Merge pull request #137 from jakeret/binder

Binder

README.rst

@@ -12,6 +12,9 @@ Tensorflow Unet
 .. image:: https://img.shields.io/badge/ascl-1611.002-blue.svg?colorB=262255
         :target: http://ascl.net/1611.002
 
+.. image:: https://mybinder.org/badge.svg
+        :target: https://mybinder.org/v2/gh/jakeret/tf_unet/binder?filepath=demo%2Fdemo_toy_problem.ipynb
+
 
 This is a generic **U-Net** implementation as proposed by `Ronneberger et al. <https://arxiv.org/pdf/1505.04597.pdf>`_ developed with **Tensorflow**. The code has been developed and used for `Radio Frequency Interference mitigation using deep convolutional neural networks <http://arxiv.org/abs/1609.09077>`_ .
 

demo/README.rst

@@ -0,0 +1,13 @@
+=============================
+Tensorflow Unet demos
+=============================
+
+.. image:: https://mybinder.org/badge.svg
+        :target: https://mybinder.org/v2/gh/jakeret/tf_unet/binder?filepath=demo%2Fdemo_toy_problem.ipynb
+
+
+
+Here you can find demo Jupyter notebooks for a `toy problem <https://github.com/jakeret/tf_unet/blob/master/demo/demo_toy_problem.ipynb>`_ or the `Radio Frequency Interference mitigation <https://github.com/jakeret/tf_unet/blob/master/demo/demo_radio_data.ipynb>`_ discussed in our paper.
+
+
+You can use the binder badge to start an interactive version of the toy problem without having to install anything on your machine.

postBuild

@@ -0,0 +1,4 @@
+#!/bin/bash
+
+# NOTE: this file needs to be executable in order to work.
+python setup.py install

requirements.txt

@@ -1,4 +1,5 @@
 click
 numpy
 Pillow
-tensorflow>=1.0.0
+tensorflow>=1.0.0
+matplotlib