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output.html
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<title>ImageHash</title>
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<body>
<div class="document" id="imagehash">
<h1 class="title">ImageHash</h1>
<p>A image hashing library written in Python.
Supports:</p>
<ul class="simple">
<li>average hashing (aHash)</li>
<li>perception hashing (pHash)</li>
<li>difference hashing (dHash)</li>
</ul>
<div class="section" id="requirements">
<h1>Requirements</h1>
<p>Based on PIL Image, numpy and scipy.fftpack (for pHash)</p>
</div>
<div class="section" id="basic-usage">
<h1>Basic usage</h1>
<pre class="literal-block">
>>> 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
</pre>
<p>Demo function find_similar_images illustrates finding similar images in a directory.</p>
<p>References:</p>
<pre class="literal-block">
* pHash implementation following http://www.hackerfactor.com/blog/index.php?/archives/432-Looks-Like-It.html
* dHash implementation following http://www.hackerfactor.com/blog/index.php?/archives/529-Kind-of-Like-That.html
</pre>
</div>
</div>
</body>
</html>