333 lines
11 KiB
Python
333 lines
11 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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图像处理工具类
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用于处理base64编码、图像转换等功能
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"""
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import base64
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import io
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import logging
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from typing import Dict, Any, List, Optional, Tuple
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from pathlib import Path
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from PIL import Image
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import json
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logger = logging.getLogger(__name__)
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class ImageProcessor:
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"""图像处理工具类"""
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@staticmethod
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def image_to_base64(image_path: str, format: str = "PNG") -> str:
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"""
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将图像文件转换为base64编码
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Args:
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image_path: 图像文件路径
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format: 输出格式 (PNG, JPEG等)
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Returns:
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base64编码的字符串
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"""
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try:
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with open(image_path, "rb") as image_file:
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# 读取图像文件
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image_data = image_file.read()
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# 转换为base64
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base64_data = base64.b64encode(image_data).decode('utf-8')
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# 添加MIME类型前缀
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mime_type = f"image/{format.lower()}"
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if format.upper() == "JPEG":
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mime_type = "image/jpeg"
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elif format.upper() == "PNG":
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mime_type = "image/png"
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return f"data:{mime_type};base64,{base64_data}"
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except Exception as e:
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logger.error(f"图像转base64失败: {e}")
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return ""
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@staticmethod
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def pil_image_to_base64(image: Image.Image, format: str = "PNG") -> str:
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"""
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将PIL图像对象转换为base64编码
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Args:
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image: PIL图像对象
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format: 输出格式 (PNG, JPEG等)
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Returns:
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base64编码的字符串
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"""
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try:
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# 创建内存缓冲区
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buffer = io.BytesIO()
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# 保存图像到缓冲区
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if format.upper() == "JPEG":
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image.save(buffer, format="JPEG", quality=85)
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else:
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image.save(buffer, format="PNG")
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# 获取字节数据
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image_data = buffer.getvalue()
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# 转换为base64
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base64_data = base64.b64encode(image_data).decode('utf-8')
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# 添加MIME类型前缀
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mime_type = f"image/{format.lower()}"
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if format.upper() == "JPEG":
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mime_type = "image/jpeg"
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elif format.upper() == "PNG":
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mime_type = "image/png"
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return f"data:{mime_type};base64,{base64_data}"
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except Exception as e:
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logger.error(f"PIL图像转base64失败: {e}")
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return ""
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@staticmethod
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def base64_to_image(base64_string: str) -> Optional[Image.Image]:
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"""
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将base64编码转换为PIL图像对象
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Args:
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base64_string: base64编码的字符串
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Returns:
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PIL图像对象，如果转换失败则返回None
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"""
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try:
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# 移除MIME类型前缀
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if "data:image" in base64_string:
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base64_data = base64_string.split(",")[1]
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else:
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base64_data = base64_string
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# 解码base64
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image_data = base64.b64decode(base64_data)
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# 创建PIL图像对象
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image = Image.open(io.BytesIO(image_data))
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return image
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except Exception as e:
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logger.error(f"base64转图像失败: {e}")
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return None
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@staticmethod
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def get_image_metadata(image_path: str) -> Dict[str, Any]:
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"""
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获取图像文件的元数据
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Args:
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image_path: 图像文件路径
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Returns:
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元数据字典
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"""
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try:
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with Image.open(image_path) as image:
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metadata = {
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"width": image.width,
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"height": image.height,
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"format": image.format,
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"mode": image.mode,
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"size_bytes": Path(image_path).stat().st_size if Path(image_path).exists() else 0
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}
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# 获取EXIF数据（如果有）
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if hasattr(image, '_getexif') and image._getexif():
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metadata["exif"] = dict(image._getexif())
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return metadata
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except Exception as e:
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logger.error(f"获取图像元数据失败: {e}")
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return {}
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@staticmethod
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def resize_image(image: Image.Image, max_width: int = 1920, max_height: int = 1080) -> Image.Image:
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"""
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调整图像尺寸
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Args:
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image: PIL图像对象
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max_width: 最大宽度
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max_height: 最大高度
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Returns:
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调整后的图像对象
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"""
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try:
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# 计算缩放比例
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width, height = image.size
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scale = min(max_width / width, max_height / height, 1.0)
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if scale < 1.0:
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new_width = int(width * scale)
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new_height = int(height * scale)
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image = image.resize((new_width, new_height), Image.Resampling.LANCZOS)
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return image
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except Exception as e:
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logger.error(f"调整图像尺寸失败: {e}")
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return image
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@staticmethod
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def create_collage_from_paths(image_paths: List[str], target_size: Tuple[int, int] = (1350, 1800)) -> Optional[Image.Image]:
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"""
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从图像路径列表创建拼图
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Args:
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image_paths: 图像路径列表
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target_size: 目标尺寸 (宽度, 高度)
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Returns:
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拼图图像对象，如果创建失败则返回None
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"""
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try:
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if not image_paths:
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logger.warning("没有提供图像路径")
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return None
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# 加载图像
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images = []
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for path in image_paths[:4]: # 最多使用4张图片
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try:
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with Image.open(path) as img:
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# 转换为RGB模式
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if img.mode != 'RGB':
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img = img.convert('RGB')
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images.append(img)
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except Exception as e:
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logger.warning(f"加载图像失败 {path}: {e}")
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continue
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if not images:
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logger.error("没有成功加载任何图像")
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return None
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# 创建拼图画布
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collage = Image.new('RGB', target_size, (255, 255, 255))
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# 计算每个图像的位置和尺寸
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if len(images) == 1:
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# 单张图片，居中显示
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img = images[0]
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img = ImageProcessor.resize_image(img, target_size[0], target_size[1])
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x = (target_size[0] - img.width) // 2
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y = (target_size[1] - img.height) // 2
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collage.paste(img, (x, y))
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elif len(images) == 2:
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# 两张图片，上下排列
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for i, img in enumerate(images):
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img = ImageProcessor.resize_image(img, target_size[0], target_size[1] // 2)
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x = (target_size[0] - img.width) // 2
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y = i * (target_size[1] // 2)
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collage.paste(img, (x, y))
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elif len(images) >= 3:
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# 多张图片，2x2网格
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cell_width = target_size[0] // 2
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cell_height = target_size[1] // 2
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for i, img in enumerate(images[:4]):
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img = ImageProcessor.resize_image(img, cell_width, cell_height)
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row = i // 2
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col = i % 2
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x = col * cell_width
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y = row * cell_height
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collage.paste(img, (x, y))
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return collage
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except Exception as e:
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logger.error(f"创建拼图失败: {e}")
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return None
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@staticmethod
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def process_images_for_poster(image_paths: List[str],
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target_size: Tuple[int, int] = (1350, 1800),
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create_collage: bool = False) -> Dict[str, Any]:
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"""
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处理图像用于海报生成
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Args:
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image_paths: 图像路径列表
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target_size: 目标尺寸
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create_collage: 是否创建拼图
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Returns:
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处理结果字典
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"""
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result = {
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"main_image": None,
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"collage_image": None,
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"all_images": [],
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"metadata": {}
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}
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try:
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# 处理所有图像
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for i, path in enumerate(image_paths):
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try:
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# 转换为base64
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base64_data = ImageProcessor.image_to_base64(path)
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# 获取元数据
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metadata = ImageProcessor.get_image_metadata(path)
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image_info = {
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"index": i,
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"path": path,
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"base64": base64_data,
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"metadata": metadata
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}
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result["all_images"].append(image_info)
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# 第一张图片作为主图
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if i == 0:
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result["main_image"] = image_info
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except Exception as e:
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logger.error(f"处理图像失败 {path}: {e}")
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continue
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# 如果需要创建拼图
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if create_collage and len(image_paths) > 1:
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collage = ImageProcessor.create_collage_from_paths(image_paths, target_size)
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if collage:
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collage_base64 = ImageProcessor.pil_image_to_base64(collage, "JPEG")
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result["collage_image"] = {
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"base64": collage_base64,
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"metadata": {
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"width": collage.width,
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"height": collage.height,
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"format": "JPEG",
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"type": "collage"
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}
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}
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# 添加总体元数据
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result["metadata"] = {
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"total_images": len(result["all_images"]),
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"has_collage": result["collage_image"] is not None,
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"target_size": target_size
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}
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return result
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except Exception as e:
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logger.error(f"处理图像失败: {e}")
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return result |