287 lines
8.9 KiB
Python
287 lines
8.9 KiB
Python
from pathlib import Path
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from typing import cast
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from typing import List, Optional, Union
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import numpy as np
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import torch
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from PIL import Image
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#----------------------------------------------------------------------------
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here = Path(__file__).parent.absolute()
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comfy_dir = here.parent.parent
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#----------------------------------------------------------------------------
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def pil2tensor(image: Union[Image.Image, List[Image.Image]]) -> torch.Tensor:
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if isinstance(image, list):
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return torch.cat([pil2tensor(img) for img in image], dim=0)
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return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)
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#----------------------------------------------------------------------------
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# 添加一个辅助函数，用于交换宽度和高度
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def swap_width_height(width, height):
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return height, width
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#----------------------------------------------------------------------------
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import logging
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import re
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import os
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base_log_level = logging.DEBUG if os.environ.get("MTB_DEBUG") else logging.INFO
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# Custom object that discards the output
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class NullWriter:
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def write(self, text):
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pass
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class Formatter(logging.Formatter):
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grey = "\x1b[38;20m"
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cyan = "\x1b[36;20m"
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purple = "\x1b[35;20m"
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yellow = "\x1b[33;20m"
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red = "\x1b[31;20m"
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bold_red = "\x1b[31;1m"
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reset = "\x1b[0m"
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# format = "%(asctime)s - [%(name)s] - %(levelname)s - %(message)s (%(filename)s:%(lineno)d)"
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format = "[%(name)s] | %(levelname)s -> %(message)s"
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FORMATS = {
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logging.DEBUG: purple + format + reset,
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logging.INFO: cyan + format + reset,
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logging.WARNING: yellow + format + reset,
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logging.ERROR: red + format + reset,
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logging.CRITICAL: bold_red + format + reset,
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}
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def format(self, record):
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log_fmt = self.FORMATS.get(record.levelno)
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formatter = logging.Formatter(log_fmt)
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return formatter.format(record)
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def mklog(name, level=base_log_level):
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logger = logging.getLogger(name)
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logger.setLevel(level)
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for handler in logger.handlers:
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logger.removeHandler(handler)
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ch = logging.StreamHandler()
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ch.setLevel(level)
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ch.setFormatter(Formatter())
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logger.addHandler(ch)
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# Disable log propagation
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logger.propagate = False
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return logger
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# - The main app logger
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log = mklog(__package__, base_log_level)
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def log_user(arg):
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print("\033[34mComfy MTB Utils:\033[0m {arg}")
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def get_summary(docstring):
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return docstring.strip().split("\n\n", 1)[0]
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def blue_text(text):
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return f"\033[94m{text}\033[0m"
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def cyan_text(text):
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return f"\033[96m{text}\033[0m"
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def get_label(label):
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words = re.findall(r"(?:^|[A-Z])[a-z]*", label)
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return " ".join(words).strip()
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# 禁用 aiohttp 的访问日志记录器
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logging.getLogger('aiohttp.access').disabled = True
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#----------------------------------------------------------------------------
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def bbox_dim(bbox):
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left, upper, right, lower = bbox
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width = right - left
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height = lower - upper
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return width, height
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#----------------------------------------------------------------------------
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class Text_Image_Frame_Zho:
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fonts = {}
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def __init__(self):
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# - This is executed when the graph is executed, we could conditionaly reload fonts there
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pass
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@classmethod
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def CACHE_FONTS(cls):
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font_extensions = ["*.ttf", "*.otf", "*.woff", "*.woff2", "*.eot"]
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fonts = []
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for extension in font_extensions:
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fonts.extend(comfy_dir.glob(f"**/{extension}"))
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if not fonts:
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log.warn(
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"> No fonts found in the comfy folder, place at least one font file somewhere in ComfyUI's hierarchy"
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)
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else:
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log.debug(f"> Found {len(fonts)} fonts")
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for font in fonts:
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log.debug(f"Adding font {font}")
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cls.fonts[font.stem] = font.as_posix()
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@classmethod
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def INPUT_TYPES(cls):
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if not cls.fonts:
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cls.CACHE_FONTS()
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else:
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log.debug(f"Using cached fonts (count: {len(cls.fonts)})")
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return {
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"required": {
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"number": (
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"STRING",
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{"default": "0"},
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),
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# 增加frame参数
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"frame": (
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"INT",
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{"default": 1, "min": 1, "max": 100, "step": 1},
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),
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# 增加step参数
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"step": (
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"INT",
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{"default": 1, "min": 1, "max": 100, "step": 1},
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),
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"selected_font": ((sorted(cls.fonts.keys())),),
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"align": (["left", "center", "right"],
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),
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"wrap": (
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"INT",
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{"default": 10, "min": 0, "max": 8096, "step": 1},
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),
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"font_size": (
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"INT",
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{"default": 50, "min": 1, "max": 2500, "step": 1},
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),
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"color": (
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"COLOR",
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{"default": "red"},
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),
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"outline_size": (
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"INT",
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{"default": 0, "min": 0, "max": 8096, "step": 1},
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),
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"outline_color": (
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"COLOR",
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{"default": "blue"}, # 设置默认的描边颜色
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),
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"margin_x": (
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"INT",
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{"default": 0, "min": 0, "max": 8096, "step": 1},
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),
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"margin_y": (
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"INT",
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{"default": 0, "min": 0, "max": 8096, "step": 1},
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),
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"width": (
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"INT",
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{"default": 512, "min": 1, "max": 8096, "step": 1},
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),
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"height": (
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"INT",
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{"default": 512, "min": 1, "max": 8096, "step": 1},
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),
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"swap": ("BOOLEAN", {"default": False}), # 添加交换宽度和高度的按钮
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}
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}
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RETURN_TYPES = ("IMAGE",)
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RETURN_NAMES = ("image",)
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FUNCTION = "text_to_image_frame"
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CATEGORY = "Zho模块组/text"
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def text_to_image(
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self, number, selected_font, align, wrap, font_size, width, height, color, outline_size, outline_color, margin_x, margin_y, swap=False
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):
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from PIL import Image, ImageDraw, ImageFont
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import textwrap
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# 如果用户选择交换宽度和高度，则调用交换函数
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if swap:
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width, height = swap_width_height(width, height)
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font_path = self.fonts[selected_font]
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(_, top, _, _) = ImageFont.truetype(font_path, font_size).getbbox(number)
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font = cast(ImageFont.FreeTypeFont, ImageFont.truetype(font_path, font_size))
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if wrap == 0:
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wrap = width / font_size
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wrap = int(wrap)
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lines = textwrap.wrap(number, width=wrap)
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log.debug(f"Lines: {lines}")
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line_height = bbox_dim(font.getbbox("hg"))[1]
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img_height = height # line_height * len(lines)
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img_width = width # max(font.getsize(line)[0] for line in lines)
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img = Image.new("RGBA", (img_width, img_height), (0, 0, 0, 0))
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draw = ImageDraw.Draw(img)
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# 初始化 y_text
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y_text = margin_y + outline_size - top
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for line in lines:
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width, height = bbox_dim(font.getbbox(line))
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# 根据 align 参数计算文本的 x 坐标
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if align == "left":
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x_text = margin_x
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elif align == "center":
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x_text = (img_width - width) // 2
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elif align == "right":
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x_text = img_width - width - margin_x
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else:
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x_text = margin_x # 默认为左对齐
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draw.text(
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(x_text, y_text),
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text=line,
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fill=color,
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stroke_fill=outline_color,
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stroke_width=outline_size,
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font=font,
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)
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y_text += height
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return (pil2tensor(img),)
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def text_to_image_frame(self, number, frame, step, selected_font, align, wrap, font_size, width, height, color, outline_size, outline_color, margin_x, margin_y, swap=False):
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images = []
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for i in range(frame):
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current_text = str(int(number) + i * step) # 计算当前步的文本内容
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image = self.text_to_image(
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current_text, selected_font, align, wrap, font_size, width, height, color, outline_size, outline_color, margin_x, margin_y, swap
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)
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images.append(image[0]) # image[0] 是因为 text_to_image 返回的是元组
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s = torch.cat(images, dim=0)
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return (s,)
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#----------------------------------------------------------------------------
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NODE_CLASS_MAPPINGS = {
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"Text_Image_Frame_Zho": Text_Image_Frame_Zho,
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} |