异步协程开发实战：优化图片识别与处理的速度

import asyncio
from PIL import Image

async def process_image(image_path):
    # 读取图片
    image = Image.open(image_path)

    # 图片处理代码
    # ...

    await asyncio.sleep(0)  # 模拟CPU密集型任务

    # 保存图片
    processed_image_path = 'processed_' + image_path
    image.save(processed_image_path)

    return processed_image_path

async def process_folder(folder_path):
    files = os.listdir(folder_path)

    tasks = []
    for file in files:
        file_path = os.path.join(folder_path, file)
        task = asyncio.create_task(process_image(file_path))  # 创建图片处理任务
        tasks.append(task)

    processed_images = await asyncio.gather(*tasks)

    return processed_images

async def main():
    folder_path = 'image_folder'
    processed_images = await process_folder(folder_path)

    for image in processed_images:
        print('Processed image:', image)

if __name__ == '__main__':
    asyncio.run(main())