How to batch process images using Python

How to use Python to batch process pictures

Introduction:
In today’s era of social media and digital culture, pictures have become indispensable in people’s daily lives. missing part. However, sometimes we need to perform the same operations on a large number of pictures, such as resizing, cropping, rotating, etc. Processing these images manually is very time consuming and tedious. Therefore, using Python to batch process images will greatly improve efficiency. This article will introduce how to use Python's Pillow library to batch process images and provide corresponding code examples.

Step 1: Install the Pillow library
Before we begin, we need to install the Pillow library first. Enter the following command on the command line to complete the installation:

pip install pillow

Step 2: Import the required libraries and modules
Before writing Python code, we need to import the required libraries and modules. Add the following lines to the code:

from PIL import Image
import os

Step 3: Set the input and output folder paths
Before batch processing, we need to set the paths of the input and output folders. The following example assumes that our input folder path is 'input_folder' and our output folder path is 'output_folder'. You can modify these paths according to your needs.

input_folder = 'path/to/input_folder'
output_folder = 'path/to/output_folder'

Step 4: Write an image processing function
Before writing the main loop, we first write a function to process images. The following example shows how to resize an image and save it to the output folder:

def process_image(input_path, output_path, width, height):
    image = Image.open(input_path)
    resized_image = image.resize((width, height))
    resized_image.save(output_path)

In this function, we first open the input image using Image.open() and call resize()Method to resize the image. Finally, we use the save() method to save the processed image to the specified output path.

You can add other image processing operations to this function according to your own needs, such as cropping, rotation, etc.

Step 5: Traverse the input folder and batch process
Now we can write the main loop to traverse all the pictures in the input folder and batch process each picture. The following example shows how to iterate through the input folder and call the above image processing function:

for filename in os.listdir(input_folder):
    if filename.endswith('.jpg') or filename.endswith('.png'):
        input_path = os.path.join(input_folder, filename)
        output_path = os.path.join(output_folder, filename)
        process_image(input_path, output_path, 800, 600)

In this example, we use the os.listdir() function to get all the files in the input folder file name, and use the os.path.join() function to concatenate the file name and folder path into a complete file path.

Then, we use the endswith() method to check whether the suffix of the file name is ".jpg" or ".png" so that only these image files can be processed.

Finally, we call the above process_image() function, passing the input path, output path and required image size as parameters. In this example, we set the image size to 800x600 pixels.

Summary:
By using Python’s Pillow library, we can easily batch process images. This article introduces an example of how to use the Pillow library to resize an image and provides a complete code example. You can extend these codes to add other image processing operations according to your needs. Start using Python to batch process images and improve work efficiency!

The above is an introduction to how to use Python to batch process images. Whether in a personal project or a commercial application, these tips will help you save time and energy. Hope this article helps you.

Reference:

• Python Software Foundation. (n.d.). Python Imaging Library (PIL). https://pypi.org/project/Pillow/
• Python Software Foundation. (2021). Python Imaging Library Handbook. https://pillow.readthedocs.io/en/stable/handbook/index.html

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