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Lots of documentation! It's hosted!

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Sofus Albert Høgsbro Rose 2017-01-25 23:13:57 -05:00
parent 892d511525
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GPG Key ID: 3D01BE95F3EFFEB9
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doc/source/_themes/sphinx_rtd_theme 120000
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sphinx_rtd_theme_git/sphinx_rtd_theme/

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doc/source/_themes/sphinx_rtd_theme_git 160000

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doc/source/builtins.rst 100644
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Builtin Resources
=================
openlut.gamma module
--------------------
.. automodule:: openlut.gamma
:members:
:undoc-members:
:show-inheritance:
openlut.gamut module
--------------------
.. automodule:: openlut.gamut
:members:
:undoc-members:
:show-inheritance:
openlut.lib.olOpt module
------------------------
olOpt is the reason openlut is snappy! It contains the lower-level, fast functions
that drive the rest of openlut.
.. automodule:: openlut.lib.olOpt
:members:
:undoc-members:
:show-inheritance:

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doc/source/conf.py
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@ -63,9 +63,9 @@ author = u'Sofus Rose'
# built documents.
#
# The short X.Y version.
version = u'0.0.1'
version = u'0.2.1'
# The full version, including alpha/beta/rc tags.
release = u'0.0.1'
release = u'0.2.1'
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
@ -125,16 +125,18 @@ todo_include_todos = False
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
#
html_theme = 'alabaster'
html_theme = 'sphinx_rtd_theme'
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
#
# html_theme_options = {}
html_theme_options = {
"collapse_navigation" : False
}
# Add any paths that contain custom themes here, relative to this directory.
# html_theme_path = []
html_theme_path = ["_themes",]
# The name for this set of Sphinx documents.
# "<project> v<release> documentation" by default.

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doc/source/imageio.rst 100644
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Image Input/Output
=================
All image IO happens via the ColMap module.
openlut.ColMap module
---------------------
.. automodule:: openlut.ColMap
:members:
:undoc-members:
:show-inheritance:

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doc/source/index.rst
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@ -6,11 +6,16 @@
Welcome to openlut's documentation!
===================================
Contents:
Table of Contents:
.. toctree::
:maxdepth: 2
:maxdepth: 4
intro
imageio
transforms
builtins
Indices and tables
@ -20,3 +25,12 @@ Indices and tables
* :ref:`modindex`
* :ref:`search`
Full Docs
=========
No nice explanations here - just all the docs in a list.
.. toctree::
:maxdepth: 3
modules

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doc/source/intro.rst 100644
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Introduction to openlut
======================
Hello! TBD

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doc/source/modules.rst
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@ -1,4 +1,4 @@
openlut
Full Documentation
=======
.. toctree::

68
doc/source/openlut.rst
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@ -8,66 +8,6 @@ Subpackages
openlut.lib
Submodules
----------
openlut.ColMap module
---------------------
.. automodule:: openlut.ColMap
:members:
:undoc-members:
:show-inheritance:
openlut.ColMat module
---------------------
.. automodule:: openlut.ColMat
:members:
:undoc-members:
:show-inheritance:
openlut.Func module
-------------------
.. automodule:: openlut.Func
:members:
:undoc-members:
:show-inheritance:
openlut.LUT module
------------------
.. automodule:: openlut.LUT
:members:
:undoc-members:
:show-inheritance:
openlut.Transform module
------------------------
.. automodule:: openlut.Transform
:members:
:undoc-members:
:show-inheritance:
openlut.gamma module
--------------------
.. automodule:: openlut.gamma
:members:
:undoc-members:
:show-inheritance:
openlut.gamut module
--------------------
.. automodule:: openlut.gamut
:members:
:undoc-members:
:show-inheritance:
Module contents
---------------
@ -75,3 +15,11 @@ Module contents
:members:
:undoc-members:
:show-inheritance:
C++ Extension: olOpt
--------------
.. automodule:: openlut.lib.olOpt
:members:
:undoc-members:
:show-inheritance:

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doc/source/transforms.rst 100644
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Transforms
=================
Doing image transforms in openlut uses the :py:func:`~ColMap.apply` method to apply Transform objects. A Transform
object is any subclass of the Transform listed below. Examples include LUT, Func, and ColMat.
openlut.Transform module
------------------------
.. automodule:: openlut.Transform
:members:
:undoc-members:
:show-inheritance:
openlut.LUT module
------------------
.. automodule:: openlut.LUT
:members:
:undoc-members:
:show-inheritance:
openlut.Func module
-------------------
.. automodule:: openlut.Func
:members:
:undoc-members:
:show-inheritance:
openlut.ColMat module
---------------------
.. automodule:: openlut.ColMat
:members:
:undoc-members:
:show-inheritance:

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doc/upload.sh 100755
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#!/bin/bash
REMOTE=sofus@wakingnexus
rsync -avzP build/html/* $REMOTE:~/openlut/
#ssh $REMOTE 'bash -s' << 'ENDSSH'
#
#cd /var/www/openlut
#chown -R www-data:www-data *
#
#ENDSSH

1
interp.py
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@ -1,6 +1,7 @@
from functools import reduce
from imp import reload
import numpy as np
import openlut as ol
from openlut.lib.files import Log

322
openlut/ColMap.py
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@ -1,14 +1,9 @@
import sys, os, os.path
from functools import reduce
import numpy as np
#~ import skimage as si
#~ import skimage.io
#~ si.io.use_plugin('freeimage')
#~ from PIL import Image
#~ import tifffile as tff
import wand
import wand.image
import wand.display
@ -24,38 +19,134 @@ from . import gamma
from .LUT import LUT
from .Viewer import Viewer
from .lib import olOpt as olo
class ColMap :
def __init__(self, resX, resY, depth = 16) :
self.depth = depth
self.rgbArr =
'''
The ColMap class stores an image in its 32 bit float internal working space.
:var DEPTHS: A dictionary of depths in relation to the Depths dictionary.
ColMaps are initialized by default with 0's; a black image. You can use
`open` to load a path, :py:func:`~fromArray` to load from a numpy array, or :py:func:`~fromBinary` to load from
a binary representation (useful in pipes).
:param shape: The numpy-style shape of the empty image. Specify width, then height.
:type shape: tuple[int, int] or tuple[int, int, int]
:param depth: The integer depth used for int format's input and output. Set to DEPTHS['full'] by default.
:type depth: int or None
:return: An empty ColMap, holding a black image of specified shape.
:raises ValueError: When trying to use unsupported bit depth.
:raises ValueError: When using invalid image shape.
'''
DEPTHS = { 'default' : None,
'comp' : 8,
'half' : 16,
'full' : 32,
'double' : 64
}
#Constructors
def __init__(self, shape, depth = None) :
if depth not in ColMap.DEPTHS.values :
raise ValueError('Bit depth not supported! Supported bit depths: {}'.format(', '.join(ColMap.DEPTHS.values)))
if len(shape) not in (2, 3) :
raise ValueError('Please use a valid numpy image array shape!')
self.depth = depth if depth is None else ColMap.DEPTHS['full'] #This represents the real precision of data.
self.rgbArr = np.zeros((shape[0], shape[1], 3), dtype=np.float32)
@staticmethod
def fromArray(imgArr, depth = 16) :
self.depth = depth
def fromArray(imgArr) :
'''
Initialize a ColMap from a numpy array of either float or int type (containing an image).
self.rgbArr = np.array(rgbArr, dtype=np.float32) #Enforce 32 bit floats. Save memory.
See :py:class:`~ColMap` initialization for a lower-level constructor.
@staticmethod
def fromIntArray(imgArr) :
:param imgArr: The numpy image array. Must have shape (width, height, 3)
:param depth: The integer depth used for int format's input and output. None will use highest available.
:type depth: int or None
:return: A ColMap containing the image represented in imgArr.
:raises ValueError: When trying to use unsupported array data type
'''
#Infer bitDepth from array to create new array, nArr, which we'll use to make our ColMap.
if issubclass(imgArr.dtype.type, np.integer) : #If it's an integer.
bitDepth = int(''.join([i for i in str(imgArr.dtype) if i.isdigit()]))
self.depth = bitDepth
nArr = np.divide(imgArr.astype(np.float32), 2 ** bitDepth - 1)
return ColMap(np.divide(imgArr.astype(np.float32), 2 ** bitDepth - 1))
elif issubclass(imgArr.dtype.type, np.floating) : #It it's a float.
#If we're dealing with an np.float16 array, we can't exactly start giving 32 bit output.
if int(''.join([i for i in str(imgArr.dtype) if i.isdigit()])) == 16 :
bitDepth = 16
else :
bitDepth = None
#Operations - returns new ColMaps.
def apply(self, transform) :
nArr = np.array(imgArr, dtype=np.float32)
else :
raise ValueError('The input image array uses an invalid data type {}! Please use any np.int or np.float variant!'.format(imgArr.dtype.type))
#We're taking over the creation of img.rgbArr, so we need to do different error checking of our own.
if len(nArr.shape) not in (2, 3) :
raise ValueError('Please use a valid numpy image array shape!')
elif len(nArr.shape) == 2 :
#If we're dealing with a greyscale image, then we need to convert it to RGB using an optimized C++ function.
nArr = olo.grey_to_rgb(nArr.reshape(reduce(lambda a, b: a*b, nArr.shape))).reshape((nArr.shape[0], nArr.shape[1], 3))
img = ColMap(nArr.shape, depth=bitDepth)
img.rgbArr = nArr
return img
@staticmethod
def fromBinary(binData, fmt, width=None, height=None) :
'''
Applies a Transform object by running its apply method.
'''
#~ return transform.apply(self)
return ColMap.fromArray(transform.sample(self.asarray()))
Construct a ColMap from an image in binary form. See :py:func:`~ColMap.toBinary` for the inverse.
* This won't work for greyscale data - it's assumed to be RGB.
:param bin binData: The binary data blob to open.
:param str fmt: Wand needs to know what image format the binary data being thrown at it is in! See https://www.imagemagick.org/script/formats.php .
:param str width: You may specify a specific width if you're having problems.
:param str height: You may specify a specific height if you're having problems.
:return: The image, as a ColMat.
:rtype: :py:class:`~ColMap`
This is great for pipes, where you're receiving binary data through stdin.
* Set binData to `sys.stdin.buffer.read()` in a script to pipe data into it!
**NOTE: Uses Wand's "blob" functionality, and as such incurs Wand's limitations.**
'''
with wand.image.Image(blob=binData, format=fmt, width=width, height=height) as img:
return ColMap.fromArray(np.fromstring(img.make_blob("RGB"), dtype='uint{}'.format(img.depth)).reshape(img.height, img.width, 3))
#IO Functions
@staticmethod
def open(path) :
'''
Opens 8 and 16 bit images of many formats.
Construct a ColMap from an image on the disk.
:param str path: The image path to open.
:return: The image, as a ColMat.
:rtype: :py:class:`~ColMap`
ColMap currently uses ImageMagick to open a wide range of formats, including:
* **EXR**: The industry standard for HDR, wide-gamut, linear-encoded images.
* **DPX**: An older production format.
* **PNG**: Can store 16-bit images well. Usually quite slow.
* *Any other IM-supported formats...* See https://www.imagemagick.org/script/formats.php
'''
try :
@ -69,16 +160,32 @@ class ColMap :
#Fallback to opening using Wand.
return ColMap.openWand(path)
#Operations - returns new ColMaps.
def apply(self, transform) :
'''
Apply an image transformation, in the form of a subclass of :py:class:`~Transform`.
You can apply LUTs, gamma functions, matrices - simply insert an instance of :py:class:`~LUT`,
:py:class:`~Func`, :py:class:`~ColMat`, or any other :py:class:`~Transform` object to apply it
to the image!
:param transform: An image transform.
:type transform: :py:class:`~Transform`
:return: A transformed ColMap.
'''
return ColMap.fromArray(transform.sample(self.asarray()))
#Vendor-specific open methods.
#~ def openSci(path) :
#~ return ColMap.fromIntArray(si.io.imread(path)[:,:,:3])
@staticmethod
def openWand(path) :
'''
Open a file using the Wand ImageMagick binding.
Vendor-specific :py:func:`~ColMap.open` function. See :py:func:`~ColMap.open`
:param str path: The image path to open.
:return: The image, as a ColMat.
:rtype: :py:class:`~ColMap`
'''
with wand.image.Image(filename=path) as img:
#Quick inverse sRGB transform, to undo what Wand did - but not for exr's, which are linear bastards.
if img.format != 'EXR' :
@ -87,32 +194,32 @@ class ColMap :
img.colorspace = 'srgb' if img.format == 'DPX' else 'rgb' #Fix for IM's dpx bug.
return ColMap.fromIntArray(np.fromstring(img.make_blob("RGB"), dtype='uint{}'.format(img.depth)).reshape(img.height, img.width, 3))
@staticmethod
def fromBinary(binData, fmt, width=None, height=None) :
'''
Using the Wand blob functionality, creates a ColMap from binary data. Set binData to sys.stdin.buffer.read() to activate piping!
'''
with wand.image.Image(blob=binData, format=fmt, width=width, height=height) as img:
return ColMap.fromIntArray(np.fromstring(img.make_blob("RGB"), dtype='uint{}'.format(img.depth)).reshape(img.height, img.width, 3))
def toBinary(self, fmt, depth=16) :
'''
Using Wand blob functionality
'''
with self.asWandImg(depth) as img :
img.format = fmt
return img.make_blob()
return ColMap.fromArray(np.fromstring(img.make_blob("RGB"), dtype='uint{}'.format(img.depth)).reshape(img.height, img.width, 3))
def save(self, path, compress = None, depth = None) :
'''
Save the image. The filetype will be inferred from the path, and the appropriate backend will be used.
Save a ColMap to an image file on the disk.
Compression scheme will be applied based on the backend compatiblity. Wand compression types can be used: Browse then
at http://docs.wand-py.org/en/0.4.3/wand/image.html#wand.image.COMPRESSION_TYPES .
:param str path: The path to save the image file at. The extension specified determines the output format.
:param compress: Compression options passed to the vendor. Currently broken.
:type compress: str or None
:param depth: You may override the ColMap's depth if you wish.
:type depth: int or None
ColMap currently uses ImageMagick to save a wide range of formats, including:
* **EXR**: The industry standard for HDR, wide-gamut, linear-encoded images.
* **DPX**: An older production format.
* **PNG**: Can store 16-bit images well. Usually quite slow.
* *Any other IM-supported formats...* See https://www.imagemagick.org/script/formats.php
**NOTE: EXRs are only saveable as 16-bit integer, with no compression options. This is an IM/Wand library limitation.**
'''
if depth is None: depth = 16
if depth not in ColMap.DEPTHS.values :
raise ValueError('Bit depth not supported! Supported bit depths: {}'.format(', '.join(ColMap.DEPTHS.values)))
try :
saveFunction = {
"exr" : self.saveWand,
@ -126,9 +233,24 @@ class ColMap :
#Fallback to saving using Wand.
self.saveWand(path, compress, depth)
#Vendor-specific save methods
def saveWand(self, path, compress = None, depth = 16) :
def saveWand(self, path, compress = None, depth = None) :
'''
Vendor-specific :py:func:`~ColMap.save` function. See :py:func:`~ColMap.save`
:param str path: The image path to save to.
:param compress: Compression options passed to Wand. Currently broken.
:param depth: You may override the ColMap's depth if you wish.
:type depth: int or None
**NOTE: EXRs are only saveable as 16-bit integer, with no compression options. This is an IM/Wand library limitation.**
'''
if depth not in ColMap.DEPTHS.values :
raise ValueError('Bit depth not supported! Supported bit depths: {}'.format(', '.join(ColMap.DEPTHS.values)))
data = self.apply(LUT.lutFunc(gamma.sRGB)) if path[path.rfind('.')+1:] == 'dpx' else self
i = data.asWandImg(depth)
@ -142,16 +264,17 @@ class ColMap :
i.save(filename=path)
#~ def saveSci(self, path, compress = None, depth = 16) :
#~ if compress is not None: raise ValueError('Scipy Backend cannot compress the output image!')
#~ si.io.imsave(path, self.asIntArray())
#Display Functions
@staticmethod
def display(path, width = 1000) :
'''
Shows an image at a path without making a ColMap.
Display an image at a path on the disk, using the builtin OpenGL Viewer.
:param width: The desired width of the viewer; the height is automatically gleaned from the aspect ratio.
For the viewer source code, see :py:class:`~Viewer`.
'''
img = ColMap.open(path).rgbArr
@ -163,35 +286,98 @@ class ColMap :
Viewer.run(img, xRes, yRes, title = os.path.basename(path))
def show(self, width = 1000) :
'''
Display this ColMap using the builtin OpenGL Viewer.
:param width: The desired width of the viewer; the height is automatically gleaned from the aspect ratio.
For the viewer source code, see :py:class:`~Viewer`.
'''
#Use my custom OpenGL viewer!
Viewer.run(self.rgbArr, width, int(width * self.rgbArr.shape[0]/self.rgbArr.shape[1]))
@staticmethod
def wandShow(wandImg) :
#Do a quick sRGB transform for viewing. Must be in 'rgb' colorspace for this to take effect.
wandImg.transform_colorspace('srgb')
wand.display.display(wandImg)
#Data Output Types
def asWandImg(self, depth = None) :
'''
Output this ColMap as a Wand image.
wandImg.transform_colorspace('rgb') #This transforms it back to linearity.
:param depth: You may override the ColMap's depth if you wish.
:type depth: int or None
:return: The Wand Image.
:rtype: wand.image
See http://docs.wand-py.org/en/0.4.4/index.html for Wand docs.
'''
if depth not in ColMap.DEPTHS.values :
raise ValueError('Bit depth not supported! Supported bit depths: {}'.format(', '.join(ColMap.DEPTHS.values)))
if depth is None :
d = ColMap.DEPTHS['half'] if self.depth >= ColMap.DEPTHS['half'] else self.depth #Highest is half - 16.
else :
d = depth
#Data Form Functions
def asWandImg(self, depth = 16) :
#~ i = wand.image.Image(blob=self.asarray().tostring(), width=np.shape(self.rgbArr)[1], height=np.shape(self.rgbArr)[0], format='RGB') #Float Array
i = wand.image.Image(blob=self.asIntArray(depth).tostring(), width=np.shape(self.rgbArr)[1], height=np.shape(self.rgbArr)[0], format='RGB')
i = wand.image.Image(blob=self.asIntArray(d).tostring(), width=np.shape(self.rgbArr)[1], height=np.shape(self.rgbArr)[0], format='RGB')
i.colorspace = 'rgb' #Specify, to Wand, that this image is to be treated as raw, linear, data.
return i
def toBinary(self, fmt, depth=None) :
'''
Output this ColMap in binary form. See :py:func:`~ColMap.fromBinary` for the inverse.
:param str fmt: Wand needs to know what format to output! See https://www.imagemagick.org/script/formats.php .
:param depth: You may override the ColMap's bit depth if you wish.
:type depth: int or None
:return: The image, as a ColMat.
:rtype: :py:class:`~ColMap`
This is great for pipes, where you're sending binary data through stdout.
* Use the return value as the argument of sys.stdout.write() to pipe the image to other applications!
**NOTE: Uses Wand's "blob" functionality, and as such incurs Wand's limitations.**
'''
if depth not in ColMap.DEPTHS.values :
raise ValueError('Bit depth not supported! Supported bit depths: {}'.format(', '.join(ColMap.DEPTHS.values)))
with self.asWandImg(d) as img :
img.format = fmt
return img.make_blob()
def asarray(self) :
"""
Returns the base float array.
Returns the internal np.float32 image array directly.
:return: The internal numpy array.
:rtype: np.array
"""
return self.rgbArr
def asIntArray(self, depth = 16, us = True) :
u = 'u' if us else ''
def asIntArray(self, depth = None, us = True) :
"""
Returns the internal image array as an int array.
:param depth: You may override the ColMap's bit depth if you wish.
:type depth: int or None
:param bool us: True will output unsigned ints, False will output signed ints.
:return: The internal numpy array.
:rtype: np.array
"""
if depth not in ColMap.DEPTHS.values :
raise ValueError('Bit depth not supported! Supported bit depths: {}'.format(', '.join(ColMap.DEPTHS.values)))
if depth is None :
d = self.depth #No limits here.
else :
d = depth
u = 'u' if us else '' #Unsigned or no?
return np.multiply(self.rgbArr.clip(0, 1), 2.0 ** depth - 1).astype("{0}int{1}".format(u, depth))

21
openlut/LUT.py
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@ -69,29 +69,27 @@ class LUT(Transform) :
'''
return LUT.lutArray(splev(np.linspace(0, 1, num=len(idArr)), splrep(idArr, mapArr)))
#LUT Functions.
#Transform Functions.
def _splInterp(q, cpu, spSeq, ID, array) :
q.put( (cpu, splev(spSeq, splrep(ID, array))) ) #Spline Interpolation. Pretty quick, considering.
def sample(self, fSeq, spl=True) :
'''
Sample the LUT using a flat float sequence (ideally a numpy array; (0..1) ).
Apply the 1D LUT to the numpy image array, using fast C++ math.
Each n (dimensions) clump of arguments will be used to sample the LUT. So:
1D LUT: in1, in2, in3 --> out1, out2, out3
*Min 1 argument.
Latest Performance:
apply(ol.LUT): 0.026462205679908948,, (avg. 100 Trials) *sRGB LUT
3D LUT: inR, inG, inB --> outR, outG, outB
*Min 3 arguments, len(arguments) % 3 must equal 0.
Returns a numpy array with identical shape to the input array.
:return: Returns a numpy array with identical shape to the input array.
'''
fSeq = np.array(fSeq)
if self.dims == 1 :
#If scipy isn't loaded, we can't use spline interpolation!
if (not MOD_SCIPY) or self.size > 25 : # Auto-adapts all but the smallest LUTs to use the faster linear interpolation.
#Scipy must be loaded & the LUT must be rediculously small before spline interpolation sets in.
if (not MOD_SCIPY) or self.size > 25 :
return olo.lut1dlin(fSeq.reshape(reduce(lambda a, b: a*b, fSeq.shape)), self.array, self.range[0], self.range[1]).reshape(fSeq.shape)
else :
#~ return np.interp(spSeq, self.ID, self.array) #non-threaded way.
out = []
@ -109,6 +107,7 @@ class LUT(Transform) :
elif self.dims == 3 :
print("3D LUT Not Implemented!")
#LUT Functions
def resized(self, newSize) :
'''
Return the LUT, resized to newSize.

35
openlut/lib/olOpt.cpp
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@ -144,6 +144,35 @@ py::array_t<float> matr(py::array_t<float> img, py::array_t<float> mat) {
}
}
//grey_to_rgb takes a flattened greyscale image array and outputs a flattened numpy image array.
py::array_t<float> grey_to_rgb(py::array_t<float> arr) {
py::buffer_info bufIn = arr.request();
//To use with an image, MAKE SURE to flatten the 3D array to a 1D array, then back out to a 3D array after.
if (bufIn.ndim == 1) {
//Make numpy allocate the buffer.
auto result = py::array_t<float>(bufIn.size * 3); //Size is multiplied by 3 - we're outputting RGB!
//Get the pointers that we can manipulate from C++.
auto bufOut = result.request();
float *ptrIn = (float *) bufIn.ptr,
*ptrOut = (float *) bufOut.ptr;
//The reason for all this bullshit as opposed to vectorizing is this pragma!!!
#pragma omp parallel for
for (size_t i = 0; i < bufOut.shape[0]; i+=3) {
float val = ptrIn[(i+1)/3 - 1]; //Little bit of indexing math to get the value; remember we're skipping by threes.
ptrOut[i] = val;
ptrOut[i + 1] = val;
ptrOut[i + 2] = val;
}
return result;
}
}
@ -164,6 +193,12 @@ PYBIND11_PLUGIN(olOpt) {
py::arg("mat")
);
mod.def( "grey_to_rgb",
&grey_to_rgb,
"Takes a flattened 2D greyscale image array and outputs a flattened 3D numpy image array.",
py::arg("arr")
);
mod.def( "lut1dlin",
&lut1dlin,
"Apply any 1D LUT to a flattened numpy image array; vectorized & parallel.",