- Python Pillow Tutorial
- Python Pillow - Home
- Python Pillow - Overview
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- Basic Image Operations
- Python Pillow - Working with Images
- Python Pillow - Resizing an Image
- Python Pillow - Flip and Rotate Images
- Python Pillow - Cropping an Image
- Python Pillow - Adding Borders to Images
- Python Pillow - Identifying Image Files
- Python Pillow - Merging Images
- Python Pillow - Cutting and Pasting Images
- Python Pillow - Rolling an Image
- Python Pillow - Writing text on image
- Python Pillow - ImageDraw Module
- Python Pillow - Concatenating two Images
- Python Pillow - Creating Thumbnails
- Python Pillow - Creating a Watermark
- Python Pillow - Image Sequences
- Python Pillow Color Conversions
- Python Pillow - Colors on an Image
- Python Pillow - Creating Images With Colors
- Python Pillow - Converting Color String to RGB Color Values
- Python Pillow - Converting Color String to Grayscale Values
- Python Pillow - Change the Color by Changing the Pixel Values
- Image Manipulation
- Python Pillow - Reducing Noise
- Python Pillow - Changing Image Modes
- Python Pillow - Compositing Images
- Python Pillow - Working with Alpha Channels
- Python Pillow - Applying Perspective Transforms
- Image Filtering
- Python Pillow - Adding Filters to an Image
- Python Pillow - Convolution Filters
- Python Pillow - Blur an Image
- Python Pillow - Edge Detection
- Python Pillow - Embossing Images
- Python Pillow - Enhancing Edges
- Python Pillow - Unsharp Mask Filter
- Image Enhancement and Correction
- Python Pillow - Enhancing Contrast
- Python Pillow - Enhancing Sharpness
- Python Pillow - Enhancing Color
- Python Pillow - Correcting Color Balance
- Python Pillow - Removing Noise
- Image Analysis
- Python Pillow - Extracting Image Metadata
- Python Pillow - Identifying Colors
- Advanced Topics
- Python Pillow - Creating Animated GIFs
- Python Pillow - Batch Processing Images
- Python Pillow - Converting Image File Formats
- Python Pillow - Adding Padding to an Image
- Python Pillow - Color Inversion
- Python Pillow - M L with Numpy
- Python Pillow with Tkinter BitmapImage and PhotoImage objects
- Image Module
- Python Pillow - Image Blending
- Python Pillow Useful Resources
- Python Pillow - Quick Guide
- Python Pillow - Function Reference
- Python Pillow - Useful Resources
- Python Pillow - Discussion
Python Pillow - ImageChops.darker() Function
The PIL.ImageChops.darker function compares the two input images pixel by pixel and returns a new image containing the darker values from each corresponding pair of pixels.
The operation is defined as follows −
$$\mathrm{Out\:=\:min(image1,image2)}$$
Syntax
Following is the syntax of the function −
PIL.ImageChops.darker(image1, image2)
Parameters
Here are the details of this function parameters −
image1 − The first input image.
image2 − The second input image.
Return Value
The return type of this function is an Image.
Examples
Example 1
In this example, the ImageChops.darker() function is applied to two random RGB images (image1 and image2) to create a new image containing the darker values among the two input images. Here we will observe the pixel values of the two input images, and the output image at a specified location using the getpixel() function.
from PIL import Image, ImageChops import numpy as np # Create two random RGB images image1 = Image.fromarray(np.array([(35, 64, 3), (255, 0, 0), (255, 255, 0), (255, 255, 255), (164, 0, 3)]), mode="RGB") print("Pixel values of image1 at (0, 0):", image1.getpixel((0, 0))) image2 = Image.fromarray(np.array([(25, 14, 3), (25, 222, 0), (255, 155, 0), (255, 55, 100), (180, 0, 78)]), mode="RGB") print("Pixel values of image2 at (0, 0):", image2.getpixel((0, 0))) # Get the darker values of the two images result = ImageChops.darker(image1, image2) print("Pixel values of the result at (0, 0) after darker:", result.getpixel((0, 0)))
Output
Pixel values of image1 at (0, 0): (35, 0, 0) Pixel values of image2 at (0, 0): (25, 0, 0) Pixel values of the result at (0, 0) after darker: (25, 0, 0)
Example 2
In this example, ImageChops.darker() function is used to compare the pixel values of two input pixels to select the darker values for each corresponding pixel pair.
from PIL import Image, ImageChops # Open two image files image1 = Image.open('Images/black rose.jpg') image2 = Image.open('Images/black-doted-butterflies.jpg') # Compare the two images pixel by pixel and get the darker values result = ImageChops.darker(image1, image2) # Display the input and resulting images image1.show() image2.show()
Output
Input Image 1
Input Image 2
Output Image
Example 3
Here is an example that uses the ImageChops.darker() function on two PNG image files to get a new images with darker values.
from PIL import Image, ImageChops # Open two image files image1 = Image.open('Images/dark_img1.png') image2 = Image.open('Images/dark_img2.png') # Compare the two images pixel by pixel and get the darker values result = ImageChops.darker(image1, image2) # Display the input and resulting images image1.show() image2.show() result.show()
Output
Input Image 1
Input Image 2
Output Image