402 lines
15 KiB
Python
402 lines
15 KiB
Python
"""
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图层合成模块 - 将生成的各个图层组合成完整海报 (修改版)
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提供增强的图层信息导出，便于PSD模块使用
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"""
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import os
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import json
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import logging
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from typing import List, Dict, Any, Optional, Tuple
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import numpy as np
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from PIL import Image, ImageFont, ImageDraw
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# 配置日志
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
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logger = logging.getLogger(__name__)
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class PosterComposer:
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"""海报合成类，负责将各个图层组合成完整海报"""
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def __init__(self, images_dir: str = "./images", output_dir: str = "./outputs"):
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"""
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初始化海报合成器
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参数:
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images_dir: 源图像目录
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output_dir: 合成图像输出目录
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"""
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self.images_dir = images_dir
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self.output_dir = output_dir
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os.makedirs(output_dir, exist_ok=True)
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logger.info(f"海报合成器初始化完成，图像目录: {images_dir}, 输出目录: {output_dir}")
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def apply_golden_ratio_positioning(self,
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canvas_size: Tuple[int, int],
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element_size: Tuple[int, int],
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position: str = "right") -> Tuple[int, int]:
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"""
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基于黄金分割比例(约1.618)计算位置
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参数:
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canvas_size: 画布宽度和高度
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element_size: 要放置元素的宽度和高度
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position: 黄金分割位置 ("left", "right", "top", "bottom")
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返回:
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元素的(x, y)坐标
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"""
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width, height = canvas_size
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elem_width, elem_height = element_size
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# 黄金比例约为1.618
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golden_ratio = 1.618
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if position == "right":
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# 水平方向右侧黄金分割点
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x = int((width / golden_ratio) - (elem_width / 2))
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y = int((height - elem_height) / 2) # 垂直居中
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elif position == "left":
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# 水平方向左侧黄金分割点
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x = int(width - (width / golden_ratio) - (elem_width / 2))
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y = int((height - elem_height) / 2) # 垂直居中
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elif position == "top":
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# 垂直方向上侧黄金分割点
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x = int((width - elem_width) / 2) # 水平居中
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y = int((height / golden_ratio) - (elem_height / 2))
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elif position == "bottom":
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# 垂直方向下侧黄金分割点
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x = int((width - elem_width) / 2) # 水平居中
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y = int(height - (height / golden_ratio) - (elem_height / 2))
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else: # 默认居中
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x = int((width - elem_width) / 2)
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y = int((height - elem_height) / 2)
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return (x, y)
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def calculate_position(self,
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position_type: str,
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canvas_size: Tuple[int, int],
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element_size: Tuple[int, int],
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offset: Tuple[int, int] = (0, 0),
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reference: str = None) -> Tuple[int, int]:
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"""
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根据指定的位置类型计算位置
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参数:
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position_type: 位置类型 ("center", "golden_ratio", "corner", "custom")
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canvas_size: 画布宽度和高度
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element_size: 要放置元素的宽度和高度
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offset: 从计算位置的(x, y)偏移量
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reference: 额外位置参考 (如 "top_left", "golden_right")
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返回:
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元素的(x, y)坐标
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"""
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width, height = canvas_size
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elem_width, elem_height = element_size
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offset_x, offset_y = offset
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if position_type == "center":
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# 居中定位
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x = int((width - elem_width) / 2) + offset_x
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y = int((height - elem_height) / 2) + offset_y
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elif position_type == "golden_ratio":
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# 黄金分割定位
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golden_pos = reference.split("_")[1] if reference else "right"
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x, y = self.apply_golden_ratio_positioning(canvas_size, element_size, golden_pos)
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x += offset_x
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y += offset_y
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elif position_type == "corner":
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# 角落定位
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corner = reference if reference else "top_left"
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if corner == "top_left":
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x, y = 0, 0
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elif corner == "top_right":
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x, y = width - elem_width, 0
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elif corner == "bottom_left":
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x, y = 0, height - elem_height
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elif corner == "bottom_right":
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x, y = width - elem_width, height - elem_height
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x += offset_x
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y += offset_y
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elif position_type == "custom":
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# 自定义位置，偏移量为绝对位置
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x, y = offset_x, offset_y
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else: # 默认居中
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x = int((width - elem_width) / 2) + offset_x
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y = int((height - elem_height) / 2) + offset_y
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return (x, y)
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def fit_image_to_canvas(self,
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image: Image.Image,
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canvas_size: Tuple[int, int],
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fit_method: str = "contain") -> Image.Image:
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"""
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调整图像大小以适应画布尺寸
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参数:
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image: 要调整大小的PIL图像
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canvas_size: 目标画布尺寸
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fit_method: 适应方法 ("contain", "cover", "stretch")
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返回:
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调整大小后的PIL图像
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"""
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canvas_width, canvas_height = canvas_size
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img_width, img_height = image.size
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if fit_method == "contain":
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# 缩放图像以适应画布同时保持纵横比
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ratio = min(canvas_width / img_width, canvas_height / img_height)
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new_width = int(img_width * ratio)
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new_height = int(img_height * ratio)
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elif fit_method == "cover":
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# 缩放图像以覆盖画布同时保持纵横比
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ratio = max(canvas_width / img_width, canvas_height / img_height)
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new_width = int(img_width * ratio)
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new_height = int(img_height * ratio)
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elif fit_method == "stretch":
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# 拉伸图像以匹配画布尺寸
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new_width = canvas_width
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new_height = canvas_height
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else: # 默认为"contain"
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ratio = min(canvas_width / img_width, canvas_height / img_height)
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new_width = int(img_width * ratio)
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new_height = int(img_height * ratio)
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# 调整图像大小
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return image.resize((new_width, new_height), Image.LANCZOS)
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def apply_overlay(self,
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base_image: Image.Image,
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overlay_image: Image.Image,
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position: Tuple[int, int] = (0, 0),
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opacity: float = 1.0) -> Image.Image:
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"""
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将叠加图像应用到基础图像上
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参数:
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base_image: 基础PIL图像
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overlay_image: 叠加PIL图像
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position: 放置叠加图的位置(x, y)
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opacity: 叠加图像的不透明度(0.0到1.0)
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返回:
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合并后的PIL图像
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"""
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# 创建基础图像的副本
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result = base_image.copy()
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# 确保叠加图像有alpha通道
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if overlay_image.mode != 'RGBA':
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overlay_image = overlay_image.convert('RGBA')
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# 如果不透明度小于1，调整alpha通道
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if opacity < 1.0:
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overlay_data = list(overlay_image.getdata())
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new_data = []
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for item in overlay_data:
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# 通过不透明度调整alpha通道
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new_data.append((item[0], item[1], item[2], int(item[3] * opacity)))
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overlay_image.putdata(new_data)
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# 将叠加图粘贴到结果上
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result.paste(overlay_image, position, overlay_image)
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return result
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def load_image(self, path: str) -> Optional[Image.Image]:
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"""
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从文件路径加载图像
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参数:
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path: 图像文件的路径
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返回:
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PIL图像对象，加载失败则返回None
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"""
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try:
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if os.path.exists(path):
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return Image.open(path).convert('RGBA')
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else:
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logger.warning(f"未找到图像文件: {path}")
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return None
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except Exception as e:
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logger.error(f"从{path}加载图像时出错: {e}")
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return None
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def compose_from_layout(self,
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layout_config: Dict[str, Any],
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output_filename: str = "composed_poster.png",
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canvas_size: Tuple[int, int] = (1200, 1600)) -> Dict[str, Any]:
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"""
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根据布局配置合成海报
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参数:
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layout_config: 指定图层及其属性的配置
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output_filename: 输出图像文件的名称
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canvas_size: 输出画布的大小(宽度，高度)
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返回:
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包含合成海报信息的字典
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"""
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# 创建带alpha通道的空白画布
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canvas = Image.new('RGBA', canvas_size, (0, 0, 0, 0))
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# 获取从底到顶的图层顺序
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layer_order = layout_config.get("layer_order", [
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"background", "main_subject", "secondary_subject",
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"decorative_elements", "logo", "title", "subtitle"
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])
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# 跟踪已处理的图层以供输出信息
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processed_layers = {}
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# 根据布局配置处理每个图层
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for layer_name in layer_order:
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layer_config = layout_config.get(layer_name, {})
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if not layer_config:
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logger.warning(f"未找到图层'{layer_name}'的配置")
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continue
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# 获取图层图像路径
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image_path = layer_config.get("image_path", "")
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full_path = os.path.join(self.images_dir, image_path) if image_path else None
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if not full_path or not os.path.exists(full_path):
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logger.warning(f"未找到图层'{layer_name}'的图像文件: {full_path}")
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continue
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# 加载图层图像
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layer_img = self.load_image(full_path)
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if layer_img is None:
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continue
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# 获取拟合方法
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fit_method = layer_config.get("fit_method", "contain")
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# 如果指定，调整图层大小以适应画布
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if fit_method != "none":
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layer_img = self.fit_image_to_canvas(layer_img, canvas_size, fit_method)
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# 获取位置信息
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position_type = layer_config.get("position_type", "center")
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position_reference = layer_config.get("position_reference", None)
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position_offset = layer_config.get("position_offset", (0, 0))
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# 计算位置
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position = self.calculate_position(
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position_type,
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canvas_size,
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layer_img.size,
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position_offset,
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position_reference
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)
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# 获取不透明度
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opacity = layer_config.get("opacity", 1.0)
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# 将图层应用到画布
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canvas = self.apply_overlay(canvas, layer_img, position, opacity)
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# 记录处理信息
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processed_layers[layer_name] = {
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"image_path": full_path,
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"size": layer_img.size,
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"position": position,
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"opacity": opacity
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}
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logger.info(f"已添加图层'{layer_name}'，位置{position}，大小{layer_img.size}")
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# 保存合成图像
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output_path = os.path.join(self.output_dir, output_filename)
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canvas.save(output_path, format="PNG")
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logger.info(f"已保存合成图像到{output_path}")
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# 保存图层顺序，用于PSD导出
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composition_result = {
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"output_path": output_path,
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"layers": processed_layers,
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"canvas_size": canvas_size,
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"layer_order": [layer for layer in layer_order if layer in processed_layers] # 只包含实际处理的图层
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}
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return composition_result
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def generate_layer_info_for_psd(self, composition_result: Dict[str, Any]) -> Dict[str, Any]:
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"""
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生成PSD导出所需的完整图层信息
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参数:
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composition_result: compose_from_layout的结果
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返回:
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包含图层位置、路径、透明度等信息的字典，供PSD导出使用
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"""
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# 这个方法直接返回composition_result中已经包含的完整图层信息
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# 为了保持与原代码的API兼容性，我们保留这个方法
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psd_info = {
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"layer_order": composition_result.get("layer_order", []),
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"layers": composition_result.get("layers", {}),
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"canvas_size": composition_result.get("canvas_size", (1200, 1600))
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}
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logger.info(f"已生成PSD导出信息，包含{len(psd_info['layer_order'])}个图层")
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return psd_info
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def load_layout_config(config_path: str) -> Dict[str, Any]:
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"""
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从JSON文件加载布局配置
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参数:
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config_path: 布局配置JSON文件的路径
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返回:
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包含布局配置的字典
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"""
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try:
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with open(config_path, 'r', encoding='utf-8') as f:
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return json.load(f)
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except Exception as e:
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logger.error(f"从{config_path}加载布局配置时出错: {e}")
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return {}
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if __name__ == "__main__":
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# 示例用法
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layout_config_path = "../configs/layout_config.json"
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# 加载布局配置
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layout_config = load_layout_config(layout_config_path)
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# 创建合成器并合成海报
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composer = PosterComposer()
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composition_result = composer.compose_from_layout(layout_config)
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print(f"海报成功合成到: {composition_result['output_path']}")
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# 为PSD导出生成图层信息
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psd_info = composer.generate_layer_info_for_psd(composition_result)
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print(f"PSD导出信息准备完成，包含{len(psd_info['layer_order'])}个图层") |