Category: python Pillow

Python pillow – Overview ”; Previous Next In today’s digital world, we come across lots of digital images. In case, we are working with Python programming language, it provides lot of image processing libraries to add image processing capabilities to digital images. Some of the most common image processing libraries are: OpenCV, Scikit-image, Pillow, Mahotas and more. However, in this tutorial, we are only focusing on Pillow library and will try to explore various capabilities of this module. What is Pillow? Pillow or the Python Imaging Library (PIL) fork by Jeffrey A.Clark and contributors, is a powerful Python library for working with digital images and Image processing. It”s built on top of the Python Image Library (PIL) and offers a wide range of functionalities for working with images. It provides extensive functionality for opening, manipulating and saving images in various formats. Pillow is a widely used tool in applications involving image processing, computer vision, web development, graphic design and more. Pillow offers a wide range of tools and functions for image processing, allowing you to perform tasks such as − Opening and Loading Images − Pillow allows us to open and load images in various formats making them available for processing. Resizing and Scaling − We can resize images to specific dimensions, scale them up or down and generate thumbnails. Cropping − Image cropping involves removing unwanted portions of an image to focus on a specific region. Rotation and Flipping − Images can be rotated to correct orientation or for creative purposes. We can also flip images horizontally or vertically. Color Adjustment − Pillow provides functions to adjust image properties, including brightness, contrast and color balance. Filtering and Effects − Image filtering involves applying filters like blurring, sharpening, edge detection and various effects to enhance or modify the appearance of images. Text and Drawing − We can add text, shapes and drawings to images which is useful for annotation and labeling. Color Mode Conversion − Pillow supports converting images between different color modes such as RGB, grayscale and CMYK. Histogram Equalization − This is a technique for enhancing the contrast of an image by redistributing pixel values. Image Filtering − We can apply custom convolution filters to images allowing for advanced image processing operations. Geometric Transformations − Pillow supports geometric transformations like affine and perspective transformations which are used for tasks such as correcting image distortion. Merging and Compositing − We can merge multiple images or overlay images to create composite images or visual effects. Metadata Handling − Pillow allows us to access and modify image metadata such as EXIF and ICC profiles which can be useful for data extraction and management. Data Access and Analysis − We can access and manipulate pixel data at a low level enabling more advanced image processing and analysis tasks. Why Pillow? Pillow is a preferred choice for image processing in Python due to its − Image Processing Capabilities − Pillow provides a comprehensive set of tools for image manipulation such as opening, editing, enhancing and saving images. It supports various image formats for making it versatile for handling different types of image data. Ease of Use − Python as a high-level programming language is known for its readability and simplicity. Pillow inherits these characteristics and making it easy for developers to work with images even if they have minimal experience in image processing. Platform Independence − Python is platform-independent and so is Pillow. This means we can use Pillow to process images on different operating systems without worrying about compatibility issues. Abundance of Documentation − Python and Pillow have extensive documentation, tutorials and a supportive community which simplifies the learning curve for newcomers and provides a wealth of resources for experienced developers. Integration with Other Libraries − Python can seamlessly integrate Pillow with other popular libraries and frameworks such as NumPy and OpenCV for advanced image processing and computer vision tasks. Open Source − Both Python and Pillow are open-source which means they are free to use and continually improved by a large community of contributors. Basic Example Here is a basic example to get you started with Pillow. Opening and Displaying an Image This example demonstrates how to open and display an image in Python Pillow. from PIL import Image #Load an image loaded_image = Image.open(“Images/logo-w.png”) # Display the image loaded_image.show() Output The above code will load an image from the specified path and display it using the default image viewer on your system. Print Page Previous Next Advertisements ”;

Python Pillow – Merging Images ”; Previous Next Pillow (PIL) library is used for merging or combining individual bands of an image to create a new multiband image. It”s particularly useful when working with multispectral or multichannel images such as RGB or CMYK images and we want to create a new image by merging specific bands. In pillow we have the merge() method which belongs to the Image module which is used to merge the given input images. This method is useful for tasks like combining multiple channels of satellite or medical images, creating custom color images or working with images that have separate channels that need to be combined into a single image. Here”s the syntax and usage of the Image.merge() method − Image.merge(mode, bands) Where, mode − This parameter specifies the mode of the new multiband image. It should match the mode of the individual bands we want to merge. Common modes include “RGB” for color images, “RGBA” for images with an alpha channel, and “CMYK” for cyan, magenta, yellow and black color spaces. bands − This parameter is a tuple of individual image bands that we want to merge. Each band should be a single-channel image or a grayscale image. Example Here is an example of how to use the Image.merge() method to merge the red, green and blue bands of an image to create a new RGB image. from PIL import Image image = Image.open(“Images/butterfly.jpg”) r, g, b = image.split() image = Image.merge(“RGB”, (b, g, r)) image.show() Image to be used Output Example Here, in this example we are merging two input images by using the merge() method of the Image module of pillow library. from PIL import Image image1 = Image.open(“Images/butterfly.jpg”) image2 = Image.open(“Images/hand writing.jpg”) #resize, first image image1 = image1.resize((426, 240)) image1_size = image1.size image2_size = image2.size new_image = Image.new(“RGB”,(2*image1_size[0], image1_size[1]), (250,250,250)) new_image.paste(image1,(0,0)) new_image.paste(image2,(image1_size[0],1)) new_image.save(“output Image/merged.jpg”) new_image.show() The two images to be merged Output Print Page Previous Next Advertisements ”;

Pillow – Resizing an Image ”; Previous Next Resizing an image in Pillow Library involves changing the dimensions i.e. width and height of the image. This operation can be used to make an image larger or smaller and it can serve various purposes such as preparing images for display on a website, reducing file size or generating thumbnails. Resizing an Image using the resize() method In Pillow the resize() method is used to change the dimensions of an image. This function allows us to resize an image in the following ways. Absolute Dimensions − We can specify the new width and height in pixels to which the image should be resized. Maintaining Aspect Ratio − If We only specify one dimension either width or height then Pillow can automatically calculate the other dimension to maintain the image”s aspect ratio. Scaling − We can resize the image by a scale factor which uniformly resizes both width and height while preserving the aspect ratio. Here”s the basic syntax for the resize() method − PIL.Image.resize(size, resample=3) Where, size − This can be either a tuple specifying the new width and height in pixels i.e. a single integer specifying the new size (width or height) or a float specifying a scaling factor. resample(optional) − The default value is 3 which corresponds to the anti-aliased high-quality filter. We can choose from various resampling filters such as Image.NEAREST, Image.BOX, Image.BILINEAR, Image.HAMMING, Image.BICUBIC, Image.LANCZOS, etc. Following is the input image used in all the examples of this chapter. Example In this example we are using the resize() function for adjusting the width and height of the image by passing a tuple as input parameter. from PIL import Image #Open an image image = Image.open(“Images/rose.jpg”) #Resize to specific dimensions (e.g., 300×200 pixels) new_size = (300, 200) resized_image = image.resize(new_size) #Display resized image resized_image.show() Output Example Here in this example we are resizing the image by maintaining the same aspect ratio of the original input image. from PIL import Image #Open an image image = Image.open(“Images/rose.jpg”) #Resize by maintaining aspect ratio (e.g., specify the width) new_width = 200 aspect_ratio_preserved = image.resize((new_width, int(image.height * (new_width / image.width)))) aspect_ratio_preserved.show() Output Example In this example we are resizing the image with the scale by factor. from PIL import Image #Open an image image = Image.open(“Images/rose.jpg”) #Scale the image by a factor (e.g., 10% of the original size) scaling_factor = 0.1 scaled_image = image.resize((int(image.width * scaling_factor), int(image.height * scaling_factor))) scaled_image.show() Output Print Page Previous Next Advertisements ”;

Python Pillow Tutorial Table of content Python Pillow Tutorial Why to Learn Python Pillow? Features of Python Pillow Applications of Python Pillow Installing Python Pillow Who Should Learn Python Pillow Python Pillow Jobs and Opportunities Prerequisites to Learn Python Pillow Frequently Asked Questions about Python Pillow PDF Version Quick Guide Resources Job Search Discussion Python Pillow Tutorial Pillow or the Python Imaging Library (PIL) fork by Jeffrey A.Clark and contributors, is an open-source library that makes it easy to work with images in Python. It is one of the important libraries of python for image processing. It provides a comprehensive suite of tools and functions for image processing tasks, from basic operations to advanced image manipulation. In this tutorial, you will see the hands-on approach to learn different functionalities of pillow, From loading and saving images to performing image enhancements, transformations, and more. Why to Learn Python Pillow? Learning Pillow is essential for anyone interested in image processing using Python. Its ease of use and integration with other Python libraries make it a valuable tool for a variety of applications, from basic image manipulations to advanced computer vision projects. Pillow supports a wide range of image file formats, including JPEG, PNG, GIF, TIFF, and many others. This flexibility allows you to read images from various sources and save your processed images in the desired format. Whether you are working on simple image resizing or complex image transformations, Pillow has the capabilities you need. By mastering Pillow, you”ll be able to handle images effortlessly, extract useful information, and apply meaningful transformations to visual data. Features of Python Pillow Following are the main features of Python Pillow − Pillow is an open-source library, freely available for use and contribution. Easy to read and write images of various formats. The library support for various image formats including JPEG, PNG, GIF, TIFF, BMP, and more. This flexibility allows you to handle images from different sources. It offers a wide range of image processing tools, making it easy to manipulate and transform images to meet specific needs. The library includes various predefined image enhancement filters, such as brightness, sharpness, and color adjustments. Additionally, it supports different image filters for effects like blurring, contouring, and edge detection. With Pillow, you can perform complex image transformations such as affine, perspective, and projective transformations, allowing for advanced image manipulation tasks. And it offers a user-friendly API that simplifies the process of performing image processing tasks. Applications of Python Pillow Pillow is a powerful tool widely used in various applications involving image processing and computer vision. Whether you are developing web applications that require image uploads, creating image processing scripts, or analyzing images, Pillow provides a rich set of tools to achieve your goals. And this Library is best suited for image archival and batch processing applications. Installing Python Pillow To install Pillow you can simply use pip (the default package manager for Python), just run the below command in your command prompt − pip install pillow For detailed installation instructions, visit the Environment Setup chapter. Who Should Learn Python Pillow? This tutorial is basically designed to work as a guide for individuals who wants to learn python capabilities, automate image editing. It is also for the beginners who wish to know the image processing capabilities of python using pillow package and for the web developers who wants to update and use images with logos & watermark on their websites. Python Pillow Jobs and Opportunities Proficiency in Pillow opens up a range of career opportunities in industries such as − Web Development Data Science Machine Learning Computer Vision Job roles like Image Processing Engineer, Computer Vision Developer, Data Scientist specializing in image analysis, Machine Learning Engineer, and Data Analyst often require knowledge of Pillow. Prerequisites to Learn Python Pillow To get started with Pillow, familiarity with Python programming is essential. Knowledge of basic concepts such as python data types, functions, and libraries will help you understand Pillow”s functionality more effectively. Additionally, being comfortable with installing Python packages using pip (e.g., “pip install pillow”) will be helpful. Frequently Asked Questions about Python Pillow There are some very Frequently Asked Questions(FAQ) about Python Pillow, this section tries to answer them briefly. What is Pillow in Python used for? Pillow is a powerful library used for image processing in Python. What are the capabilities of Pillow in Python? Pillow allows users to perform various image processing tasks such as opening and loading images, resizing, cropping, rotation, color adjustment, filtering, text and drawing, color mode conversion, histogram equalization, metadata handling, and more. How to resize image in python pillow? To resize an image in Python using Pillow, you can use the resize() function from the pillow’s Image module. How to install pillow in Python? Installing Pillow in Python can be done by using pip or conda installers, which depends on your preference. You can install Pillow in Python using pip. Simply run pip install Pillow in your command prompt or terminal. What color format is Python pillow? Python Pillow supports various color formats, including RGB, RGBA, CMYK, and grayscale. Is Pillow a standard Python library? No, Pillow is not a standard Python library it is not integrated in the standard library and does not come with distributions of Python. You need to install it separately using pip. What formats can pillow Python save? Pillow in Python can save images in various formats, including JPEG, PNG, BMP, GIF, TIFF, BPL, and many more. Which Python version supports Pillow? The current Pillow versions 10.1 supports the following Python versions − Python 3.12 Python 3.11 Python 3.10 Python 3.9 Python 3.8 Which is the best place to learn Python Pillow? You can use our simple and the best Python Pillow tutorial to learn Python Pillow. Our tutorial offers an excellent starting point for learning Image processing with Python Pillow. You can explore our simple and effective learning materials at your own pace. Also, you can find resources to learn Python Pillow on