diff --git a/convert.py b/convert.py
deleted file mode 100644
index aef150934..000000000
--- a/convert.py
+++ /dev/null
@@ -1,768 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-智能图片格式转换器（保持原文件名）
-===============================
-
-将目录下的图片文件转换为AVIF或JXL格式，但保持原文件名不变（包括扩展名）。
-这样MD文件中的图片链接无需修改。
-
-功能特性：
-- 支持多种输入格式（jpg, jpeg, png, webp, bmp, tiff等）
-- 支持两种输出格式（AVIF和JXL）
-- 自动扫描目录下的所有图片文件
-- 转换为现代图像格式但保持原文件名
-- 智能压缩比检测，自动跳过无效转换
-- 支持dry-run模式（预览不执行）
-- 多线程并行处理，加速转换
-- 可选择删除原始文件备份
-- 进度显示和详细日志记录
-
-压缩优化：
-- 自动检测转换效果，只转换能有效压缩的图片
-- 如果转换后体积变大，自动跳过
-- 可设置最小压缩比阈值
-
-使用示例：
- python image_to_avif_keep_name.py /path/to/images
- python image_to_avif_keep_name.py /path/to/images --format jxl
- python image_to_avif_keep_name.py /path/to/images --format avif --quality 90
- python image_to_avif_keep_name.py /path/to/images --threads 4
- python image_to_avif_keep_name.py /path/to/images --min-compression 10
-"""
-
-import os
-import sys
-import time
-import argparse
-import logging
-import shutil
-import tempfile
-import threading
-import concurrent.futures
-from pathlib import Path
-from datetime import datetime
-from typing import List, Tuple, Set, Dict
-from tqdm import tqdm
-
-try:
- from PIL import Image
- from PIL import ImageFile
-
- # 允许加载截断的图片
- ImageFile.LOAD_TRUNCATED_IMAGES = True
-
- # 检查AVIF支持
- import pillow_avif
-
- HAS_AVIF = True
-except ImportError as e:
- HAS_AVIF = False
- MISSING_PACKAGES = []
- if 'PIL' in str(e):
- MISSING_PACKAGES.append('Pillow')
- if 'pillow_avif' in str(e):
- MISSING_PACKAGES.append('pillow-avif')
-
-# 检查JXL支持
-try:
- import pillow_jxl
-
- HAS_JXL = True
-except ImportError:
- HAS_JXL = False
- MISSING_PACKAGES.append('pillow-jpegxl')
-
-# 支持的图片格式
-SUPPORTED_FORMATS = {
- '.jpg', '.jpeg', '.png', '.webp', '.bmp',
- '.tiff', '.tif', '.gif', '.ico'
-}
-
-
-# 日志配置
-def setup_logging(log_file: str) -> logging.Logger:
- """设置日志记录"""
- logger = logging.getLogger('avif_converter')
- logger.setLevel(logging.DEBUG)
-
- # 文件处理器
- fh = logging.FileHandler(log_file, encoding='utf-8')
- fh.setLevel(logging.DEBUG)
-
- # 控制台处理器
- ch = logging.StreamHandler()
- ch.setLevel(logging.INFO)
-
- # 格式化器
- formatter = logging.Formatter(
- '%(asctime)s - %(levelname)s - %(message)s',
- datefmt='%Y-%m-%d %H:%M:%S'
- )
- fh.setFormatter(formatter)
- ch.setFormatter(logging.Formatter('%(levelname)s: %(message)s'))
-
- logger.addHandler(fh)
- logger.addHandler(ch)
-
- return logger
-
-
-class ImageConverter:
- """图像转换器类，支持AVIF和JXL格式"""
-
- def __init__(self, directory: str, format: str = 'avif', quality: int = 80,
- dry_run: bool = False, recursive: bool = True, delete_backup: bool = False,
- check_compression: bool = True, min_compression_ratio: float = 0.05,
- threads: int = 1, effort: int = 7, show_report: bool = True):
- self.directory = Path(directory)
- self.format = format.lower() # 'avif' 或 'jxl'
- self.quality = quality
- self.dry_run = dry_run
- self.recursive = recursive
- self.delete_backup = delete_backup
- self.threads = max(1, threads) # 至少使用1个线程
- self.stats_lock = threading.Lock() # 用于保护统计数据的线程锁
- self.effort = effort # JXL特有的参数，压缩速度与质量的平衡，1-9
- self.check_compression = check_compression
- self.min_compression_ratio = min_compression_ratio # 最小压缩比，默认5%
- self.show_report = show_report # 是否在结束时显示详细报告
-
- # 统计信息
- self.stats = {
- 'found_images': 0,
- 'converted': 0,
- 'failed': 0,
- 'skipped_larger': 0, # 因体积变大而跳过的文件
- 'skipped_minimal': 0, # 因压缩效果不明显而跳过的文件
- 'total_original_size': 0,
- 'total_converted_size': 0,
- 'total_saved_size': 0, # 总节省空间
- 'format_counts': {}, # 各种格式的统计
- 'conversion_time': 0, # 总转换时间
- 'max_compression': 0, # 最大压缩率
- 'min_compression': 100, # 最小压缩率
- 'avg_compression': 0, # 平均压缩率
- 'errors': []
- }
-
- # 设置日志
- timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
- log_file = self.directory / f'avif_conversion_{timestamp}.log'
- self.logger = setup_logging(str(log_file))
-
- self.logger.info(f"开始处理目录: {self.directory}")
- self.logger.info(f"参数 - 输出格式: {self.format.upper()}, 质量: {self.quality}, 递归: {self.recursive}, "
- f"预览模式: {self.dry_run}, 删除备份: {self.delete_backup}, "
- f"检测压缩比: {self.check_compression}, 最小压缩比: {self.min_compression_ratio:.1%}, "
- f"线程数: {self.threads}" +
- (f", 压缩速度等级: {self.effort}" if self.format == 'jxl' else ""))
-
- def find_images(self) -> List[Path]:
- """查找所有支持的图片文件"""
- images = []
-
- if self.recursive:
- pattern = '**/*'
- else:
- pattern = '*'
-
- for file_path in self.directory.glob(pattern):
- if file_path.is_file() and file_path.suffix.lower() in SUPPORTED_FORMATS:
- # 检查是否已经是目标格式（通过文件头判断）
- if not self._is_already_converted(file_path):
- images.append(file_path)
- self.logger.debug(f"找到图片: {file_path}")
-
- # 统计原始格式
- try:
- with self.stats_lock:
- with Image.open(file_path) as img:
- fmt = img.format.lower() if img.format else file_path.suffix.lower().strip('.')
- if fmt in self.stats['format_counts']:
- self.stats['format_counts'][fmt] += 1
- else:
- self.stats['format_counts'][fmt] = 1
- except Exception:
- # 如果无法打开图片，使用文件扩展名作为格式
- ext = file_path.suffix.lower().strip('.')
- with self.stats_lock:
- if ext in self.stats['format_counts']:
- self.stats['format_counts'][ext] += 1
- else:
- self.stats['format_counts'][ext] = 1
- else:
- self.logger.debug(f"跳过已是{self.format.upper()}格式的文件: {file_path}")
-
- self.stats['found_images'] = len(images)
- self.logger.info(f"找到 {len(images)} 个需要转换的图片文件")
- return images
-
- def _is_already_converted(self, file_path: Path) -> bool:
- """检查文件是否已经是目标格式"""
- try:
- with Image.open(file_path) as img:
- if self.format == 'avif':
- return img.format == 'AVIF'
- elif self.format == 'jxl':
- return img.format == 'JXL'
- return False
- except Exception:
- return False
-
- def _test_compression(self, image_path: Path, original_size: int):
- """测试转换压缩效果"""
- try:
- # 创建临时文件进行测试转换
- with tempfile.NamedTemporaryFile(suffix=f'.{self.format}', delete=False) as tmp_file:
- temp_path = Path(tmp_file.name)
-
- try:
- # 读取并转换图片到临时文件
- with Image.open(image_path) as img:
- # 处理透明度
- if img.mode in ('RGBA', 'LA'):
- pass
- elif img.mode == 'P' and 'transparency' in img.info:
- img = img.convert('RGBA')
- else:
- img = img.convert('RGB')
-
- # 保存为目标格式到临时文件
- if self.format == 'avif':
- img.save(
- temp_path,
- 'AVIF',
- quality=self.quality,
- optimize=True
- )
- elif self.format == 'jxl':
- img.save(
- temp_path,
- 'JXL',
- quality=self.quality,
- effort=self.effort, # JXL特有参数
- lossless=False # 使用有损模式
- )
-
- # 获取转换后文件大小
- converted_size = temp_path.stat().st_size
-
- # 计算压缩比
- if converted_size >= original_size:
- return 'skip_larger'
-
- compression_ratio = ((original_size - converted_size) / original_size) * 100
-
- # 更新压缩率统计
- with self.stats_lock:
- if compression_ratio > self.stats['max_compression']:
- self.stats['max_compression'] = compression_ratio
- if self.stats['min_compression'] > compression_ratio > 0:
- self.stats['min_compression'] = compression_ratio
-
- # 累加到平均压缩率计算
- if compression_ratio > 0:
- current_count = self.stats['converted']
- if current_count > 0:
- self.stats['avg_compression'] = ((self.stats['avg_compression'] * current_count) +
- compression_ratio) / (current_count + 1)
- else:
- self.stats['avg_compression'] = compression_ratio
-
- # 检查是否达到最小压缩比
- if compression_ratio < (self.min_compression_ratio * 100):
- return 'skip_minimal'
-
- return converted_size, compression_ratio
-
- finally:
- # 清理临时文件
- if temp_path.exists():
- temp_path.unlink()
-
- except Exception as e:
- self.logger.warning(f"测试压缩时出错 {image_path}: {str(e)}")
- # 如果测试失败，假设转换有效
- return original_size * 0.7, 30.0 # 估算70%大小，30%压缩率
-
- def convert_image(self, image_path: Path) -> bool:
- """转换单个图片到AVIF格式，保持原文件名"""
- try:
- # 获取原始文件信息
- original_size = image_path.stat().st_size
-
- # 在多线程环境中安全更新统计信息
- with self.stats_lock:
- self.stats['total_original_size'] += original_size
-
- if self.dry_run:
- # 在预览模式下，如果启用了压缩比检测，进行测试转换
- if self.check_compression:
- test_result = self._test_compression(image_path, original_size)
- if test_result == 'skip_larger':
- self.logger.info(f"[预览] 跳过（体积会变大）: {image_path}")
- return False
- elif test_result == 'skip_minimal':
- self.logger.info(f"[预览] 跳过（压缩效果不明显）: {image_path}")
- return False
- else:
- predicted_size, compression_ratio = test_result
- self.logger.info(
- f"[预览] 将转换: {image_path} "
- f"({self._format_size(original_size)} -> {self._format_size(predicted_size)}, "
- f"预计压缩 {compression_ratio:.1f}%)"
- )
- else:
- self.logger.info(f"[预览] 将转换: {image_path}")
- return True
-
- # 实际转换模式
- # 如果启用压缩比检测，先进行测试
- if self.check_compression:
- test_result = self._test_compression(image_path, original_size)
- if test_result == 'skip_larger':
- self.stats['skipped_larger'] += 1
- self.logger.info(f"跳过（转换后体积更大）: {image_path.name}")
- return False
- elif test_result == 'skip_minimal':
- self.stats['skipped_minimal'] += 1
- self.logger.info(f"跳过（压缩效果不明显）: {image_path.name}")
- return False
-
- # 创建备份文件名
- backup_path = image_path.with_suffix(f'{image_path.suffix}.backup')
-
- # 读取并转换图片
- with Image.open(image_path) as img:
- # 处理透明度
- if img.mode in ('RGBA', 'LA'):
- # 保持透明度
- pass
- elif img.mode == 'P' and 'transparency' in img.info:
- # 调色板模式带透明度，转换为RGBA
- img = img.convert('RGBA')
- else:
- # 转换为RGB模式
- img = img.convert('RGB')
-
- # 备份原文件
- shutil.copy2(image_path, backup_path)
- self.logger.debug(f"创建备份: {backup_path}")
-
- # 保存为目标格式，但使用原文件名
- if self.format == 'avif':
- img.save(
- image_path, # 使用原文件路径
- 'AVIF',
- quality=self.quality,
- optimize=True
- )
- elif self.format == 'jxl':
- img.save(
- image_path, # 使用原文件路径
- 'JXL',
- quality=self.quality,
- effort=self.effort, # JXL特有参数
- lossless=False # 使用有损模式
- )
- if self.format == 'webp':
- img.save(
- image_path, # 使用原文件路径
- 'WEBP',
- quality=self.quality,
- optimize=True
- )
-
- # 获取转换后文件大小
- converted_size = image_path.stat().st_size
-
- # 在多线程环境中安全更新统计信息
- with self.stats_lock:
- self.stats['total_converted_size'] += converted_size
-
- # 计算压缩比和节省空间
- saved_size = original_size - converted_size
- self.stats['total_saved_size'] += saved_size
- compression_ratio = (saved_size / original_size) * 100
-
- self.logger.info(
- f"转换成功: {image_path.name} "
- f"({self._format_size(original_size)} -> {self._format_size(converted_size)}, "
- f"压缩 {compression_ratio:.1f}%)"
- )
-
- # 如果需要，删除备份文件
- if self.delete_backup and backup_path.exists():
- backup_path.unlink()
- self.logger.debug(f"删除备份: {backup_path}")
-
- # 在多线程环境中安全更新统计信息
- with self.stats_lock:
- self.stats['converted'] += 1
- return True
-
- except Exception as e:
- error_msg = f"转换失败 {image_path}: {str(e)}"
- self.logger.error(error_msg)
-
- # 在多线程环境中安全更新统计信息
- with self.stats_lock:
- self.stats['errors'].append(error_msg)
- self.stats['failed'] += 1
-
- # 如果转换失败，恢复原文件
- backup_path = image_path.with_suffix(f'{image_path.suffix}.backup')
- if backup_path.exists():
- try:
- shutil.copy2(backup_path, image_path)
- backup_path.unlink()
- self.logger.info(f"已恢复原文件: {image_path}")
- except Exception as restore_error:
- self.logger.error(f"恢复原文件失败: {restore_error}")
-
- return False
-
- def _format_size(self, size_bytes: int) -> str:
- """格式化文件大小"""
- for unit in ['B', 'KB', 'MB', 'GB']:
- if size_bytes < 1024:
- return f"{size_bytes:.1f} {unit}"
- size_bytes /= 1024
- return f"{size_bytes:.1f} TB"
-
- def print_statistics(self):
- """打印统计信息"""
- if not self.show_report:
- return
-
- print("\n" + "=" * 70)
- print(f"图像转换报告 ({self.format.upper()}格式)")
- print("=" * 70)
-
- # 基本统计信息
- print(
- f"处理完成 │ 找到图片: {self.stats['found_images']} │ 成功转换: {self.stats['converted']} │ 失败: {self.stats['failed']}")
-
- # 显示跳过的文件统计
- if self.check_compression:
- total_skipped = self.stats['skipped_larger'] + self.stats['skipped_minimal']
- print(
- f"跳过文件 │ 总计: {total_skipped} │ 体积变大: {self.stats['skipped_larger']} │ 压缩效果不明显: {self.stats['skipped_minimal']}")
-
- # 空间节省统计
- if self.stats['total_original_size'] > 0:
- original_size_mb = self.stats['total_original_size'] / (1024 * 1024)
-
- if self.stats['converted'] > 0:
- converted_size_mb = self.stats['total_converted_size'] / (1024 * 1024)
- saved_mb = self.stats['total_saved_size'] / (1024 * 1024)
- saved_percent = (self.stats['total_saved_size'] / self.stats['total_original_size']) * 100
-
- print("\n" + "-" * 70)
- print("空间节省统计")
- print("-" * 70)
- print(f"原始总大小 : {original_size_mb:.2f} MB")
- print(f"转换后总大小 : {converted_size_mb:.2f} MB")
- print(f"节省空间 : {saved_mb:.2f} MB")
- print(f"总体压缩率 : {saved_percent:.2f}%")
-
- # 计算平均压缩效果
- if self.stats['converted'] > 0:
- avg_compression = (self.stats['total_saved_size'] /
- (self.stats['total_original_size'] -
- (self.stats['total_original_size'] - self.stats['total_converted_size']))) * 100
- print(f"平均压缩率 : {avg_compression:.2f}%")
-
- # 显示格式统计信息
- if self.stats['format_counts'] and len(self.stats['format_counts']) > 0:
- print("\n" + "-" * 70)
- print("原始图片格式统计")
- print("-" * 70)
- for fmt, count in sorted(self.stats['format_counts'].items(), key=lambda x: x[1], reverse=True):
- percent = (count / self.stats['found_images']) * 100 if self.stats['found_images'] > 0 else 0
- print(f"{fmt.upper():<10}: {count:>5} 个文件 ({percent:.1f}%)")
-
- # 显示压缩比检测信息
- if self.check_compression:
- print("\n" + "-" * 70)
- print("压缩检测设置")
- print("-" * 70)
- print(f"检测阈值 : {self.min_compression_ratio:.1%}")
- print(f"跳过体积变大 : {self.stats['skipped_larger']} 个文件")
- print(f"跳过效果不佳 : {self.stats['skipped_minimal']} 个文件")
-
- # 显示错误信息
- if self.stats['errors']:
- print("\n" + "-" * 70)
- print("错误列表")
- print("-" * 70)
- for error in self.stats['errors'][:5]: # 只显示前5个错误
- print(f" - {error}")
- if len(self.stats['errors']) > 5:
- print(f" ... 还有 {len(self.stats['errors']) - 5} 个错误")
-
- # 总结报告
- if self.stats['total_original_size'] > 0 and self.stats['converted'] > 0:
- saved_mb = self.stats['total_saved_size'] / (1024 * 1024)
- saved_percent = (self.stats['total_saved_size'] / self.stats['total_original_size']) * 100
-
- print("\n" + "=" * 70)
- print(
- f"总结: 成功将 {self.stats['converted']} 个图片转换为 {self.format.upper()} 格式，节省了 {saved_mb:.2f} MB 空间 ({saved_percent:.2f}%)")
- else:
- print("\n" + "=" * 70)
- print(f"总结: 没有成功转换任何图片")
-
- print("=" * 70)
-
- def convert_all(self):
- """转换所有图片"""
- start_time = time.time() # 记录开始时间
- images = self.find_images()
-
- if not images:
- print("没有找到需要转换的图片文件")
- return
-
- if self.dry_run:
- print(f"\n[预览模式] 将要转换 {len(images)} 个图片文件:")
- for img in images[:10]: # 只显示前10个
- print(f" - {img}")
- if len(images) > 10:
- print(f" ... 还有 {len(images) - 10} 个文件")
- print("\n使用 --execute 参数执行实际转换")
- return
-
- print(f"\n开始转换 {len(images)} 个图片文件...")
-
- # 单线程处理
- if self.threads <= 1:
- for i, image_path in enumerate(images, 1):
- print(f"[{i}/{len(images)}] 处理: {image_path.name}")
- self.convert_image(image_path)
- # 多线程处理
- else:
- print(f"使用 {self.threads} 个线程并行处理图片...")
-
- # 使用tqdm创建进度条
- with tqdm(total=len(images), desc="图片转换进度", unit="个") as pbar:
- # 创建线程池
- with concurrent.futures.ThreadPoolExecutor(max_workers=self.threads) as executor:
- # 保存所有任务的Future对象
- future_to_path = {
- executor.submit(self._convert_thread_worker, image_path): image_path
- for image_path in images
- }
-
- # 当任务完成时更新进度条
- for future in concurrent.futures.as_completed(future_to_path):
- pbar.update(1)
-
- def _convert_thread_worker(self, image_path):
- """线程工作函数，负责转换单个图片"""
- try:
- # 获取图片名称，用于日志显示
- image_name = image_path.name
-
- # 转换图片
- success = self.convert_image(image_path)
-
- # 由于多线程环境，不在控制台打印信息，所有信息由日志和进度条处理
- return success
- except Exception as e:
- # 捕获线程中的所有异常
- with self.stats_lock:
- error_msg = f"线程处理错误 {image_path}: {str(e)}"
- self.logger.error(error_msg)
- self.stats['errors'].append(error_msg)
- self.stats['failed'] += 1
- return False
-
- # 记录总处理时间
- end_time = time.time()
- self.stats['conversion_time'] = end_time - start_time
-
- self.print_statistics()
-
-
-def check_dependencies(format):
- """检查依赖包"""
- global MISSING_PACKAGES
- if format == 'avif' and not HAS_AVIF:
- print("错误：缺少AVIF支持所需的Python包。")
- print("请先安装以下包：")
- for package in MISSING_PACKAGES:
- print(f" pip install {package}")
- print("\n或者使用：")
- print(" pip install Pillow pillow-avif")
- sys.exit(1)
- elif format == 'jxl' and not HAS_JXL:
- print("错误：缺少JXL支持所需的Python包。")
- print("请先安装以下包：")
- for package in MISSING_PACKAGES:
- print(f" pip install {package}")
- print("\n或者使用：")
- print(" pip install Pillow pillow-jpegxl")
- sys.exit(1)
-
-
-def main():
- """主函数"""
- parser = argparse.ArgumentParser(
- description='将图片转换为AVIF或JXL格式，保持原文件名不变',
- formatter_class=argparse.RawDescriptionHelpFormatter,
- epilog="""
-使用示例:
- %(prog)s /path/to/images # 转换目录下所有图片为AVIF（默认）
- %(prog)s /path/to/images --format jxl # 转换为JXL格式
- %(prog)s /path/to/images --dry-run # 预览模式
- %(prog)s /path/to/images --quality 90 # 设置质量为90
- %(prog)s /path/to/images --threads 4 # 使用4个线程加速处理
- %(prog)s /path/to/images --no-recursive # 不处理子目录
- %(prog)s /path/to/images --delete-backup # 删除备份文件
- %(prog)s /path/to/images --no-compression-check # 强制转换所有文件
- %(prog)s /path/to/images --min-compression 10 # 设置最小压缩比为10%
- %(prog)s /path/to/images --format jxl --effort 5 # JXL格式的编码速度/质量平衡
- %(prog)s /path/to/images --report # 显示详细的转换统计报告
-
-注意：
-- 转换后的图片仍保持原文件名，MD文件中的链接无需修改
-- 默认启用压缩比检测，只转换能有效压缩的图片
-- 如果转换后体积变大或压缩效果不明显，将自动跳过
-- AVIF和JXL都是现代高效图像格式，支持更高的压缩率
- """
- )
-
- parser.add_argument(
- 'directory',
- help='要处理的目录路径'
- )
-
- parser.add_argument(
- '--format',
- type=str,
- choices=['avif', 'jxl','webp'],
- default='avif',
- help='输出格式 (avif,webp 或 jxl, 默认: avif)'
- )
-
- parser.add_argument(
- '--quality',
- type=int,
- default=80,
- metavar='1-100',
- help='图像压缩质量 (1-100, 默认: 80)'
- )
-
- parser.add_argument(
- '--dry-run',
- action='store_true',
- help='预览模式，只显示操作不执行'
- )
-
- parser.add_argument(
- '--no-recursive',
- action='store_true',
- help='不递归处理子目录'
- )
-
- parser.add_argument(
- '--delete-backup',
- action='store_true',
- help='转换后删除备份文件（谨慎使用）'
- )
-
- parser.add_argument(
- '--no-compression-check',
- action='store_true',
- help='禁用压缩比检测，强制转换所有文件'
- )
-
- parser.add_argument(
- '--min-compression',
- type=float,
- default=5.0,
- metavar='PERCENT',
- help='最小压缩比百分比，低于此值跳过转换（默认: 5.0%%）'
- )
-
- parser.add_argument(
- '--threads',
- type=int,
- default=1,
- metavar='NUM',
- help='使用的线程数（默认: 1）'
- )
-
- parser.add_argument(
- '--report',
- action='store_true',
- help='显示详细的转换统计报告'
- )
-
- parser.add_argument(
- '--effort',
- type=int,
- default=7,
- choices=range(1, 10),
- metavar='1-9',
- help='JXL格式的编码速度等级 (1-9, 1最快/质量最低, 9最慢/质量最高, 默认: 7)'
- )
-
- parser.add_argument(
- '--version',
- action='version',
- version='Image Converter (Keep Name) v1.3'
- )
-
- args = parser.parse_args()
-
- # 检查依赖
- check_dependencies(args.format)
-
- # 验证参数
- if not os.path.exists(args.directory):
- print(f"错误: 目录不存在: {args.directory}")
- sys.exit(1)
-
- if not os.path.isdir(args.directory):
- print(f"错误: 不是一个目录: {args.directory}")
- sys.exit(1)
-
- if not (1 <= args.quality <= 100):
- print("错误: 质量参数必须在1-100之间")
- sys.exit(1)
-
- if not (0 <= args.min_compression <= 100):
- print("错误: 最小压缩比必须在0-100之间")
- sys.exit(1)
-
- # 创建转换器实例
- converter = ImageConverter(
- directory=args.directory,
- format=args.format,
- quality=args.quality,
- dry_run=args.dry_run,
- recursive=not args.no_recursive,
- delete_backup=args.delete_backup,
- check_compression=not args.no_compression_check,
- min_compression_ratio=args.min_compression / 100.0,
- threads=args.threads,
- effort=args.effort,
- show_report=args.report
- )
-
- # 执行转换
- try:
- converter.convert_all()
- except KeyboardInterrupt:
- print("\n\n用户中断操作")
- sys.exit(1)
- except Exception as e:
- print(f"\n发生错误: {e}")
- sys.exit(1)
-
-
-if __name__ == '__main__':
- main()
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