Merge pull request #110 from juglab/tf2

Upgrade to TensorFlow 2

Author: tibuch

.travis.yml

@@ -12,18 +12,10 @@ env:
 
 matrix:
   include:
-    - os: linux
-      dist: bionic
-      python: 3.6
-      env: TENSORFLOW='tensorflow==1.14.0' KERAS='keras==2.2.5'
-    - os: linux
-      dist: bionic
-      python: 3.6
-      env: TENSORFLOW='tensorflow==1.12.0' KERAS='keras==2.2.5'
     - os: linux
       dist: bionic
       python: 3.7
-      env: TENSORFLOW='tensorflow==1.14.0' KERAS='keras==2.2.5'
+      env: TENSORFLOW='tensorflow==2.4.1' KERAS='keras==2.3.1'
 
 install:
   - pip install $TENSORFLOW $KERAS

README.md

@@ -13,7 +13,9 @@ Our implementation is based on [CSBDEEP](http://csbdeep.bioimagecomputing.com) (
 
 ## Installation
 This implementation requires [Tensorflow](https://www.tensorflow.org/install/).
-We have tested Noise2Void on LinuxMint 19 and Ubuntu 18.0 using python 3.6 and 3.7 and tensorflow-gpu 1.12.0 and 1.14.0.
+We have tested Noise2Void using Python 3.7 and tensorflow-gpu 2.4.1.
+
+Note: If you want to use TensorFlow 1.15 you have to install N2V v0.2.1. N2V v0.3.0 supports TensorFlow 2 only.
 
 #### If you start from scratch...
 We recommend using [miniconda](https://docs.conda.io/en/latest/miniconda.html).
@@ -22,13 +24,12 @@ If you do not yet have a strong opinion, just use it too!
 After installing Miniconda, the following lines might are likely the easiest way to get Tensorflow and CuDNN installed on your machine (_Note:_ Macs are not supported, and if you sit on a Windows machine all this might also require some modifications.):
 
 ```
-$ conda create -n 'n2v' python=3.6
+$ conda create -n 'n2v' python=3.7
 $ source activate n2v
-$ conda install tensorflow-gpu=1.14 keras=2.2.4
+$ conda install tensorflow-gpu=2.4.1 keras=2.3.1
 $ pip install jupyter
 ```
 
-Note: it is very important that the version of keras be 2.2.4 or 2.2.5, hence the explicit installation above.
 Once this is done (or you had tensorflow et al. installed already), you can install N2V with one of the following two options:
 
 #### Option 1: PIP (current stable release)