107 lines
3.9 KiB
Text
107 lines
3.9 KiB
Text
Metadata-Version: 2.4
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Name: blurhash
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Version: 1.1.5
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Summary: Pure-Python implementation of the blurhash algorithm.
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Home-page: https://github.com/halcy/blurhash-python
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Author: Lorenz Diener
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Author-email: lorenzd+blurhashpypi@gmail.com
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License: MIT
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Keywords: blurhash graphics web_development
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Classifier: Development Status :: 5 - Production/Stable
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Classifier: Intended Audience :: Developers
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Classifier: Topic :: Multimedia :: Graphics
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Classifier: License :: OSI Approved :: MIT License
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Classifier: Programming Language :: Python :: 2
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Classifier: Programming Language :: Python :: 3
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Description-Content-Type: text/markdown
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License-File: LICENSE
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Provides-Extra: test
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Requires-Dist: pytest; extra == "test"
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Requires-Dist: Pillow; extra == "test"
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Requires-Dist: numpy; extra == "test"
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Dynamic: author
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Dynamic: author-email
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Dynamic: classifier
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Dynamic: home-page
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Dynamic: keywords
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Dynamic: license
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Dynamic: license-file
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Dynamic: provides-extra
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Dynamic: summary
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# blurhash-python
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```python
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import blurhash
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import PIL.Image
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import numpy
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PIL.Image.open("cool_cat_small.jpg")
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# Result:
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```
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```python
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blurhash.encode(numpy.array(PIL.Image.open("cool_cat_small.jpg").convert("RGB")))
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# Result: 'UBL_:rOpGG-oBUNG,qRj2so|=eE1w^n4S5NH'
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PIL.Image.fromarray(numpy.array(blurhash.decode('UBL_:rOpGG-oBUNG,qRj2so|=eE1w^n4S5NH', 128, 128)).astype('uint8'))
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# Result:
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```
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Blurhash is an algorithm that lets you transform image data into a small text representation of a blurred version of the image. This is useful since this small textual representation can be included when sending objects that may have images attached around, which then can be used to quickly create a placeholder for images that are still loading or that should be hidden behind a content warning.
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This library contains a pure-python implementation of the blurhash algorithm, closely following the original swift implementation by Dag Ågren. The module has no dependencies (the unit tests require PIL and numpy). You can install it via pip:
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```bash
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$ pip3 install blurhash
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```
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It exports five functions:
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* "encode" and "decode" do the actual en- and decoding of blurhash strings
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* "components" returns the number of components x- and y components of a blurhash
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* "srgb_to_linear" and "linear_to_srgb" are colour space conversion helpers
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Have a look at example.py for an example of how to use all of these working together.
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Documentation for each function:
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```python
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blurhash.encode(image, components_x = 4, components_y = 4, linear = False):
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"""
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Calculates the blurhash for an image using the given x and y component counts.
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Image should be a 3-dimensional array, with the first dimension being y, the second
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being x, and the third being the three rgb components that are assumed to be 0-255
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srgb integers (incidentally, this is the format you will get from a PIL RGB image).
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You can also pass in already linear data - to do this, set linear to True. This is
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useful if you want to encode a version of your image resized to a smaller size (which
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you should ideally do in linear colour).
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"""
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blurhash.decode(blurhash, width, height, punch = 1.0, linear = False)
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"""
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Decodes the given blurhash to an image of the specified size.
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Returns the resulting image a list of lists of 3-value sRGB 8 bit integer
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lists. Set linear to True if you would prefer to get linear floating point
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RGB back.
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The punch parameter can be used to de- or increase the contrast of the
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resulting image.
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As per the original implementation it is suggested to only decode
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to a relatively small size and then scale the result up, as it
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basically looks the same anyways.
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"""
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blurhash.srgb_to_linear(value):
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"""
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srgb 0-255 integer to linear 0.0-1.0 floating point conversion.
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"""
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blurhash.linear_to_srgb(value):
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"""
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linear 0.0-1.0 floating point to srgb 0-255 integer conversion.
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"""
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```
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