Update of documentation

MANIFEST.in

@@ -1 +1 @@
-include README.rst
+include README.md

README.rst

@@ -1,27 +1,43 @@
-# IPFML
+IPFML
+=====
 
 Image Processing For Machine Learning package.
 
-## Modules
+How to use ?
+------------
+
+To use, simply do::
+
+    >>> from PIL import Image
+    >>> import IPFML as iml
+    >>> img = Image.open('path/to/image.png')
+    >>> s = iml.metrics.get_SVD_s(img)
+
+
+Modules
+-------
 
 This project contains modules.
 
-### **img_processing** : *PIL image processing part*
+- **img_processing** : *PIL image processing part*
     - fig2data(fig): *Convert a Matplotlib figure to a 3D numpy array with RGB channels and return it*
     - fig2img(fig): *Convert a Matplotlib figure to a PIL Image in RGB format and return it*
 
-### **metrics** : *Metrics computation of PIL image*
+- **metrics** : *Metrics computation of PIL image*
     - get_SVD(image): *Transforms PIL Image into SVD*
     - get_SVD_s(image): *Transforms PIL Image into SVD and returns only 's' part*
     - get_SVD_U(image): *Transforms PIL Image into SVD and returns only 'U' part*
     - get_SVD_V(image): *Transforms PIL Image into SVD and returns only 'V' part*
 
-### **ts_model_helper** : *contains helpful function to save or display model information and performance of tensorflow model*
+- **ts_model_helper** : *contains helpful function to save or display model information and performance of tensorflow model*
     - save(history, filename): *Function which saves data from neural network model*
     - show(history, filename): *Function which shows data from neural network model*
 
 All these modules will be enhanced during development of the project
 
-## How to contribute
+How to contribute
+-----------------
+
+This git project uses git-flow_ 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.
+.. _git-flow : https://danielkummer.github.io/git-flow-cheatsheet/

setup.py

@@ -1,18 +1,18 @@
 from setuptools import setup
 
 def readme():
-    with open('README.rst') as f:
+    with open('README.md') as f:
         return f.read()
 
 setup(name='IPFML',
-      version='0.0.1',
+      version='0.0.2',
       description='Image Processing For Machine Learning',
       long_description=readme(),
       classifiers=[
         'Development Status :: 3 - Alpha',
         'License :: OSI Approved :: MIT License',
         'Programming Language :: Python :: 3.6',
-        'Topic :: Image Processing :: Machine Learning',
+        'Topic :: Scientific/Engineering :: Artificial Intelligence'
       ],
       url='https://gogs.univ-littoral.fr/jerome.buisine/IPFML',
       author='Jérôme BUISINE',