diff --git a/README.rst b/README.rst index 79e08a4..76ebf8e 100644 --- a/README.rst +++ b/README.rst @@ -194,7 +194,7 @@ API Usage .. |build_travis| image:: https://img.shields.io/travis/com/hahnec/color-matcher?style=square :target: https://travis-ci.com/github/hahnec/color-matcher -.. |build_github| image:: https://img.shields.io/github/workflow/status/hahnec/color-matcher/ColorMatcher's%20CI%20Pipeline/master?style=square +.. |build_github| image:: https://img.shields.io/github/actions/workflow/status/hahnec/color-matcher/gh_actions.yml?branch=master&style=square :target: https://github.com/hahnec/color-matcher/actions :alt: GitHub Workflow Status diff --git a/docs/build/html/apidoc.html b/docs/build/html/apidoc.html index 7483b93..5f69693 100644 --- a/docs/build/html/apidoc.html +++ b/docs/build/html/apidoc.html @@ -61,7 +61,7 @@

Class hierarchy
-main() numpy.ndarray
+main() numpy.ndarray

The main function is the high-level entry point performing the mapping based on instantiation arguments.

Returns
@@ -75,14 +75,14 @@

Class hierarchy
-transfer(src: Optional[numpy.ndarray] = None, ref: Optional[numpy.ndarray] = None, method: Optional[str] = None) numpy.ndarray
+transfer(src: Optional[numpy.ndarray] = None, ref: Optional[numpy.ndarray] = None, method: Optional[str] = None) numpy.ndarray

Transfer function to map colors based on provided transfer method.

Parameters
    -
  • src (ndarray) – Source image that requires transfer

  • -
  • ref (ndarray) – Palette image which serves as reference

  • -
  • method (str) – (‘default’, ‘hm’, ‘reinhard’, ‘mvgd’, ‘mkl’, ‘hm-mvgd-hm’, ‘hm-mkl-hm’) determining color mapping

  • +
  • src (ndarray) – Source image that requires transfer

  • +
  • ref (ndarray) – Palette image which serves as reference

  • +
  • method (str) – (‘default’, ‘hm’, ‘reinhard’, ‘mvgd’, ‘mkl’, ‘hm-mvgd-hm’, ‘hm-mkl-hm’) determining color mapping

Returns
@@ -106,15 +106,15 @@

Class hierarchy
-hist_match(src: Optional[numpy.ndarray] = None, ref: Optional[numpy.ndarray] = None) numpy.ndarray
+hist_match(src: Optional[numpy.ndarray] = None, ref: Optional[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.

Parameters
    -
  • src (ndarray) – Source image that requires transfer

  • -
  • ref (ndarray) – Palette image which serves as reference

  • -
  • res (ndarray) – Resulting image after the mapping

  • +
  • src (ndarray) – Source image that requires transfer

  • +
  • ref (ndarray) – Palette image which serves as reference

  • +
  • res (ndarray) – Resulting image after the mapping

Returns
@@ -138,7 +138,7 @@

Class hierarchy
-analytical_solver() numpy.ndarray
+analytical_solver() numpy.ndarray

An analytical solution to the linear equation system of Multi-Variate Gaussian Distributions (MVGDs).

Returns
@@ -177,15 +177,15 @@

Class hierarchy
-multivar_transfer(src: Optional[numpy.ndarray] = None, ref: Optional[numpy.ndarray] = None, fun: Optional[function] = None) numpy.ndarray
+multivar_transfer(src: Optional[numpy.ndarray] = None, ref: Optional[numpy.ndarray] = None, fun: Optional[function] = None) numpy.ndarray

Transfer function to map colors based on for Multi-Variate Gaussian Distributions (MVGDs).

Parameters
    -
  • src (ndarray) – Source image that requires transfer

  • -
  • ref (ndarray) – Palette image which serves as reference

  • +
  • src (ndarray) – Source image that requires transfer

  • +
  • ref (ndarray) – Palette image which serves as reference

  • fun – Optional argument to pass a transfer function to solve for covariance matrices

  • -
  • res (ndarray) – Resulting image after the mapping

  • +
  • res (ndarray) – Resulting image after the mapping

Returns
@@ -199,42 +199,42 @@

Class hierarchy
-static w2_dist(mu_a: numpy.ndarray, mu_b: numpy.ndarray, cov_a: numpy.ndarray, cov_b: numpy.ndarray) float
+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

Parameters
    -
  • mu_a (ndarray) – Gaussian mean of distribution a

  • -
  • mu_b (ndarray) – Gaussian mean of distribution b

  • -
  • cov_a (ndarray) – Covariance matrix of distribution a

  • -
  • cov_b (ndarray) – Covariance matrix of distribution b

  • +
  • mu_a (ndarray) – Gaussian mean of distribution a

  • +
  • mu_b (ndarray) – Gaussian mean of distribution b

  • +
  • cov_a (ndarray) – Covariance matrix of distribution a

  • +
  • cov_b (ndarray) – Covariance matrix of distribution b

Returns

scalar: Wasserstein-2 metric as a scalar

Return type
-

float

+

float

-w2_img_dist(img_a: numpy.ndarray, img_b: numpy.ndarray)
+w2_img_dist(img_a: numpy.ndarray, img_b: numpy.ndarray)

Wasserstein-2 image distance metric is a similarity measure for Gaussian distributions

Parameters
    -
  • img_a (ndarray) – Image array a

  • -
  • img_b (ndarray) – Image array b

  • +
  • img_a (ndarray) – Image array a

  • +
  • img_b (ndarray) – Image array b

Returns

scalar: Wasserstein-2 image metric as a scalar

Return type
-

float

+

float

@@ -251,15 +251,15 @@

Class hierarchy
-reinhard(src: Optional[numpy.ndarray] = None, ref: Optional[numpy.ndarray] = None) numpy.ndarray
+reinhard(src: Optional[numpy.ndarray] = None, ref: Optional[numpy.ndarray] = None) numpy.ndarray

This function conducts color matching based on the principles proposed by Reinhard et al. The paper of the original work can be found at https://www.cs.tau.ac.il/~turkel/imagepapers/ColorTransfer.pdf

Parameters
    -
  • src (ndarray) – Source image that requires transfer

  • -
  • ref (ndarray) – Palette image which serves as reference

  • -
  • res (ndarray) – Resulting image after the mapping

  • +
  • src (ndarray) – Source image that requires transfer

  • +
  • ref (ndarray) – Palette image which serves as reference

  • +
  • res (ndarray) – Resulting image after the mapping

Returns
@@ -283,12 +283,12 @@

Class hierarchy
-static rgb2gray(rgb: Optional[numpy.ndarray] = None, standard: str = 'HDTV') numpy.ndarray
+static rgb2gray(rgb: Optional[numpy.ndarray] = None, standard: str = 'HDTV') numpy.ndarray

Convert RGB color space to monochromatic color space

Parameters
    -
  • rgb (ndarray) – input array in red, green and blue (RGB) space

  • +
  • rgb (ndarray) – input array in red, green and blue (RGB) space

  • standard (string) – option that determines whether head- and footroom are excluded (‘HDTV’) or considered otherwise

diff --git a/docs/build/html/color_matcher.html b/docs/build/html/color_matcher.html index 2ffc86a..5bf261d 100644 --- a/docs/build/html/color_matcher.html +++ b/docs/build/html/color_matcher.html @@ -45,7 +45,7 @@

Submodules
class color_matcher.baseclass.MatcherBaseclass(*args, **kwargs)
-

Bases: object

+

Bases: object

__init__(*args, **kwargs)
@@ -53,12 +53,12 @@

Submodules
-static rgb2gray(rgb: Optional[numpy.ndarray] = None, standard: str = 'HDTV') numpy.ndarray
+static rgb2gray(rgb: Optional[numpy.ndarray] = None, standard: str = 'HDTV') numpy.ndarray

Convert RGB color space to monochromatic color space

Parameters
    -
  • rgb (ndarray) – input array in red, green and blue (RGB) space

  • +
  • rgb (ndarray) – input array in red, green and blue (RGB) space

  • standard (string) – option that determines whether head- and footroom are excluded (‘HDTV’) or considered otherwise

@@ -99,15 +99,15 @@

Submodules
-hist_match(src: Optional[numpy.ndarray] = None, ref: Optional[numpy.ndarray] = None) numpy.ndarray
+hist_match(src: Optional[numpy.ndarray] = None, ref: Optional[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.

Parameters
    -
  • src (ndarray) – Source image that requires transfer

  • -
  • ref (ndarray) – Palette image which serves as reference

  • -
  • res (ndarray) – Resulting image after the mapping

  • +
  • src (ndarray) – Source image that requires transfer

  • +
  • ref (ndarray) – Palette image which serves as reference

  • +
  • res (ndarray) – Resulting image after the mapping

Returns
@@ -126,12 +126,12 @@

Submodules

color_matcher.io_handler module

-color_matcher.io_handler.load_img_file(file_path: Optional[str] = None) numpy.ndarray
+color_matcher.io_handler.load_img_file(file_path: Optional[str] = None) numpy.ndarray
-color_matcher.io_handler.save_img_file(img, file_path: Optional[str] = None, file_type: Optional[str] = None) bool
+color_matcher.io_handler.save_img_file(img, file_path: Optional[str] = None, file_type: Optional[str] = None) bool
@@ -159,7 +159,7 @@

Submodules
-analytical_solver() numpy.ndarray
+analytical_solver() numpy.ndarray

An analytical solution to the linear equation system of Multi-Variate Gaussian Distributions (MVGDs).

Returns
@@ -198,15 +198,15 @@

Submodules
-multivar_transfer(src: Optional[numpy.ndarray] = None, ref: Optional[numpy.ndarray] = None, fun: Optional[function] = None) numpy.ndarray
+multivar_transfer(src: Optional[numpy.ndarray] = None, ref: Optional[numpy.ndarray] = None, fun: Optional[function] = None) numpy.ndarray

Transfer function to map colors based on for Multi-Variate Gaussian Distributions (MVGDs).

Parameters
    -
  • src (ndarray) – Source image that requires transfer

  • -
  • ref (ndarray) – Palette image which serves as reference

  • +
  • src (ndarray) – Source image that requires transfer

  • +
  • ref (ndarray) – Palette image which serves as reference

  • fun – Optional argument to pass a transfer function to solve for covariance matrices

  • -
  • res (ndarray) – Resulting image after the mapping

  • +
  • res (ndarray) – Resulting image after the mapping

Returns
@@ -220,42 +220,42 @@

Submodules
-static w2_dist(mu_a: numpy.ndarray, mu_b: numpy.ndarray, cov_a: numpy.ndarray, cov_b: numpy.ndarray) float
+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

Parameters
    -
  • mu_a (ndarray) – Gaussian mean of distribution a

  • -
  • mu_b (ndarray) – Gaussian mean of distribution b

  • -
  • cov_a (ndarray) – Covariance matrix of distribution a

  • -
  • cov_b (ndarray) – Covariance matrix of distribution b

  • +
  • mu_a (ndarray) – Gaussian mean of distribution a

  • +
  • mu_b (ndarray) – Gaussian mean of distribution b

  • +
  • cov_a (ndarray) – Covariance matrix of distribution a

  • +
  • cov_b (ndarray) – Covariance matrix of distribution b

Returns

scalar: Wasserstein-2 metric as a scalar

Return type
-

float

+

float

-w2_img_dist(img_a: numpy.ndarray, img_b: numpy.ndarray)
+w2_img_dist(img_a: numpy.ndarray, img_b: numpy.ndarray)

Wasserstein-2 image distance metric is a similarity measure for Gaussian distributions

Parameters
    -
  • img_a (ndarray) – Image array a

  • -
  • img_b (ndarray) – Image array b

  • +
  • img_a (ndarray) – Image array a

  • +
  • img_b (ndarray) – Image array b

Returns

scalar: Wasserstein-2 image metric as a scalar

Return type
-

float

+

float

@@ -268,7 +268,7 @@

Submodules
class color_matcher.normalizer.Normalizer(data=None, min=None, max=None)
-

Bases: object

+

Bases: object

__init__(data=None, min=None, max=None)
@@ -314,7 +314,7 @@

Submodules
-main() numpy.ndarray
+main() numpy.ndarray

The main function is the high-level entry point performing the mapping based on instantiation arguments.

Returns
@@ -328,14 +328,14 @@

Submodules
-transfer(src: Optional[numpy.ndarray] = None, ref: Optional[numpy.ndarray] = None, method: Optional[str] = None) numpy.ndarray
+transfer(src: Optional[numpy.ndarray] = None, ref: Optional[numpy.ndarray] = None, method: Optional[str] = None) numpy.ndarray

Transfer function to map colors based on provided transfer method.

Parameters
    -
  • src (ndarray) – Source image that requires transfer

  • -
  • ref (ndarray) – Palette image which serves as reference

  • -
  • method (str) – (‘default’, ‘hm’, ‘reinhard’, ‘mvgd’, ‘mkl’, ‘hm-mvgd-hm’, ‘hm-mkl-hm’) determining color mapping

  • +
  • src (ndarray) – Source image that requires transfer

  • +
  • ref (ndarray) – Palette image which serves as reference

  • +
  • method (str) – (‘default’, ‘hm’, ‘reinhard’, ‘mvgd’, ‘mkl’, ‘hm-mvgd-hm’, ‘hm-mkl-hm’) determining color mapping

Returns
diff --git a/docs/build/html/objects.inv b/docs/build/html/objects.inv index bd45406..28f75d7 100644 Binary files a/docs/build/html/objects.inv and b/docs/build/html/objects.inv differ diff --git a/docs/build/html/py-modindex.html b/docs/build/html/py-modindex.html index 8c79334..379a971 100644 --- a/docs/build/html/py-modindex.html +++ b/docs/build/html/py-modindex.html @@ -52,7 +52,7 @@

Python Module Index

- color_matcher + color_matcher diff --git a/docs/build/html/readme.html b/docs/build/html/readme.html index 027e88a..2ab8d81 100644 --- a/docs/build/html/readme.html +++ b/docs/build/html/readme.html @@ -53,7 +53,7 @@

Descriptionrelease License GitHub Workflow Status coverage PyPi Dl2 PyPI Downloads

+

release License GitHub Workflow Status coverage PyPi Dl2 PyPI Downloads

binder

@@ -61,10 +61,10 @@

Results - - - - + + + + @@ -75,24 +75,24 @@

Results

Photograph

-

-

-

+

+

+

Film sequence

-

-

-

+

+

+

Light-field correction

-

-

-

+

+

+

Paintings

-

-

-

+

+

+

diff --git a/docs/build/html/searchindex.js b/docs/build/html/searchindex.js index 9aac1ff..71910ad 100644 --- a/docs/build/html/searchindex.js +++ b/docs/build/html/searchindex.js @@ -1 +1 @@ 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