_extension + extension) |
|
|
| fullfn_without_extension, extension = os.path.splitext(params.filename) |
| if hasattr(os, 'statvfs'): |
| max_name_len = os.statvfs(path).f_namemax |
| fullfn_without_extension = fullfn_without_extension[:max_name_len - max(4, len(extension))] |
| params.filename = fullfn_without_extension + extension |
| fullfn = params.filename |
| _atomically_save_image(image, fullfn_without_extension, extension) |
|
|
| image.already_saved_as = fullfn |
|
|
| oversize = image.width > opts.target_side_length or image.height > opts.target_side_length |
| if opts.export_for_4chan and (oversize or os.stat(fullfn).st_size > opts.img_downscale_threshold * 1024 * 1024): |
| ratio = image.width / image.height |
| resize_to = None |
| if oversize and ratio > 1: |
| resize_to = round(opts.target_side_length), round(image.height * opts.target_side_length / image.width) |
| elif oversize: |
| resize_to = round(image.width * opts.target_side_length / image.height), round(opts.target_side_length) |
|
|
| if resize_to is not None: |
| try: |
| |
| image = image.resize(resize_to, LANCZOS) |
| except Exception: |
| image = image.resize(resize_to) |
| try: |
| _atomically_save_image(image, fullfn_without_extension, ".jpg") |
| except Exception as e: |
| errors.display(e, "saving image as downscaled 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(f"{info}\n") |
| else: |
| txt_fullfn = None |
|
|
| script_callbacks.image_saved_callback(params) |
|
|
| return fullfn, txt_fullfn |
|
|
|
|
| IGNORED_INFO_KEYS = { |
| 'jfif', 'jfif_version', 'jfif_unit', 'jfif_density', 'dpi', 'exif', |
| 'loop', 'background', 'timestamp', 'duration', 'progressive', 'progression', |
| 'icc_profile', 'chromaticity', 'photoshop', |
| } |
|
|
|
|
| def read_info_from_image(image: Image.Image) -> tuple[str | None, dict]: |
| items = (image.info or {}).copy() |
|
|
| 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") |
|
|
| if exif_comment: |
| items['exif comment'] = exif_comment |
| geninfo = exif_comment |
|
|
| for field in IGNORED_INFO_KEYS: |
| 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: |
| errors.report("Error parsing NovelAI image generation parameters", exc_info=True) |
|
|
| return geninfo, items |
|
|
|
|
| def image_data(data): |
| import gradio as gr |
|
|
| 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 gr.update(), 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') |
|
|