ImageHash
A image hashing library written in Python. ImageHash supports:
average hashing (aHash)
perception hashing (pHash)
difference hashing (dHash)
wavelet hashing (wHash)
Requirements
Based on PIL/Pillow Image, numpy and scipy.fftpack (for pHash) Easy installation through pypi.
Basic usage
>>> from PIL import Image
>>> import imagehash
>>> hash = imagehash.average_hash(Image.open('test.png'))
>>> print(hash)
d879f8f89b1bbf
>>> otherhash = imagehash.average_hash(Image.open('other.bmp'))
>>> print(otherhash)
ffff3720200ffff
>>> print(hash == otherhash)
False
>>> print(hash - otherhash)
36
The demo script find_similar_images illustrates how to find similar images in a directory.
Source hosted at github: https://github.com/JohannesBuchner/imagehash
1 maintainer
Release files for ImageHash 2.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ImageHash-2.1.tar.gz | 4.8 kB | Details |
Release files / ImageHash-2.1.tar.gz
| Download URL | ImageHash-2.1.tar.gz |
|---|---|
| Size | 4.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
7e52d443ac29dc6475417207617dfa8e9f76dfe3451c1fb1927d53d1dd55a16b
|
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BLAKE2b-256 checksum How to use checksums |
5547f841e9b6b79b875a11ef5fe3684ab1c761a75d31939866906bf60f71d5d9
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
