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Image compression reduces file size while maintaining acceptable visual quality. Below are two popular methods to implement image compression using Python.
1. Using K-Means Clustering
This method reduces the number of colors in an image by clustering similar colors and replacing them with representative values.
Steps:
Install Required Libraries:
pip install numpy matplotlib scikit-learnCopied!âś•CopyLoad and Preprocess the Image: Convert the image into a 2D array of pixels.
Apply K-Means Clustering: Use the KMeans algorithm from sklearn to group pixels into k clusters.
Reconstruct the Image: Replace each pixel with its cluster's representative color.
Save the Compressed Image: Save the reconstructed image with reduced file size.
Code Example:
jpeg-image-compression · GitHub Topics · GitHub
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Jun 11, 2015 · Is there some Python package with a function that will take an image and quality number as inputs and return a jpeg version of that image with the given quality?
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Code sample
im1 = Image.open(IMAGE_FILE)buffer = StringIO.StringIO()im1.save(buffer, "JPEG", quality=10)with open("./photo-quality10.jpg", "w") as handle:handle.write(buffer.contents())...How to compress images using Python and PIL?
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