A Python Perceptual Image Hashing Module
Project description
This was mainly created just for my own use and education. It’s a perceptual hash algorithm, used to find if two images are similar.
Installation
pip install PhotoHash
Usage
average_hash
Returns the hash of the image using an average hash algorithm. This algorithm compares each pixel in the image to the average value of all the pixels.:
import photohash hash = photohash.average_hash('/path/to/myimage.jpg')
distance
Returns the hamming distance between the average_hash of the given images.:
import photohash distance = photohash.distance('/path/to/myimage.jpg', '/path/to/myotherimage.jpg')
is_look_alike
Returns a boolean of whether or not the photos look similar.:
import photohash similar = photohash.is_look_alike('/path/to/myimage.jpg', '/path/to/myotherimage.jpg')
is_look_alike also takes an optional tolerance argument that defines how strict the comparison should be.:
import photohash similar = photohash.is_look_alike('/path/to/myimage.jpg', '/path/to/myimage.jpg', tolerance=3)
TODO
Add more hash algorithms.
Project details
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PhotoHash-0.3.0.tar.gz
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