Installing keras

keras is great. It makes building convolution networks so much easier. Obviously I am using keras with tensorflow backend, but it can be theano. I tried three methods:

1. Install keras using conda

 $ conda install keras  
 Fetching package metadata ...........  
 PackageNotFoundError: Package not found: Conda could not find '  

--> Obviously it failed

2. Install keras using pip3

 $ pip3 install keras  
 ...  
 Successfully installed keras-2.0.0 pyyaml-3.12  

--> Can't import keras on python 3.6

3. Install keras using pip

 $ pip install keras  
 ...  
 Successfully installed keras-2.0.0 pyyaml-3.12  

--> Now I can import keras on python 3.6

• Anaconda is great but I still don't understand what you can and cannot conda
• I am using python 3.6 and I still don't understand whether I should use pip or pip3 for individual modules

Compile OpenCV 3.2 for Anaconda Python 3.6

I need Open CV to do some image processing and visualization. Open CV seems to be an equivalent of Matlab "Image Processing Toolbox". However, it turns out that it's a huge headache to install Open CV 3 in Anaconda Python 3.6 environment due to the dependency issues. After extensive web search I found this site. I tested it in my MacBookAir and it seems to be working well.

1. Setup
Linux

 $ sudo apt install gcc g++ git libjpeg-dev libpng-dev libtiff5-dev libjasper-dev libavcodec-dev libavformat-dev libswscale-dev pkg-config cmake libgtk2.0-dev libeigen3-dev libtheora-dev libvorbis-dev libxvidcore-dev libx264-dev sphinx-common libtbb-dev yasm libfaac-dev libopencore-amrnb-dev libopencore-amrwb-dev libopenexr-dev libgstreamer-plugins-base1.0-dev libavcodec-dev libavutil-dev libavfilter-dev libavformat-dev libavresample-dev 

OSX

 $ brew install git cmake pkg-config jpeg libpng libtiff openexr eigen tbb

2. Download OpenCV (http://opencv.org/)

$ cd ~/Downloads
$ unzip opencv-3.2.0.zip
$ cd opencv-3.2.0

3. Cmake configuration: OpenCV for Python 3

$ mkdir release
$ cd release
$ sudo cmake -DBUILD_TIFF=ON -DBUILD_opencv_java=OFF -DWITH_CUDA=OFF -DENABLE_AVX=ON -DWITH_OPENGL=ON -DWITH_OPENCL=ON -DWITH_IPP=OFF -DWITH_TBB=ON -DWITH_EIGEN=ON -DWITH_V4L=ON -DWITH_VTK=OFF -DBUILD_TESTS=OFF -DBUILD_PERF_TESTS=OFF -DCMAKE_BUILD_TYPE=RELEASE -DBUILD_opencv_python2=OFF -DCMAKE_INSTALL_PREFIX=$(python3 -c "import sys; print(sys.prefix)") -DPYTHON3_EXECUTABLE=$(which python3) -DPYTHON3_INCLUDE_DIR=$(python3 -c "from distutils.sysconfig import get_python_inc; print(get_python_inc())") -DPYTHON3_PACKAGES_PATH=$(python3 -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())") .. 

4. Compile and install OpenCV source

$ sudo make -j4
$ sudo make install

5. Fix a couple of things (for Linux only)

$ mv libstdc++.so.6 libstdc++.so.6.bak
$ mv libgomp.so.1 libgomp.so.1.bak

6. Test installation

$ python3
>>> import cv2
>>>

Re-installing tensorflow

Finally I understood why my friend recommended Anaconda. It's so much easier to install Anaconda, which includes all the goodies that come with it, rather than installing each component on an as-needed basis (e.g. Spyder, iPython, etc.) The only reason I didn't go with Anaconda installation of tensorflow previously was that the tensorflow official documentation did not strongly recommend it. I used Anaconda to install tensorflow in my MacBookAir, and had no issues so far. So why not use it for the GPU box as well?

1. Install Anaconda (Python 3.6 at the time of this writing)

2. Create a conda environment named tensorflow to run Python 3.6:

$ conda create -n tensorflow

3. Activate the conda environment:

$ source activate tensorflow
  (tensorflow) username$ # Your prompt should change

4. Install tensorflow within the conda environment:

(tensorflow) username$ pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.0.1-cp36-cp36m-linux_x86_64.whl   

# This is for Python 3.6 with GPU support

I tried pip3 at the beginning and got an error. pip works without an issue. I still don't quite understand pip3 (python3) vs. pip (python2).

5.  Verify that tensorflow is installed within Anaconda

(tensorflow) username$ ls /home/username/anaconda3/envs/tensorflow/bin/

activate  conda  deactivate

6. Install ipython and jupyter

(tensorflow) username$ conda install ipython

(tensorflow) username$ pip3 install jupyter  

7. Verify that ipython and  is installed within Anaconda

(tensorflow) username$ ls /home/username/anaconda3/envs/tensorflow/bin/

2to3          easy_install-3.6  pydoc       python3.6-config   tclsh8.5
2to3-3.6      idle3             pydoc3      python3.6m         unxz
activate      idle3.6           pydoc3.6    python3.6m-config  wheel
conda         ipython           pygmentize  python3-config     wish8.5
c_rehash      ipython3          python      pyvenv             xz
deactivate    openssl           python3     pyvenv-3.6
easy_install  pip               python3.6   sqlite3 


Now I can use tensorflow in ipython within Anaconda!