【Related learning recommendations: python tutorial】
Preface
When I was preprocessing some training images of the project team, I found that the processed images were divided into categories and stored in nesting doll style in folders within folders, so I batch processed them and processed them according to the original When folder rules are stored, it will cause a lot of trouble
But through the combination of the following functions, it helped me successfully complete a series of preprocessing.
1. Use the Zhishan library that you won’t get tired of
##1. Install the library
pip Installation:pip install zisan
2.getFiles function
Function call:import zisan.FileTools as zf file_path = 'C:/Users/xxx/Desktop/2016/Annotations' whole_file = zf.getFiles(file_path)Pictures are stored in: Folder 2016 -> Folder Annotations -> ;Subfolder-> 00000.png
Through the getFiles function, you can call out all the picture paths in all folders in Annotations
2. Other functions
1.os.listdir function
After this function is called, it will return the name of the folder under the path, which is stored in the list in the form of a string The code is as follows:import os file_path = 'C:/Users/xxx/Desktop/2016/Annotations' file_names = os.listdir(file_path) print(file_names)Effect:
2.os.mkdir function
Code:import os new_file_path = 'C:/Users/xxx/Destop/2016/newfile' os.mkdir(new_file_path)Used to create new folders
3. Application
Requirements: Process each sub-file in the Annotations folder folder, and store them in the corresponding location in the new file folder according to the original rules. The naming rules are such as 00000.jpgimport zisan.FileTools as zf import os import cv2 from skimage import io file_path = 'C:/Users/xxx/Desktop/2016/Annotations' new_file_path = 'C:/Users/xxx/Destop/2016/newfile' file_names = os.listdir(file_path) #获取Annotations文件夹的子文件夹名称 for i in file_names: #遍历每个子文件夹名称 Index = 0 file_name = file_path + '/' + i #巧妙运用+号得到改子文件夹的路径 os.mkdir(new_file_path + '/' + i) #在newfile里创建一个与子文件夹名称相同的文件夹 whole_pic = zf.getFiles(file_name) #用getFiles函数读取子文件夹内的图片路径 for f in whole_pic: msk = io.imread(f) msk=cv2.cvtColor(msk,cv2.COLOR_RGBA2GRAY) msk[np.where(msk!=0)]=255 io.imsave(new_file_path + '/' + i + '/' + str("%05d" % Index) + '.jpg' , msk) #处理命名可直接+'.jpg'让其以jepg形式存储 Index += 1. This is my basic idea and process for solving the problem of folder processing. Each function It can be used in combination and placed outside or inside the loop to have different effects according to specific requirements.
The above is the detailed content of How to batch process matryoshka-style folders via Python. For more information, please follow other related articles on the PHP Chinese website!

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Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

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