Merge branch 'release/v0.1.4'

README.md

@@ -27,6 +27,7 @@ This project contains modules.
     - divide_in_blocks(image, block_size): *Divide image into equal size blocks*
     - rgb_to_mscn(image): *Convert RGB Image into Mean Subtracted Contrast Normalized (MSCN) using only gray level*
     - rgb_to_grey_low_bits(image, bind=15): *Convert RGB Image into grey image using only 4 low bits values by default*
+    - rgb_to_LAB_L_low_bits(image, bind=15): *Convert RGB Image into LAB L channel image using only 4 low bits values by default*
     - normalize_arr(arr): *Normalize array values*
     - normalize_arr_with_range(arr, min, max): *Normalize array values with specific min and max values*
     - normalize_2D_arr(arr): *Return 2D array normalize from its min and max values*
@@ -51,4 +52,4 @@ All these modules will be enhanced during development of the project
 How to contribute
 -----------------
 
-This git project uses [git-flow](https://danielkummer.github.io/git-flow-cheatsheet/) implementation. You are free to contribute to it.
+This git project uses [git-flow](https://danielkummer.github.io/git-flow-cheatsheet/) implementation. You are free to contribute to it.

README.rst

@@ -28,6 +28,7 @@ This project contains modules.
     - divide_in_blocks(image, block_size): Divide image into equal size blocks
     - rgb_to_mscn(image): *Convert RGB Image into Mean Subtracted Contrast Normalized (MSCN) using only gray level*
     - rgb_to_grey_low_bits(image, bind=15): *Convert RGB Image into grey image using only 4 low bits values by default*
+    - rgb_to_LAB_L_low_bits(image, bind=15): *Convert RGB Image into LAB L channel image using only 4 low bits values by default*
     - normalize_arr(arr): *Normalize array values*
     - normalize_arr_with_range(arr, min, max): *Normalize array values with specific min and max values*
     - normalize_2D_arr(arr): *Return 2D array normalize from its min and max values*
@@ -54,4 +55,4 @@ How to contribute
 
 This git project uses git-flow_ implementation. You are free to contribute to it.
 
-.. _git-flow : https://danielkummer.github.io/git-flow-cheatsheet/
+.. _git-flow : https://danielkummer.github.io/git-flow-cheatsheet/

ipfml/image_processing.py

@@ -287,7 +287,7 @@ def rgb_to_LAB_L_low_bits(image, bind=15):
     >>> from PIL import Image
     >>> from ipfml import image_processing
     >>> img = Image.open('./images/test_img.png')
-    >>> low_bits_Lab_l_img = image_processing.rgb_to_Lab_L_low_bits(img)
+    >>> low_bits_Lab_l_img = image_processing.rgb_to_LAB_L_low_bits(img)
     >>> low_bits_Lab_l_img.shape
     (200, 200)
     """

ipfml/metrics.py

@@ -82,7 +82,7 @@ def get_SVD_U(image):
     >>> img = Image.open('./images/test_img.png')
     >>> U = metrics.get_SVD_U(img)
     >>> U.shape
-    (200, 200)
+    (200, 200, 3)
     """
 
     U, s, V = svd(image, full_matrices=False)

setup.py

@@ -21,7 +21,7 @@ class BuildTestCommand(setuptools.command.build_py.build_py):
     setuptools.command.build_py.build_py.run(self)
 
 setup(name='IPFML',
-      version='0.1.3',
+      version='0.1.4',
       description='Image Processing For Machine Learning',
       long_description=readme(),
       classifiers=[