带统计带进度条多线程的python批量压缩图片

from PIL import Image
import os
import logging
from datetime import datetime
from concurrent.futures import ThreadPoolExecutor
from tqdm import tqdm

def resize_and_compress_image(input_path, quality, size_threshold_kb, max_width):
    try:
        # 获取图片文件大小
        file_size_kb = os.path.getsize(input_path) / 1024

        # 仅当图片大小大于300KB时进行压缩
        if file_size_kb > size_threshold_kb:
            # 打开图片
            img = Image.open(input_path)

            # 调整宽度为最大值1000像素
            if img.width > max_width:
                ratio = max_width / float(img.width)
                new_height = int(float(img.height) * float(ratio))
                img = img.resize((max_width, new_height), Image.LANCZOS)

            # 覆盖保存为JPEG或PNG格式，根据文件类型设置相应的参数
            if input_path.lower().endswith(('.jpg', '.jpeg')):
                img.save(input_path, 'JPEG', quality=quality, optimize=True)
            elif input_path.lower().endswith('.png'):
                img.save(input_path, 'PNG', optimize=True)

            logging.info(f"成功压缩图片: {input_path}")
            return True, file_size_kb
        else:
            logging.info(f"跳过小于{size_threshold_kb}KB的图片: {input_path}")
            return False, file_size_kb
    except Exception as e:
        logging.error(f"压缩图片时发生错误: {input_path}. 错误信息: {str(e)}")
        return False, 0

def resize_and_compress_images(input_folder, quality=85, size_threshold_kb=300, max_width=1000, num_threads=4):
    # 设置日志
    log_file = f"compression_log_{datetime.now().strftime('%Y%m%d%H%M%S')}.txt"
    logging.basicConfig(filename=log_file, level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s')

    # 获取总图片数
    total_images = sum([len(files) for _, _, files in os.walk(input_folder)])

    # 初始化tqdm
    progress_bar = tqdm(total=total_images, desc="处理进度")

    # 统计信息
    compressed_images = 0
    total_original_size = 0
    total_compressed_size = 0

    # 设置线程池
    with ThreadPoolExecutor(max_workers=num_threads) as executor:
        futures = []

        for root, dirs, files in os.walk(input_folder):
            for image_file in files:
                input_path = os.path.join(root, image_file)

                # 提交任务到线程池
                future = executor.submit(resize_and_compress_image, input_path, quality, size_threshold_kb, max_width)
                futures.append(future)

        # 等待所有任务完成
        for future in tqdm(futures, total=len(futures), desc="多线程处理"):
            success, file_size_kb = future.result()
            if success:
                compressed_images += 1
                total_original_size += file_size_kb
                total_compressed_size += os.path.getsize(future.result()) / 1024

            # 更新进度条
            progress_bar.update(1)

    # 关闭进度条
    progress_bar.close()

    # 计算压缩比例
    compression_ratio = 1.0 - (total_compressed_size / total_original_size) if total_original_size > 0 else 0

    # 记录统计信息
    logging.info(f"总共图片数: {total_images}")
    logging.info(f"成功压缩图片数: {compressed_images}")
    logging.info(f"总原始大小: {total_original_size:.2f} KB")
    logging.info(f"总压缩后大小: {total_compressed_size:.2f} KB")
    logging.info(f"总压缩比例: {compression_ratio * 100:.2f}%")

    # 输出日志文件路径
    print(f"日志文件路径: {os.path.abspath(log_file)}")

if __name__ == "__main__":
    # 输入文件夹（包含待压缩的JPEG和PNG图片）
    input_folder = "input_images"

    # 设置压缩质量（仅适用于JPEG，0-100，100为最高质量）
    compression_quality = 85

    # 设置图片大小阈值（大于该阈值才进行压缩）
    size_threshold_kb = 300

    # 设置最大宽度
    max_width = 1000

    # 设置线程数
    num_threads = 4

    # 执行图片压缩（直接覆盖原文件）
    resize_and_compress_images(input_folder, quality=compression_quality, size_threshold_kb=size_threshold_kb, max_width=max_width, num_threads=num_threads)

    print("图片压缩完成。日志文件详见压缩日志。")