color_matcher package¶
Submodules¶
color_matcher.baseclass module¶
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class
color_matcher.baseclass.
MatcherBaseclass
(*args, **kwargs)¶ Bases:
object
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__init__
(*args, **kwargs)¶ Initialize self. See help(type(self)) for accurate signature.
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validate_color_chs
()¶ This function checks whether provided images consist of 3 color channels. An exception is thrown otherwise.
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validate_img_dims
()¶ This function validates the image dimensions. It throws an exception if the dimension are unequal to 2 or 3.
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color_matcher.hist_matcher module¶
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class
color_matcher.hist_matcher.
HistogramMatcher
(*args, **kwargs)¶ Bases:
color_matcher.baseclass.MatcherBaseclass
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__init__
(*args, **kwargs)¶ Initialize self. See help(type(self)) for accurate signature.
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hist_match
(src: numpy.ndarray = None, ref: numpy.ndarray = None) → numpy.ndarray¶ This function conducts channel-wise histogram matching which is invariant of image resolutions, but requires the same number of color channels in both images.
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color_matcher.io_handler module¶
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color_matcher.io_handler.
load_img_file
(file_path: str = None) → numpy.ndarray¶
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color_matcher.io_handler.
save_img_file
(img, file_path: str = None, file_type: str = None) → bool¶
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color_matcher.io_handler.
select_file
(init_dir=None, title='')¶ get filepath from tkinter dialog
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color_matcher.io_handler.
suppress_user_warning
(switch=None, category=None)¶
color_matcher.mvgd_matcher module¶
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class
color_matcher.mvgd_matcher.
TransferMVGD
(*args, **kwargs)¶ Bases:
color_matcher.baseclass.MatcherBaseclass
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__init__
(*args, **kwargs)¶ Initialize self. See help(type(self)) for accurate signature.
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analytical_solver
() → numpy.ndarray¶ An analytical solution to the linear equation system of Multi-Variate Gaussian Distributions (MVGDs).
- Returns
transfer_mat: Transfer matrix
- Return type
np.ndarray
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mkl_solver
()¶ This function computes the transfer matrix based on the Monge-Kantorovich Linearization (MKL).
- Returns
transfer_mat: Transfer matrix
- Return type
np.ndarray
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transfer
(src: numpy.ndarray = None, ref: numpy.ndarray = None, fun: function = None) → numpy.ndarray¶ Transfer function to map colors based on for Multi-Variate Gaussian Distributions (MVGDs).
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static
w2_dist
(mu_a: numpy.ndarray, mu_b: numpy.ndarray, cov_a: numpy.ndarray, cov_b: numpy.ndarray) → float¶ Wasserstein-2 distance metric is a similarity measure for Gaussian distributions
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color_matcher.normalizer module¶
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class
color_matcher.normalizer.
Normalizer
(data=None, min=None, max=None)¶ Bases:
object
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__init__
(data=None, min=None, max=None)¶ Initialize self. See help(type(self)) for accurate signature.
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norm_fun
()¶ normalize image to values between 1 and 0
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type_norm
(data=None, min=None, max=None, new_min=None, new_max=None)¶ normalize numpy image array for provided data type
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uint16_norm
()¶ normalize image array to 16-bit unsigned integer
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uint8_norm
()¶ normalize image array to 8-bit unsigned integer
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color_matcher.top_level module¶
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class
color_matcher.top_level.
ColorMatcher
(*args, **kwargs)¶ Bases:
color_matcher.hist_matcher.HistogramMatcher
,color_matcher.mvgd_matcher.TransferMVGD
,color_matcher.reinhard_matcher.ReinhardMatcher
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__init__
(*args, **kwargs)¶ Initialize self. See help(type(self)) for accurate signature.
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main
(method: str = None) → numpy.ndarray¶ The main function is the high-level entry point performing the mapping. Valid methods are:
- Parameters
method (
str
) – (‘default’, ‘mvgd’, ‘hm’, ‘hm-mkl-hm’, ‘reinhard’) describing how to conduct color mapping- Returns
Resulting image after color mapping
- Return type
np.ndarray
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