### Python批量图片转多个PDF完整解决方案 #### 一、问题解构与方案分析 **用户需求核心**：将多张图片批量转换为多个独立的PDF文件，每张图片对应一个PDF文件。这在实际工作中有多个应用场景： * **学术论文提交**：需要将实验图表、数据可视化结果分别保存为独立的PDF文档 * **商务报告制作**：将不同的图表、截图分别生成PDF便于分发给不同部门 * **个人文档整理**：将扫描的证件照、资料图片分别保存为PDF文件 **技术方案对比**： | 方案 | 使用库 | 优点 | 缺点 | 适用场景 | |------|--------|------|------|----------| | 方案一 | Pillow + img2pdf | 代码简洁，图像质量保持好 | 功能相对基础 | 简单批量转换 | | 方案二 | PyMuPDF (fitz) | 处理速度快，功能强大 | 安装稍复杂 | 大量文件处理 | | 方案三 | PIL + 报告生成 | 高度可定制化 | 代码量较多 | 复杂排版需求 | 根据参考资料分析，**Pillow + img2pdf**组合是最适合初学者且能满足基本需求的方案[ref_2][ref_5]。 #### 二、环境准备与库安装 首先需要安装必要的Python库： ```bash # 安装Pillow用于图像处理 pip install Pillow # 安装img2pdf用于PDF生成 pip install img2pdf # 可选：安装PyMuPDF作为备选方案 pip install PyMuPDF ``` #### 三、核心代码实现 ##### 3.1 基础版本：使用Pillow + img2pdf ```python import os import img2pdf from PIL import Image import glob def images_to_individual_pdfs_basic(input_folder, output_folder): """ 基础版本：将输入文件夹中的所有图片转换为独立的PDF文件 参数: input_folder: 输入图片文件夹路径 output_folder: 输出PDF文件夹路径 """ # 确保输出文件夹存在 if not os.path.exists(output_folder): os.makedirs(output_folder) # 支持的图片格式 image_extensions = ['*.jpg', '*.jpeg', '*.png', '*.bmp', '*.tiff'] # 获取所有图片文件 image_files = [] for extension in image_extensions: image_files.extend(glob.glob(os.path.join(input_folder, extension))) # 遍历每张图片并转换为PDF for image_path in image_files: try: # 获取文件名（不含扩展名） filename = os.path.splitext(os.path.basename(image_path))[0] output_pdf_path = os.path.join(output_folder, f"{filename}.pdf") # 使用img2pdf转换 with open(output_pdf_path, "wb") as pdf_file: pdf_file.write(img2pdf.convert(image_path)) print(f"成功转换: {image_path} -> {output_pdf_path}") except Exception as e: print(f"转换失败 {image_path}: {str(e)}") # 使用示例 if __name__ == "__main__": input_dir = "input_images" # 输入图片文件夹 output_dir = "output_pdfs" # 输出PDF文件夹 images_to_individual_pdfs_basic(input_dir, output_dir) ``` ##### 3.2 增强版本：支持图像预处理 ```python import os import img2pdf from PIL import Image, ImageOps import glob def images_to_individual_pdfs_enhanced(input_folder, output_folder, resize_to=None, optimize=True): """ 增强版本：支持图像预处理和优化 参数: input_folder: 输入图片文件夹路径 output_folder: 输出PDF文件夹路径 resize_to: 调整尺寸 (宽度, 高度)，None表示保持原尺寸 optimize: 是否优化图像质量 """ if not os.path.exists(output_folder): os.makedirs(output_folder) image_extensions = ['*.jpg', '*.jpeg', '*.png', '*.bmp', '*.tiff'] image_files = [] for extension in image_extensions: image_files.extend(glob.glob(os.path.join(input_folder, extension))) for image_path in image_files: try: filename = os.path.splitext(os.path.basename(image_path))[0] output_pdf_path = os.path.join(output_folder, f"{filename}.pdf") # 打开并预处理图像 with Image.open(image_path) as img: # 转换为RGB模式（确保兼容性） if img.mode != 'RGB': img = img.convert('RGB') # 调整尺寸（如果需要） if resize_to: img = img.resize(resize_to, Image.Resampling.LANCZOS) # 创建临时文件用于转换 temp_image_path = os.path.join(output_folder, f"temp_{filename}.jpg") save_kwargs = {'quality': 95} if optimize else {} img.save(temp_image_path, **save_kwargs) # 转换为PDF with open(output_pdf_path, "wb") as pdf_file: pdf_file.write(img2pdf.convert(temp_image_path)) # 删除临时文件 os.remove(temp_image_path) print(f"成功转换: {image_path} -> {output_pdf_path}") except Exception as e: print(f"转换失败 {image_path}: {str(e)}") # 使用示例 if __name__ == "__main__": input_dir = "input_images" output_dir = "output_pdfs_enhanced" # 转换为标准A4尺寸的PDF images_to_individual_pdfs_enhanced( input_dir, output_dir, resize_to=(2480, 3508), # A4尺寸 @ 300DPI optimize=True ) ``` ##### 3.3 高级版本：使用PyMuPDF（备选方案） ```python import fitz # PyMuPDF import os from PIL import Image import glob def images_to_pdf_pymupdf(input_folder, output_folder): """ 使用PyMuPDF实现图片转PDF（处理速度更快） """ if not os.path.exists(output_folder): os.makedirs(output_folder) image_extensions = ['*.jpg', '*.jpeg', '*.png', '*.bmp', '*.tiff'] image_files = [] for extension in image_extensions: image_files.extend(glob.glob(os.path.join(input_folder, extension))) for image_path in image_files: try: filename = os.path.splitext(os.path.basename(image_path))[0] output_pdf_path = os.path.join(output_folder, f"{filename}.pdf") # 创建新的PDF文档 doc = fitz.open() # 将图片作为页面插入 img = fitz.open(image_path) rect = img[0].rect # 图片尺寸 # 创建页面 page = doc.new_page(width=rect.width, height=rect.height) page.insert_image(rect, filename=image_path) # 保存PDF doc.save(output_pdf_path) doc.close() img.close() print(f"PyMuPDF转换成功: {image_path} -> {output_pdf_path}") except Exception as e: print(f"PyMuPDF转换失败 {image_path}: {str(e)}") # 使用示例 if __name__ == "__main__": input_dir = "input_images" output_dir = "output_pdfs_pymupdf" images_to_pdf_pymupdf(input_dir, output_dir) ``` #### 四、完整工具类实现 ```python import os import img2pdf from PIL import Image, ImageOps import glob from datetime import datetime class BatchImageToPDFConverter: """ 批量图片转PDF转换器类 """ def __init__(self, input_folder, output_folder): self.input_folder = input_folder self.output_folder = output_folder self.supported_extensions = ['jpg', 'jpeg', 'png', 'bmp', 'tiff'] def get_image_files(self): """获取所有支持的图片文件""" image_files = [] for ext in self.supported_extensions: pattern = os.path.join(self.input_folder, f"*.{ext}") image_files.extend(glob.glob(pattern)) return sorted(image_files) # 按文件名排序 def preprocess_image(self, image_path, target_size=None, quality=95): """预处理图像：格式转换、尺寸调整等""" with Image.open(image_path) as img: # 统一转换为RGB模式 if img.mode != 'RGB': img = img.convert('RGB') # 调整尺寸 if target_size: img = img.resize(target_size, Image.Resampling.LANCZOS) # 保存预处理后的临时文件 temp_path = os.path.join(self.output_folder, f"temp_{os.path.basename(image_path)}") img.save(temp_path, quality=quality, optimize=True) return temp_path def convert_single_image(self, image_path, output_filename=None): """转换单张图片为PDF""" try: if output_filename is None: base_name = os.path.splitext(os.path.basename(image_path))[0] output_filename = f"{base_name}.pdf" output_path = os.path.join(self.output_folder, output_filename) # 预处理图像 temp_path = self.preprocess_image(image_path) # 转换为PDF with open(output_path, "wb") as pdf_file: pdf_file.write(img2pdf.convert(temp_path)) # 清理临时文件 os.remove(temp_path) return True, output_path except Exception as e: return False, str(e) def convert_batch(self, progress_callback=None): """批量转换所有图片""" if not os.path.exists(self.output_folder): os.makedirs(self.output_folder) image_files = self.get_image_files() results = { 'total': len(image_files), 'success': 0, 'failed': 0, 'failed_files': [] } print(f"开始批量转换，共 {len(image_files)} 个文件...") for i, image_path in enumerate(image_files): if progress_callback: progress_callback(i, len(image_files)) success, result = self.convert_single_image(image_path) if success: results['success'] += 1 print(f"✓ 成功: {os.path.basename(image_path)}") else: results['failed'] += 1 results['failed_files'].append({ 'file': image_path, 'error': result }) print(f"✗ 失败: {os.path.basename(image_path)} - {result}") # 生成转换报告 self.generate_report(results) return results def generate_report(self, results): """生成转换报告""" report_path = os.path.join(self.output_folder, "conversion_report.txt") with open(report_path, 'w', encoding='utf-8') as f: f.write("批量图片转PDF转换报告\n") f.write("=" * 50 + "\n") f.write(f"转换时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n") f.write(f"输入文件夹: {self.input_folder}\n") f.write(f"输出文件夹: {self.output_folder}\n") f.write(f"总文件数: {results['total']}\n") f.write(f"成功: {results['success']}\n") f.write(f"失败: {results['failed']}\n") f.write(f"成功率: {results['success']/results['total']*100:.1f}%\n") if results['failed_files']: f.write("\n失败文件列表:\n") for item in results['failed_files']: f.write(f" - {os.path.basename(item['file'])}: {item['error']}\n") # 使用示例 if __name__ == "__main__": # 创建转换器实例 converter = BatchImageToPDFConverter( input_folder="input_images", output_folder="output_pdfs_complete" ) # 定义进度回调函数 def progress_callback(current, total): progress = (current + 1) / total * 100 print(f"进度: {progress:.1f}% ({current + 1}/{total})") # 执行批量转换 results = converter.convert_batch(progress_callback=progress_callback) print(f"\n转换完成！成功: {results['success']}, 失败: {results['failed']}") ``` #### 五、实际应用场景示例 ##### 5.1 学术论文图表转换 ```python # 专门处理学术图表的转换 def convert_academic_charts(): converter = BatchImageToPDFConverter( input_folder="research/charts", output_folder="research/pdf_charts" ) # 设置学术论文标准尺寸 def academic_preprocess(image_path): return converter.preprocess_image( image_path, target_size=(2480, 3508), # A4尺寸 quality=100 # 最高质量 ) converter.preprocess_image = academic_preprocess results = converter.convert_batch() ``` ##### 5.2 商务报告图片处理 ```python # 商务报告专用转换 def convert_business_images(): converter = BatchImageToPDFConverter( input_folder="business/images", output_folder="business/report_pdfs" ) # 商务报告通常需要统一尺寸 def business_preprocess(image_path): return converter.preprocess_image( image_path, target_size=(1920, 1080), # 16:9 商务比例 quality=90 ) converter.preprocess_image = business_preprocess return converter.convert_batch() ``` #### 六、性能优化与错误处理 ##### 6.1 内存优化版本 ```python def memory_efficient_conversion(image_path, output_path): """ 内存优化的单文件转换，适合处理大图片 """ try: # 分块处理大图片 with Image.open(image_path) as img: if img.mode != 'RGB': img = img.convert('RGB') # 如果图片太大，进行适当缩放 max_size = (4000, 4000) if img.size[0] > max_size[0] or img.size[1] > max_size[1]: img.thumbnail(max_size, Image.Resampling.LANCZOS) # 使用临时文件避免内存占用过大 temp_path = f"temp_{os.path.basename(image_path)}.jpg" img.save(temp_path, optimize=True, quality=85) # 转换为PDF with open(output_path, "wb") as f: f.write(img2pdf.convert(temp_path)) os.remove(temp_path) return True except Exception as e: print(f"内存优化转换失败: {e}") return False ``` ##### 6.2 错误处理与日志记录 ```python import logging # 设置日志 logging.basicConfig( level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s', handlers=[ logging.FileHandler('image_to_pdf_conversion.log'), logging.StreamHandler() ] ) def robust_conversion(image_path, output_path): """健壮性更强的转换函数""" try: # 检查文件是否存在 if not os.path.exists(image_path): logging.error(f"文件不存在: {image_path}") return False # 检查文件格式 valid_extensions = ['.jpg', '.jpeg', '.png', '.bmp', '.tiff'] file_ext = os.path.splitext(image_path)[1].lower() if file_ext not in valid_extensions: logging.error(f"不支持的格式: {image_path}") return False # 执行转换 return memory_efficient_conversion(image_path, output_path) except Exception as e: logging.error(f"转换过程异常: {image_path}, 错误: {e}") return False ``` 这个完整的解决方案提供了从基础到高级的多种实现方式，涵盖了不同的使用场景和性能需求。基础版本适合快速上手，增强版本提供了图像预处理功能，高级版本使用PyMuPDF获得更好的性能，而完整的工具类则提供了企业级应用所需的所有功能。