jacktheporsche's picture
Added Files
04c50e9 verified
raw
history blame
16.2 kB
from email.mime import image
import torch
import base64
import gradio as gr
import numpy as np
from PIL import Image,ImageOps,ImageDraw, ImageFont
from io import BytesIO
import random
MAX_COLORS = 12
def get_random_bool():
return random.choice([True, False])
def add_white_border(input_image, border_width=10):
"""
为PIL图像添加指定宽度的白色边框。
:param input_image: PIL图像对象
:param border_width: 边框宽度(单位:像素)
:return: 带有白色边框的PIL图像对象
"""
border_color = 'white' # 白色边框
# 添加边框
img_with_border = ImageOps.expand(input_image, border=border_width, fill=border_color)
return img_with_border
def process_mulline_text(draw, text, font, max_width):
"""
Draw the text on an image with word wrapping.
"""
lines = [] # Store the lines of text here
words = text.split()
# Start building lines of text, and wrap when necessary
current_line = ""
for word in words:
test_line = f"{current_line} {word}".strip()
# Check the width of the line with this word added
width, _ = draw.textsize(test_line, font=font)
if width <= max_width:
# If it fits, add this word to the current line
current_line = test_line
else:
# If not, store the line and start a new one
lines.append(current_line)
current_line = word
# Add the last line
lines.append(current_line)
return lines
def add_caption(image, text, position = "bottom-mid", font = None, text_color= 'black', bg_color = (255, 255, 255) , bg_opacity = 200):
if text == "":
return image
image = image.convert("RGBA")
draw = ImageDraw.Draw(image)
width, height = image.size
lines = process_mulline_text(draw,text,font,width)
text_positions = []
maxwidth = 0
for ind, line in enumerate(lines[::-1]):
text_width, text_height = draw.textsize(line, font=font)
if position == 'bottom-right':
text_position = (width - text_width - 10, height - (text_height + 20))
elif position == 'bottom-left':
text_position = (10, height - (text_height + 20))
elif position == 'bottom-mid':
text_position = ((width - text_width) // 2, height - (text_height + 20) ) # 居中文本
height = text_position[1]
maxwidth = max(maxwidth,text_width)
text_positions.append(text_position)
rectpos = (width - maxwidth) // 2
rectangle_position = [rectpos - 5, text_positions[-1][1] - 5, rectpos + maxwidth + 5, text_positions[0][1] + text_height + 5]
image_with_transparency = Image.new('RGBA', image.size)
draw_with_transparency = ImageDraw.Draw(image_with_transparency)
draw_with_transparency.rectangle(rectangle_position, fill=bg_color + (bg_opacity,))
image.paste(Image.alpha_composite(image.convert('RGBA'), image_with_transparency))
print(ind,text_position)
draw = ImageDraw.Draw(image)
for ind, line in enumerate(lines[::-1]):
text_position = text_positions[ind]
draw.text(text_position, line, fill=text_color, font=font)
return image.convert('RGB')
def get_comic(images,types = "4panel",captions = [],font = None,pad_image = None):
if pad_image == None:
pad_image = Image.open("./images/pad_images.png")
if font == None:
font = ImageFont.truetype("./fonts/Inkfree.ttf", int(30 * images[0].size[1] / 1024))
if types == "No typesetting (default)":
return images
elif types == "Four Pannel":
return get_comic_4panel(images,captions,font,pad_image)
else: # "Classic Comic Style"
return get_comic_classical(images,captions,font,pad_image)
def get_caption_group(images_groups,captions = []):
caption_groups = []
for i in range(len(images_groups)):
length = len(images_groups[i])
caption_groups.append(captions[:length])
captions = captions[length:]
if len(caption_groups[-1]) < len(images_groups[-1]):
caption_groups[-1] = caption_groups[-1] + [""] * (len(images_groups[-1]) - len(caption_groups[-1]))
return caption_groups
def get_comic_classical(images,captions = None,font = None,pad_image = None):
if pad_image == None:
raise ValueError("pad_image is None")
images = [add_white_border(image) for image in images]
pad_image = pad_image.resize(images[0].size, Image.ANTIALIAS)
images_groups = distribute_images2(images,pad_image)
print(images_groups)
if captions != None:
captions_groups = get_caption_group(images_groups,captions)
# print(images_groups)
row_images = []
for ind, img_group in enumerate(images_groups):
row_images.append(get_row_image2(img_group ,captions= captions_groups[ind] if captions != None else None,font = font))
return [combine_images_vertically_with_resize(row_images)]
def get_comic_4panel(images,captions = [],font = None,pad_image = None):
if pad_image == None:
raise ValueError("pad_image is None")
pad_image = pad_image.resize(images[0].size, Image.ANTIALIAS)
images = [add_white_border(image) for image in images]
assert len(captions) == len(images)
for i,caption in enumerate(captions):
images[i] = add_caption(images[i],caption,font = font)
images_nums = len(images)
pad_nums = int((4 - images_nums % 4) % 4)
images = images + [pad_image for _ in range(pad_nums)]
comics = []
assert len(images)%4 == 0
for i in range(len(images)//4):
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])]))
return comics
def get_row_image(images):
row_image_arr = []
if len(images)>3:
stack_img_nums = (len(images) - 2)//2
else:
stack_img_nums = 0
while(len(images)>0):
if stack_img_nums <=0:
row_image_arr.append(images[0])
images = images[1:]
elif len(images)>stack_img_nums*2:
if get_random_bool():
row_image_arr.append(concat_images_vertically_and_scale(images[:2]))
images = images[2:]
stack_img_nums -=1
else:
row_image_arr.append(images[0])
images = images[1:]
else:
row_image_arr.append(concat_images_vertically_and_scale(images[:2]))
images = images[2:]
stack_img_nums-=1
return combine_images_horizontally(row_image_arr)
def get_row_image2(images,captions = None, font = None):
row_image_arr = []
if len(images)== 6:
sequence_list = [1,1,2,2]
elif len(images)== 4:
sequence_list = [1,1,2]
else:
raise ValueError("images nums is not 4 or 6 found",len(images))
random.shuffle(sequence_list)
index = 0
for length in sequence_list:
if length == 1:
if captions != None:
images_tmp = add_caption(images[0],text = captions[index],font= font)
else:
images_tmp = images[0]
row_image_arr.append( images_tmp)
images = images[1:]
index +=1
elif length == 2:
row_image_arr.append(concat_images_vertically_and_scale(images[:2]))
images = images[2:]
index +=2
return combine_images_horizontally(row_image_arr)
def concat_images_vertically_and_scale(images,scale_factor=2):
# 加载所有图像
# 确保所有图像的宽度一致
widths = [img.width for img in images]
if not all(width == widths[0] for width in widths):
raise ValueError('All images must have the same width.')
# 计算总高度
total_height = sum(img.height for img in images)
# 创建新的图像,宽度与原图相同,高度为所有图像高度之和
max_width = max(widths)
concatenated_image = Image.new('RGB', (max_width, total_height))
# 竖直拼接图像
current_height = 0
for img in images:
concatenated_image.paste(img, (0, current_height))
current_height += img.height
# 缩放图像为1/n高度
new_height = concatenated_image.height // scale_factor
new_width = concatenated_image.width // scale_factor
resized_image = concatenated_image.resize((new_width, new_height), Image.ANTIALIAS)
return resized_image
def combine_images_horizontally(images):
# 读取所有图片并存入列表
# 获取每幅图像的宽度和高度
widths, heights = zip(*(i.size for i in images))
# 计算总宽度和最大高度
total_width = sum(widths)
max_height = max(heights)
# 创建新的空白图片,用于拼接
new_im = Image.new('RGB', (total_width, max_height))
# 将图片横向拼接
x_offset = 0
for im in images:
new_im.paste(im, (x_offset, 0))
x_offset += im.width
return new_im
def combine_images_vertically_with_resize(images):
# 获取所有图片的宽度和高度
widths, heights = zip(*(i.size for i in images))
# 确定新图片的宽度,即所有图片中最小的宽度
min_width = min(widths)
# 调整图片尺寸以保持宽度一致,长宽比不变
resized_images = []
for img in images:
# 计算新高度保持图片长宽比
new_height = int(min_width * img.height / img.width)
# 调整图片大小
resized_img = img.resize((min_width, new_height), Image.ANTIALIAS)
resized_images.append(resized_img)
# 计算所有调整尺寸后图片的总高度
total_height = sum(img.height for img in resized_images)
# 创建一个足够宽和高的新图片对象
new_im = Image.new('RGB', (min_width, total_height))
# 竖直拼接图片
y_offset = 0
for im in resized_images:
new_im.paste(im, (0, y_offset))
y_offset += im.height
return new_im
def distribute_images2(images, pad_image):
groups = []
remaining = len(images)
if len(images) <= 8:
group_sizes = [4]
else:
group_sizes = [4, 6]
size_index = 0
while remaining > 0:
size = group_sizes[size_index%len(group_sizes)]
if remaining < size and remaining < min(group_sizes):
size = min(group_sizes)
if remaining > size:
new_group = images[-remaining: -remaining + size]
else:
new_group = images[-remaining:]
groups.append(new_group)
size_index += 1
remaining -= size
print(remaining,groups)
groups[-1] = groups[-1] + [pad_image for _ in range(-remaining)]
return groups
def distribute_images(images, group_sizes=(4, 3, 2)):
groups = []
remaining = len(images)
while remaining > 0:
# 优先分配最大组(4张图片),再考虑3张,最后处理2张
for size in sorted(group_sizes, reverse=True):
# 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)
# 开始创建新组
if remaining >= size or remaining == len(images):
if remaining > size:
new_group = images[-remaining: -remaining + size]
else:
new_group = images[-remaining:]
groups.append(new_group)
remaining -= size
break
# 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
elif remaining < min(group_sizes) and groups:
groups[-1].extend(images[-remaining:])
remaining = 0
return groups
def create_binary_matrix(img_arr, target_color):
mask = np.all(img_arr == target_color, axis=-1)
binary_matrix = mask.astype(int)
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
def process_sketch(canvas_data):
binary_matrixes = []
base64_img = canvas_data['image']
image_data = base64.b64decode(base64_img.split(',')[1])
image = Image.open(BytesIO(image_data)).convert("RGB")
im2arr = np.array(image)
colors = [tuple(map(int, rgb[4:-1].split(','))) for rgb in canvas_data['colors']]
colors_fixed = []
r, g, b = 255, 255, 255
binary_matrix = create_binary_matrix(im2arr, (r,g,b))
binary_matrixes.append(binary_matrix)
binary_matrix_ = np.repeat(np.expand_dims(binary_matrix, axis=(-1)), 3, axis=(-1))
colored_map = binary_matrix_*(r,g,b) + (1-binary_matrix_)*(50,50,50)
colors_fixed.append(gr.update(value=colored_map.astype(np.uint8)))
for color in colors:
r, g, b = color
if any(c != 255 for c in (r, g, b)):
binary_matrix = create_binary_matrix(im2arr, (r,g,b))
binary_matrixes.append(binary_matrix)
binary_matrix_ = np.repeat(np.expand_dims(binary_matrix, axis=(-1)), 3, axis=(-1))
colored_map = binary_matrix_*(r,g,b) + (1-binary_matrix_)*(50,50,50)
colors_fixed.append(gr.update(value=colored_map.astype(np.uint8)))
visibilities = []
colors = []
for n in range(MAX_COLORS):
visibilities.append(gr.update(visible=False))
colors.append(gr.update())
for n in range(len(colors_fixed)):
visibilities[n] = gr.update(visible=True)
colors[n] = colors_fixed[n]
return [gr.update(visible=True), binary_matrixes, *visibilities, *colors]
def process_prompts(binary_matrixes, *seg_prompts):
return [gr.update(visible=True), gr.update(value=' , '.join(seg_prompts[:len(binary_matrixes)]))]
def process_example(layout_path, all_prompts, seed_):
all_prompts = all_prompts.split('***')
binary_matrixes = []
colors_fixed = []
im2arr = np.array(Image.open(layout_path))[:,:,:3]
unique, counts = np.unique(np.reshape(im2arr,(-1,3)), axis=0, return_counts=True)
sorted_idx = np.argsort(-counts)
binary_matrix = create_binary_matrix(im2arr, (0,0,0))
binary_matrixes.append(binary_matrix)
binary_matrix_ = np.repeat(np.expand_dims(binary_matrix, axis=(-1)), 3, axis=(-1))
colored_map = binary_matrix_*(255,255,255) + (1-binary_matrix_)*(50,50,50)
colors_fixed.append(gr.update(value=colored_map.astype(np.uint8)))
for i in range(len(all_prompts)-1):
r, g, b = unique[sorted_idx[i]]
if any(c != 255 for c in (r, g, b)) and any(c != 0 for c in (r, g, b)):
binary_matrix = create_binary_matrix(im2arr, (r,g,b))
binary_matrixes.append(binary_matrix)
binary_matrix_ = np.repeat(np.expand_dims(binary_matrix, axis=(-1)), 3, axis=(-1))
colored_map = binary_matrix_*(r,g,b) + (1-binary_matrix_)*(50,50,50)
colors_fixed.append(gr.update(value=colored_map.astype(np.uint8)))
visibilities = []
colors = []
prompts = []
for n in range(MAX_COLORS):
visibilities.append(gr.update(visible=False))
colors.append(gr.update())
prompts.append(gr.update())
for n in range(len(colors_fixed)):
visibilities[n] = gr.update(visible=True)
colors[n] = colors_fixed[n]
prompts[n] = all_prompts[n+1]
return [gr.update(visible=True), binary_matrixes, *visibilities, *colors, *prompts,
gr.update(visible=True), gr.update(value=all_prompts[0]), int(seed_)]