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			731 lines
		
	
	
		
			28 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			731 lines
		
	
	
		
			28 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| import datetime
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| 
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| import pytz
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| import io
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| import math
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| import os
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| from collections import namedtuple
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| import re
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| 
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| import numpy as np
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| import piexif
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| import piexif.helper
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| from PIL import Image, ImageFont, ImageDraw, PngImagePlugin
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| import string
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| import json
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| import hashlib
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| 
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| from modules import sd_samplers, shared, script_callbacks, errors
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| from modules.paths_internal import roboto_ttf_file
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| from modules.shared import opts
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| 
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| import modules.sd_vae as sd_vae
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| 
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| LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS)
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| 
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| 
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| def get_font(fontsize: int):
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|     try:
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|         return ImageFont.truetype(opts.font or roboto_ttf_file, fontsize)
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|     except Exception:
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|         return ImageFont.truetype(roboto_ttf_file, fontsize)
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| 
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| 
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| def image_grid(imgs, batch_size=1, rows=None):
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|     if rows is None:
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|         if opts.n_rows > 0:
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|             rows = opts.n_rows
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|         elif opts.n_rows == 0:
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|             rows = batch_size
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|         elif opts.grid_prevent_empty_spots:
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|             rows = math.floor(math.sqrt(len(imgs)))
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|             while len(imgs) % rows != 0:
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|                 rows -= 1
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|         else:
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|             rows = math.sqrt(len(imgs))
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|             rows = round(rows)
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|     if rows > len(imgs):
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|         rows = len(imgs)
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| 
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|     cols = math.ceil(len(imgs) / rows)
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| 
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|     params = script_callbacks.ImageGridLoopParams(imgs, cols, rows)
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|     script_callbacks.image_grid_callback(params)
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| 
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|     w, h = imgs[0].size
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|     grid = Image.new('RGB', size=(params.cols * w, params.rows * h), color='black')
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| 
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|     for i, img in enumerate(params.imgs):
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|         grid.paste(img, box=(i % params.cols * w, i // params.cols * h))
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| 
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|     return grid
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| 
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| 
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| Grid = namedtuple("Grid", ["tiles", "tile_w", "tile_h", "image_w", "image_h", "overlap"])
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| 
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| 
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| def split_grid(image, tile_w=512, tile_h=512, overlap=64):
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|     w = image.width
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|     h = image.height
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| 
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|     non_overlap_width = tile_w - overlap
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|     non_overlap_height = tile_h - overlap
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| 
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|     cols = math.ceil((w - overlap) / non_overlap_width)
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|     rows = math.ceil((h - overlap) / non_overlap_height)
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| 
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|     dx = (w - tile_w) / (cols - 1) if cols > 1 else 0
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|     dy = (h - tile_h) / (rows - 1) if rows > 1 else 0
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| 
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|     grid = Grid([], tile_w, tile_h, w, h, overlap)
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|     for row in range(rows):
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|         row_images = []
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| 
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|         y = int(row * dy)
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| 
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|         if y + tile_h >= h:
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|             y = h - tile_h
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| 
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|         for col in range(cols):
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|             x = int(col * dx)
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| 
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|             if x + tile_w >= w:
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|                 x = w - tile_w
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| 
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|             tile = image.crop((x, y, x + tile_w, y + tile_h))
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| 
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|             row_images.append([x, tile_w, tile])
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| 
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|         grid.tiles.append([y, tile_h, row_images])
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| 
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|     return grid
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| 
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| 
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| def combine_grid(grid):
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|     def make_mask_image(r):
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|         r = r * 255 / grid.overlap
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|         r = r.astype(np.uint8)
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|         return Image.fromarray(r, 'L')
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| 
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|     mask_w = make_mask_image(np.arange(grid.overlap, dtype=np.float32).reshape((1, grid.overlap)).repeat(grid.tile_h, axis=0))
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|     mask_h = make_mask_image(np.arange(grid.overlap, dtype=np.float32).reshape((grid.overlap, 1)).repeat(grid.image_w, axis=1))
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| 
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|     combined_image = Image.new("RGB", (grid.image_w, grid.image_h))
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|     for y, h, row in grid.tiles:
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|         combined_row = Image.new("RGB", (grid.image_w, h))
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|         for x, w, tile in row:
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|             if x == 0:
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|                 combined_row.paste(tile, (0, 0))
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|                 continue
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| 
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|             combined_row.paste(tile.crop((0, 0, grid.overlap, h)), (x, 0), mask=mask_w)
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|             combined_row.paste(tile.crop((grid.overlap, 0, w, h)), (x + grid.overlap, 0))
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| 
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|         if y == 0:
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|             combined_image.paste(combined_row, (0, 0))
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|             continue
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| 
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|         combined_image.paste(combined_row.crop((0, 0, combined_row.width, grid.overlap)), (0, y), mask=mask_h)
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|         combined_image.paste(combined_row.crop((0, grid.overlap, combined_row.width, h)), (0, y + grid.overlap))
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| 
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|     return combined_image
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| 
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| 
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| class GridAnnotation:
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|     def __init__(self, text='', is_active=True):
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|         self.text = text
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|         self.is_active = is_active
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|         self.size = None
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| 
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| 
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| def draw_grid_annotations(im, width, height, hor_texts, ver_texts, margin=0):
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|     def wrap(drawing, text, font, line_length):
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|         lines = ['']
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|         for word in text.split():
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|             line = f'{lines[-1]} {word}'.strip()
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|             if drawing.textlength(line, font=font) <= line_length:
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|                 lines[-1] = line
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|             else:
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|                 lines.append(word)
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|         return lines
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| 
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|     def draw_texts(drawing, draw_x, draw_y, lines, initial_fnt, initial_fontsize):
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|         for line in lines:
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|             fnt = initial_fnt
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|             fontsize = initial_fontsize
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|             while drawing.multiline_textsize(line.text, font=fnt)[0] > line.allowed_width and fontsize > 0:
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|                 fontsize -= 1
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|                 fnt = get_font(fontsize)
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|             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")
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| 
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|             if not line.is_active:
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|                 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)
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| 
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|             draw_y += line.size[1] + line_spacing
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| 
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|     fontsize = (width + height) // 25
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|     line_spacing = fontsize // 2
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| 
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|     fnt = get_font(fontsize)
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| 
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|     color_active = (0, 0, 0)
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|     color_inactive = (153, 153, 153)
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| 
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|     pad_left = 0 if sum([sum([len(line.text) for line in lines]) for lines in ver_texts]) == 0 else width * 3 // 4
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| 
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|     cols = im.width // width
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|     rows = im.height // height
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| 
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|     assert cols == len(hor_texts), f'bad number of horizontal texts: {len(hor_texts)}; must be {cols}'
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|     assert rows == len(ver_texts), f'bad number of vertical texts: {len(ver_texts)}; must be {rows}'
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| 
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|     calc_img = Image.new("RGB", (1, 1), "white")
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|     calc_d = ImageDraw.Draw(calc_img)
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| 
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|     for texts, allowed_width in zip(hor_texts + ver_texts, [width] * len(hor_texts) + [pad_left] * len(ver_texts)):
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|         items = [] + texts
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|         texts.clear()
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| 
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|         for line in items:
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|             wrapped = wrap(calc_d, line.text, fnt, allowed_width)
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|             texts += [GridAnnotation(x, line.is_active) for x in wrapped]
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| 
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|         for line in texts:
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|             bbox = calc_d.multiline_textbbox((0, 0), line.text, font=fnt)
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|             line.size = (bbox[2] - bbox[0], bbox[3] - bbox[1])
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|             line.allowed_width = allowed_width
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| 
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|     hor_text_heights = [sum([line.size[1] + line_spacing for line in lines]) - line_spacing for lines in hor_texts]
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|     ver_text_heights = [sum([line.size[1] + line_spacing for line in lines]) - line_spacing * len(lines) for lines in ver_texts]
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| 
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|     pad_top = 0 if sum(hor_text_heights) == 0 else max(hor_text_heights) + line_spacing * 2
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| 
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|     result = Image.new("RGB", (im.width + pad_left + margin * (cols-1), im.height + pad_top + margin * (rows-1)), "white")
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| 
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|     for row in range(rows):
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|         for col in range(cols):
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|             cell = im.crop((width * col, height * row, width * (col+1), height * (row+1)))
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|             result.paste(cell, (pad_left + (width + margin) * col, pad_top + (height + margin) * row))
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| 
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|     d = ImageDraw.Draw(result)
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| 
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|     for col in range(cols):
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|         x = pad_left + (width + margin) * col + width / 2
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|         y = pad_top / 2 - hor_text_heights[col] / 2
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| 
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|         draw_texts(d, x, y, hor_texts[col], fnt, fontsize)
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| 
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|     for row in range(rows):
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|         x = pad_left / 2
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|         y = pad_top + (height + margin) * row + height / 2 - ver_text_heights[row] / 2
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| 
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|         draw_texts(d, x, y, ver_texts[row], fnt, fontsize)
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| 
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|     return result
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| 
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| 
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| def draw_prompt_matrix(im, width, height, all_prompts, margin=0):
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|     prompts = all_prompts[1:]
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|     boundary = math.ceil(len(prompts) / 2)
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| 
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|     prompts_horiz = prompts[:boundary]
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|     prompts_vert = prompts[boundary:]
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| 
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|     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))]
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|     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))]
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| 
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|     return draw_grid_annotations(im, width, height, hor_texts, ver_texts, margin)
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| 
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| 
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| def resize_image(resize_mode, im, width, height, upscaler_name=None):
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|     """
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|     Resizes an image with the specified resize_mode, width, and height.
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| 
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|     Args:
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|         resize_mode: The mode to use when resizing the image.
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|             0: Resize the image to the specified width and height.
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|             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.
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|             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.
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|         im: The image to resize.
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|         width: The width to resize the image to.
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|         height: The height to resize the image to.
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|         upscaler_name: The name of the upscaler to use. If not provided, defaults to opts.upscaler_for_img2img.
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|     """
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| 
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|     upscaler_name = upscaler_name or opts.upscaler_for_img2img
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| 
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|     def resize(im, w, h):
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|         if upscaler_name is None or upscaler_name == "None" or im.mode == 'L':
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|             return im.resize((w, h), resample=LANCZOS)
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| 
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|         scale = max(w / im.width, h / im.height)
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| 
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|         if scale > 1.0:
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|             upscalers = [x for x in shared.sd_upscalers if x.name == upscaler_name]
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|             if len(upscalers) == 0:
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|                 upscaler = shared.sd_upscalers[0]
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|                 print(f"could not find upscaler named {upscaler_name or '<empty string>'}, using {upscaler.name} as a fallback")
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|             else:
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|                 upscaler = upscalers[0]
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| 
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|             im = upscaler.scaler.upscale(im, scale, upscaler.data_path)
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| 
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|         if im.width != w or im.height != h:
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|             im = im.resize((w, h), resample=LANCZOS)
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| 
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|         return im
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| 
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|     if resize_mode == 0:
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|         res = resize(im, width, height)
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| 
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|     elif resize_mode == 1:
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|         ratio = width / height
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|         src_ratio = im.width / im.height
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| 
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|         src_w = width if ratio > src_ratio else im.width * height // im.height
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|         src_h = height if ratio <= src_ratio else im.height * width // im.width
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| 
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|         resized = resize(im, src_w, src_h)
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|         res = Image.new("RGB", (width, height))
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|         res.paste(resized, box=(width // 2 - src_w // 2, height // 2 - src_h // 2))
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| 
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|     else:
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|         ratio = width / height
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|         src_ratio = im.width / im.height
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| 
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|         src_w = width if ratio < src_ratio else im.width * height // im.height
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|         src_h = height if ratio >= src_ratio else im.height * width // im.width
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| 
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|         resized = resize(im, src_w, src_h)
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|         res = Image.new("RGB", (width, height))
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|         res.paste(resized, box=(width // 2 - src_w // 2, height // 2 - src_h // 2))
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| 
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|         if ratio < src_ratio:
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|             fill_height = height // 2 - src_h // 2
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|             res.paste(resized.resize((width, fill_height), box=(0, 0, width, 0)), box=(0, 0))
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|             res.paste(resized.resize((width, fill_height), box=(0, resized.height, width, resized.height)), box=(0, fill_height + src_h))
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|         elif ratio > src_ratio:
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|             fill_width = width // 2 - src_w // 2
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|             res.paste(resized.resize((fill_width, height), box=(0, 0, 0, height)), box=(0, 0))
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|             res.paste(resized.resize((fill_width, height), box=(resized.width, 0, resized.width, height)), box=(fill_width + src_w, 0))
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| 
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|     return res
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| 
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| 
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| invalid_filename_chars = '<>:"/\\|?*\n'
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| invalid_filename_prefix = ' '
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| invalid_filename_postfix = ' .'
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| re_nonletters = re.compile(r'[\s' + string.punctuation + ']+')
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| re_pattern = re.compile(r"(.*?)(?:\[([^\[\]]+)\]|$)")
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| re_pattern_arg = re.compile(r"(.*)<([^>]*)>$")
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| max_filename_part_length = 128
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| NOTHING_AND_SKIP_PREVIOUS_TEXT = object()
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| 
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| 
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| def sanitize_filename_part(text, replace_spaces=True):
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|     if text is None:
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|         return None
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| 
 | |
|     if replace_spaces:
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|         text = text.replace(' ', '_')
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| 
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|     text = text.translate({ord(x): '_' for x in invalid_filename_chars})
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|     text = text.lstrip(invalid_filename_prefix)[:max_filename_part_length]
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|     text = text.rstrip(invalid_filename_postfix)
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|     return text
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| 
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| 
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| class FilenameGenerator:
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|     def get_vae_filename(self): #get the name of the VAE file.
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|         if sd_vae.loaded_vae_file is None:
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|             return "NoneType"
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|         file_name = os.path.basename(sd_vae.loaded_vae_file)
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|         split_file_name = file_name.split('.')
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|         if len(split_file_name) > 1 and split_file_name[0] == '':
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|             return split_file_name[1] # if the first character of the filename is "." then [1] is obtained.
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|         else:
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|             return split_file_name[0]
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| 
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|     replacements = {
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|         'seed': lambda self: self.seed if self.seed is not None else '',
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|         'seed_first': lambda self: self.seed if self.p.batch_size == 1 else self.p.all_seeds[0],
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|         'seed_last': lambda self: NOTHING_AND_SKIP_PREVIOUS_TEXT if self.p.batch_size == 1 else self.p.all_seeds[-1],
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|         'steps': lambda self:  self.p and self.p.steps,
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|         'cfg': lambda self: self.p and self.p.cfg_scale,
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|         'width': lambda self: self.image.width,
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|         'height': lambda self: self.image.height,
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|         '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),
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|         'sampler': lambda self: self.p and sanitize_filename_part(self.p.sampler_name, replace_spaces=False),
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|         'model_hash': lambda self: getattr(self.p, "sd_model_hash", shared.sd_model.sd_model_hash),
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|         'model_name': lambda self: sanitize_filename_part(shared.sd_model.sd_checkpoint_info.model_name, replace_spaces=False),
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|         'date': lambda self: datetime.datetime.now().strftime('%Y-%m-%d'),
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|         'datetime': lambda self, *args: self.datetime(*args),  # accepts formats: [datetime], [datetime<Format>], [datetime<Format><Time Zone>]
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|         'job_timestamp': lambda self: getattr(self.p, "job_timestamp", shared.state.job_timestamp),
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|         'prompt_hash': lambda self: hashlib.sha256(self.prompt.encode()).hexdigest()[0:8],
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|         'prompt': lambda self: sanitize_filename_part(self.prompt),
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|         'prompt_no_styles': lambda self: self.prompt_no_style(),
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|         'prompt_spaces': lambda self: sanitize_filename_part(self.prompt, replace_spaces=False),
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|         'prompt_words': lambda self: self.prompt_words(),
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|         'batch_number': lambda self: NOTHING_AND_SKIP_PREVIOUS_TEXT if self.p.batch_size == 1 or self.zip else self.p.batch_index + 1,
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|         'batch_size': lambda self: self.p.batch_size,
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|         '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),  # accepts formats:[hasprompt<prompt1|default><prompt2>..]
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|         'clip_skip': lambda self: opts.data["CLIP_stop_at_last_layers"],
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|         'denoising': lambda self: self.p.denoising_strength if self.p and self.p.denoising_strength else NOTHING_AND_SKIP_PREVIOUS_TEXT,
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|         'vae_filename': lambda self: self.get_vae_filename(),
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| 
 | |
|     }
 | |
|     default_time_format = '%Y%m%d%H%M%S'
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| 
 | |
|     def __init__(self, p, seed, prompt, image, zip=False):
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|         self.p = p
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|         self.seed = seed
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|         self.prompt = prompt
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|         self.image = image
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|         self.zip = zip
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| 
 | |
|     def hasprompt(self, *args):
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|         lower = self.prompt.lower()
 | |
|         if self.p is None or self.prompt is None:
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|             return None
 | |
|         outres = ""
 | |
|         for arg in args:
 | |
|             if arg != "":
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|                 division = arg.split("|")
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|                 expected = division[0].lower()
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|                 default = division[1] if len(division) > 1 else ""
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|                 if lower.find(expected) >= 0:
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|                     outres = f'{outres}{expected}'
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|                 else:
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|                     outres = outres if default == "" else f'{outres}{default}'
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|         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 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('-')  # splits the filename (removing the basename first if one is defined, so the sequence number is always the first element)
 | |
|             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):
 | |
|     if extension is None:
 | |
|         extension = os.path.splitext(filename)[1]
 | |
| 
 | |
|     image_format = Image.registered_extensions()[extension]
 | |
| 
 | |
|     if extension.lower() == '.png':
 | |
|         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 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 = f"-{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 = f"{filename_without_extension}.tmp"
 | |
| 
 | |
|         save_image_with_geninfo(image_to_save, info, temp_file_path, extension, params.pnginfo)
 | |
| 
 | |
|         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
 | |
| 
 | |
|         if oversize and ratio > 1:
 | |
|             image = image.resize((round(opts.target_side_length), round(image.height * opts.target_side_length / image.width)), LANCZOS)
 | |
|         elif oversize:
 | |
|             image = image.resize((round(image.width * opts.target_side_length / image.height), round(opts.target_side_length)), LANCZOS)
 | |
| 
 | |
|         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
 | |
| 
 | |
| 
 | |
| 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")
 | |
| 
 | |
|         if exif_comment:
 | |
|             items['exif comment'] = exif_comment
 | |
|             geninfo = exif_comment
 | |
| 
 | |
|     for field in ['jfif', 'jfif_version', 'jfif_unit', 'jfif_density', 'dpi', 'exif',
 | |
|                     'loop', 'background', 'timestamp', 'duration', 'progressive', 'progression',
 | |
|                     'icc_profile', 'chromaticity']:
 | |
|         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')
 | 
