Delete utils directory
This commit is contained in:
smthemex
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style_list = [
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{
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"name": "No_style",
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"prompt": "{prompt}8k, RAW photo, best quality",
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"negative_prompt": "",
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},
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{
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"name": "Realistic",
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"prompt": "{prompt}8k, RAW photo, best quality, masterpiece, ultra high res, (photorealistic:1.4), golden hour, dramatic shadows,uhd, high quality, dramatic, cinematic",
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"negative_prompt": "(worst quality, low quality, normal quality, lowres), (bad teeth, deformed teeth, deformed lips), (bad proportions), (deformed eyes, bad eyes), (deformed face, ugly face), (deformed hands,fused fingers), morbid, mutilated, mutation, disfigured",
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},
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{
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"name": "Japanese_Anime",
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"prompt": "{prompt}anime artwork illustrating,best quality, high resolution, (Anime Style, Manga Style:1.3), line art, webtoon, manhua, hand drawn, defined lines, simple shades, Linear compositions, Digital art",
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"negative_prompt": "lowres,text, error, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry",
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},
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{
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"name": "Digital_Oil_Painting",
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"prompt": "{prompt} (Extremely Detailed Oil Painting:1.2), glow effects, godrays, Hand drawn, render, 8k, octane render, cinema 4d, blender,atmospheric 4k ultra detailed, cinematic sensual, Sharp focus, humorous illustration",
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"negative_prompt": "anime, cartoon, graphic, text, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured, lowres, error, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry",
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},
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{
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"name": "Pixar_Disney_Character",
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"prompt": "Create a Disney Pixar 3D style illustration on {prompt} The scene is vibrant, motivational, filled with vivid colors and a sense of wonder",
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"negative_prompt": "lowres, text, bad eyes, bad legs, error,extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, blurry, grayscale, noisy, sloppy, messy, grainy,ultra textured,",
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},
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{
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"name": "Photographic",
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"prompt": "cinematic photo {prompt} Hyperrealistic, Hyperdetailed, detailed skin, matte skin, soft lighting, realistic, best quality, ultra realistic, 8k, golden ratio, Intricate, High Detail, film photography, soft focus",
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"negative_prompt": "drawing, painting, crayon, sketch, graphite, impressionist, noisy, blurry, soft, deformed, ugly, lowres, text, error, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username",
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},
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{
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"name": "Comic_book",
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"prompt": "comic {prompt} graphic illustration, comic art, graphic novel art, vibrant, highly detailed",
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"negative_prompt": "photograph, deformed, glitch, noisy, realistic, stock photo, lowres,text, error,extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry",
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},
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{
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"name": "Line_art",
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"prompt": "line art drawing {prompt} professional, sleek, modern, minimalist, graphic, line art, vector graphics",
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"negative_prompt": "photorealistic, 35mm film, deformed, glitch, blurry, noisy, off-center, deformed, cross-eyed, closed eyes,ugly, disfigured, mutated, realism, realistic, impressionism, expressionism,acrylic, lowres, text, error,extra digit, fewer digits, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username",
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},
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{
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"name": "Black_and_White_Film_Noir",
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"prompt": "{prompt} (b&w, Monochromatic, Film Photography:1.3), film noir, analog style, soft lighting, subsurface scattering,heavy shadow, masterpiece, best quality",
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"negative_prompt": "anime, photorealistic, 35mm film, deformed, glitch, blurry, noisy, off-center, deformed, cross-eyed, closed eyes,ugly, disfigured, mutated, impressionism, expressionism,acrylic, lowres,text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username",
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},
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{
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"name": "Isometric_Rooms",
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"prompt": "Tiny cute isometric {prompt} in a cutaway box, soft smooth lighting, soft colors, 100mm lens, 3d blender render",
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"negative_prompt": "photorealistic,35mm film,deformed,glitch,blurry,noisy,off-center,deformed,cross-eyed,closed eyes,ugly,disfigured,mutated,realism,realistic,impressionism,expressionism,acrylic,lowres,text,error,extra digit,fewer digits,cropped, worst quality, low quality, normal quality, jpeg artifacts, signature,watermark, username",
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},
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]
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styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in style_list}
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-349
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import torch
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import numpy as np
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from PIL import Image,ImageOps,ImageDraw
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MAX_COLORS = 12
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import os
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import random
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dir_path = os.path.dirname(os.path.abspath(__file__))
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path_dir = os.path.dirname(dir_path)
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file_path = os.path.dirname(path_dir)
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#print(dir_path,file_path)
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def get_random_bool():
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return random.choice([True, False])
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def add_white_border(input_image, border_width=10):
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"""
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为PIL图像添加指定宽度的白色边框。
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:param input_image: PIL图像对象
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:param border_width: 边框宽度（单位：像素）
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:return: 带有白色边框的PIL图像对象
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"""
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border_color = 'white' # 白色边框
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# 添加边框
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img_with_border = ImageOps.expand(input_image, border=border_width, fill=border_color)
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return img_with_border
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def process_mulline_text(draw, text, font, max_width):
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"""
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Draw the text on an image with word wrapping.
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"""
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lines = [] # Store the lines of text here
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words = text.split()
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# Start building lines of text, and wrap when necessary
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current_line = ""
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for word in words:
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test_line = f"{current_line} {word}".strip()
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# Check the width of the line with this word added
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bbox = draw.textbbox((0, 0), test_line, font=font)
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text_left, text_top, text_right, text_bottom = bbox
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width, _ = (text_right - text_left, text_bottom - text_top)
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if width <= max_width:
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# If it fits, add this word to the current line
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current_line = test_line
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else:
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# If not, store the line and start a new one
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lines.append(current_line)
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current_line = word
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# Add the last line
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lines.append(current_line)
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return lines
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def add_caption(image, text, position = "bottom-mid", font = None, text_color= 'black', bg_color = (255, 255, 255) , bg_opacity = 200):
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if text == "":
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return image
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image = image.convert("RGBA")
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draw = ImageDraw.Draw(image)
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width, height = image.size
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lines = process_mulline_text(draw,text,font,width)
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text_positions = []
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maxwidth = 0
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for ind, line in enumerate(lines[::-1]):
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bbox = draw.textbbox((0, 0), line, font=font)
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text_left, text_top, text_right, text_bottom = bbox
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text_width, text_height = (text_right - text_left, text_bottom - text_top)
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if position == 'bottom-right':
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text_position = (width - text_width - 10, height - (text_height + 20))
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elif position == 'bottom-left':
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text_position = (10, height - (text_height + 20))
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elif position == 'bottom-mid':
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text_position = ((width - text_width) // 2, height - (text_height + 20) ) # 居中文本
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height = text_position[1]
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maxwidth = max(maxwidth,text_width)
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text_positions.append(text_position)
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rectpos = (width - maxwidth) // 2
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rectangle_position = [rectpos - 5, text_positions[-1][1] - 5, rectpos + maxwidth + 5, text_positions[0][1] + text_height + 5]
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image_with_transparency = Image.new('RGBA', image.size)
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draw_with_transparency = ImageDraw.Draw(image_with_transparency)
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draw_with_transparency.rectangle(rectangle_position, fill=bg_color + (bg_opacity,))
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image.paste(Image.alpha_composite(image.convert('RGBA'), image_with_transparency))
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#print(ind,text_position)
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draw = ImageDraw.Draw(image)
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for ind, line in enumerate(lines[::-1]):
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text_position = text_positions[ind]
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draw.text(text_position, line, fill=text_color, font=font)
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return image.convert('RGB')
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def get_comic(images,types = "4panel",captions = [],font = None,pad_image = None):
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font_check_path = os.path.join(path_dir,"images","pad_images.png")
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if pad_image == None:
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pad_image = Image.open(font_check_path)
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if types == "No typesetting (default)":
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return images
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elif types == "Four Pannel":
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return get_comic_4panel(images,captions,font,pad_image)
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else: # "Classic Comic Style"
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return get_comic_classical(images,captions,font,pad_image)
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def get_caption_group(images_groups,captions = []):
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caption_groups = []
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for i in range(len(images_groups)):
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length = len(images_groups[i])
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caption_groups.append(captions[:length])
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captions = captions[length:]
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if len(caption_groups[-1]) < len(images_groups[-1]):
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caption_groups[-1] = caption_groups[-1] + [""] * (len(images_groups[-1]) - len(caption_groups[-1]))
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return caption_groups
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def get_comic_classical(images,captions = None,font = None,pad_image = None):
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if pad_image == None:
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raise ValueError("pad_image is None")
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images = [add_white_border(image) for image in images]
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pad_image = pad_image.resize(images[0].size, Image.LANCZOS)
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images_groups = distribute_images2(images,pad_image)
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#print(images_groups)
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if captions != None:
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captions_groups = get_caption_group(images_groups,captions)
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# print(images_groups)
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row_images = []
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for ind, img_group in enumerate(images_groups):
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row_images.append(get_row_image2(img_group ,captions= captions_groups[ind] if captions != None else None,font = font))
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return [combine_images_vertically_with_resize(row_images)]
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def get_comic_4panel(images,captions = [],font = None,pad_image = None):
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if pad_image == None:
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raise ValueError("pad_image is None")
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pad_image = pad_image.resize(images[0].size, Image.LANCZOS)
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images = [add_white_border(image) for image in images]
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assert len(captions) == len(images)
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for i,caption in enumerate(captions):
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images[i] = add_caption(images[i],caption,font = font)
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images_nums = len(images)
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pad_nums = int((4 - images_nums % 4) % 4)
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images = images + [pad_image for _ in range(pad_nums)]
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comics = []
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assert len(images)%4 == 0
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for i in range(len(images)//4):
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comics.append(combine_images_vertically_with_resize([combine_images_horizontally(images[i*4:i*4+2]), combine_images_horizontally(images[i*4+2:i*4+4])]))
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return comics
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def get_row_image(images):
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row_image_arr = []
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if len(images)>3:
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stack_img_nums = (len(images) - 2)//2
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else:
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stack_img_nums = 0
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while(len(images)>0):
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if stack_img_nums <=0:
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row_image_arr.append(images[0])
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images = images[1:]
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elif len(images)>stack_img_nums*2:
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if get_random_bool():
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row_image_arr.append(concat_images_vertically_and_scale(images[:2]))
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images = images[2:]
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stack_img_nums -=1
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else:
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row_image_arr.append(images[0])
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images = images[1:]
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else:
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row_image_arr.append(concat_images_vertically_and_scale(images[:2]))
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images = images[2:]
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stack_img_nums-=1
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return combine_images_horizontally(row_image_arr)
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def get_row_image2(images,captions = None, font = None):
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row_image_arr = []
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if len(images)== 6:
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sequence_list = [1,1,2,2]
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elif len(images)== 4:
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sequence_list = [1,1,2]
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else:
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raise ValueError("images nums is not 4 or 6 found",len(images))
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random.shuffle(sequence_list)
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index = 0
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for length in sequence_list:
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if length == 1:
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if captions != None:
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images_tmp = add_caption(images[0],text = captions[index],font= font)
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else:
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images_tmp = images[0]
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row_image_arr.append( images_tmp)
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images = images[1:]
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index +=1
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elif length == 2:
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row_image_arr.append(concat_images_vertically_and_scale(images[:2]))
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images = images[2:]
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index +=2
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return combine_images_horizontally(row_image_arr)
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def concat_images_vertically_and_scale(images,scale_factor=2):
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# 加载所有图像
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# 确保所有图像的宽度一致
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widths = [img.width for img in images]
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if not all(width == widths[0] for width in widths):
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raise ValueError('All images must have the same width.')
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# 计算总高度
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total_height = sum(img.height for img in images)
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# 创建新的图像，宽度与原图相同，高度为所有图像高度之和
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max_width = max(widths)
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concatenated_image = Image.new('RGB', (max_width, total_height))
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# 竖直拼接图像
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current_height = 0
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for img in images:
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concatenated_image.paste(img, (0, current_height))
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current_height += img.height
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# 缩放图像为1/n高度
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new_height = concatenated_image.height // scale_factor
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new_width = concatenated_image.width // scale_factor
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resized_image = concatenated_image.resize((new_width, new_height), Image.LANCZOS)
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return resized_image
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def combine_images_horizontally(images):
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# 读取所有图片并存入列表
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# 获取每幅图像的宽度和高度
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widths, heights = zip(*(i.size for i in images))
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# 计算总宽度和最大高度
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total_width = sum(widths)
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max_height = max(heights)
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# 创建新的空白图片，用于拼接
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new_im = Image.new('RGB', (total_width, max_height))
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# 将图片横向拼接
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x_offset = 0
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for im in images:
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new_im.paste(im, (x_offset, 0))
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x_offset += im.width
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return new_im
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def combine_images_vertically_with_resize(images):
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# 获取所有图片的宽度和高度
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widths, heights = zip(*(i.size for i in images))
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# 确定新图片的宽度，即所有图片中最小的宽度
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min_width = min(widths)
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# 调整图片尺寸以保持宽度一致，长宽比不变
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resized_images = []
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for img in images:
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# 计算新高度保持图片长宽比
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new_height = int(min_width * img.height / img.width)
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# 调整图片大小
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resized_img = img.resize((min_width, new_height), Image.LANCZOS)
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resized_images.append(resized_img)
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# 计算所有调整尺寸后图片的总高度
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total_height = sum(img.height for img in resized_images)
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# 创建一个足够宽和高的新图片对象
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new_im = Image.new('RGB', (min_width, total_height))
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# 竖直拼接图片
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y_offset = 0
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for im in resized_images:
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new_im.paste(im, (0, y_offset))
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y_offset += im.height
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return new_im
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def distribute_images2(images, pad_image):
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groups = []
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remaining = len(images)
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if len(images) <= 8:
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group_sizes = [4]
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else:
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group_sizes = [4, 6]
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size_index = 0
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while remaining > 0:
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size = group_sizes[size_index%len(group_sizes)]
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if remaining < size and remaining < min(group_sizes):
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size = min(group_sizes)
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if remaining > size:
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new_group = images[-remaining: -remaining + size]
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else:
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new_group = images[-remaining:]
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groups.append(new_group)
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size_index += 1
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remaining -= size
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#print(remaining,groups)
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groups[-1] = groups[-1] + [pad_image for _ in range(-remaining)]
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return groups
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def distribute_images(images, group_sizes=(4, 3, 2)):
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groups = []
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remaining = len(images)
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while remaining > 0:
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# 优先分配最大组（4张图片），再考虑3张，最后处理2张
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for size in sorted(group_sizes, reverse=True):
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# 如果剩下的图片数量大于等于当前组大小，或者为图片总数时（也就是第一次迭代）
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# 开始创建新组
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if remaining >= size or remaining == len(images):
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if remaining > size:
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new_group = images[-remaining: -remaining + size]
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else:
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new_group = images[-remaining:]
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groups.append(new_group)
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remaining -= size
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break
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# 如果剩下的图片少于最小的组大小（2张）并且已经有组了，就把剩下的图片加到最后一个组
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elif remaining < min(group_sizes) and groups:
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groups[-1].extend(images[-remaining:])
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remaining = 0
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return groups
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def create_binary_matrix(img_arr, target_color):
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mask = np.all(img_arr == target_color, axis=-1)
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binary_matrix = mask.astype(int)
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return binary_matrix
|
||||
|
||||
def preprocess_mask(mask_, h, w, device):
|
||||
mask = np.array(mask_)
|
||||
mask = mask.astype(np.float32)
|
||||
mask = mask[None, None]
|
||||
mask[mask < 0.5] = 0
|
||||
mask[mask >= 0.5] = 1
|
||||
mask = torch.from_numpy(mask).to(device)
|
||||
mask = torch.nn.functional.interpolate(mask, size=(h, w), mode='nearest')
|
||||
return mask
|
||||
|
||||
Reference in New Issue
Block a user