Added missing dependecies and updated install instructions

README.md

@@ -25,42 +25,80 @@ If you find PoseCNN useful in your research, please consider citing:
 
 ### Installation
 
-1. Install [TensorFlow](https://www.tensorflow.org/get_started/os_setup). I usually compile the source code of tensorflow locally.
+1. Install [TensorFlow](https://www.tensorflow.org/get_started/os_setup) version r1.8 from source binaries won't work because of ABI incompatibilities.
+      1. Make a virtualenv with and add these packages, otherwise tf can not be build by source: pip install mock keras Cython easydict transforms3d(the last two are needed for later to actually run the demo)
 
-2. Compile the new layers under $ROOT/lib we introduce in PoseCNN.
-    ```Shell
-    cd $ROOT/lib
-    sh make.sh
-    ```
-3. Download the VGG16 weights from [here](https://drive.google.com/open?id=1UdmOKrr9t4IetMubX-y-Pcn7AVaWJ2bL) (528M). Put the weight file vgg16.npy to $ROOT/data/imagenet_models.
+2. Download the VGG16 weights from [here](https://drive.google.com/open?id=1UdmOKrr9t4IetMubX-y-Pcn7AVaWJ2bL) (528M). Put the weight file vgg16.npy to $ROOT/data/imagenet_models.
 
-4. Compile lib/synthesize with cmake (optional). This package contains a few useful tools such as generating synthetic images for training and ICP.
+3. Get dependencies: sudo apt-get install libsuitesparse-dev openexr libopenexr-dev metis libmetis-dev
 
-   Install dependencies:
-   - [Pangolin](https://github.com/stevenlovegrove/Pangolin)
-   - [Eigen](https://eigen.tuxfamily.org)
-   - [boost](https://www.boost.org/)
-   - [Sophus](https://github.com/strasdat/Sophus)
-   - [nanoflann](https://github.com/jlblancoc/nanoflann)
-   - libsuitesparse-dev
+4. Compile lib/kinect_fusion to be able to compile lib/synthesize. 
+    1. Add nanoflann to the include dirs in cmake and sohpus to the include and link dirs
+    2. Downgrade cmake to version 3.6.0
+    3. Install Eigen 3.3.90
+    4. If Pangolin is already installed, reinstall Pangolin, since it will be pointing at the old eigen which has the cuda bug mentioned here: https://devtalk.nvidia.com/default/topic/1026622/cuda-programming-and-performance/nvcc-can-t-compile-code-that-uses-eigen/
+    5. Upgrade boost to 1.67.0 and move lib to /usr/lib/x86_64-linux-gnu and include boost the whole folder to /usr/include
+    
 
-   We use Boost.Python library to link tensorflow with the c++ code. Make sure you have it in your Boost. The tested Boost version is 1.66.0.
+5. Compile lib/synthesize with cmake (optional). This package contains a few useful tools such as generating synthetic images for training and ICP.
 
-   Change hard coded pathes in CMakeLists.txt.
+   Install dependencies:
+   - Python version 2.7, 3.X won't work
+   - [Pangolin](https://github.com/stevenlovegrove/Pangolin) commit 1ec721d59ff6b799b9c24b8817f3b7ad2c929b83 worked for me, original author used c2a6ef524401945b493f14f8b5b8aa76cc7d71a9
+   - [Eigen](https://eigen.tuxfamily.org) 3.3.90
+   - [boost](https://www.boost.org/) 1.67.0
+   - [Sophus](https://github.com/strasdat/Sophus) commit ceb6380a1584b300e687feeeea8799353d48859f
+   - [nanoflann](https://github.com/jlblancoc/nanoflann) commit ad7547f4e6beb1cdb3e360912fd2e352ef959465
+   - [nlopt](https://github.com/stevengj/nlopt) Important install from this github repo, not using the instructions [here](https://nlopt.readthedocs.io/en/latest/) commit 74e647b667f7c4500cdb4f37653e59c29deb9ee2
+
 
-   The Pangolin branch I use: c2a6ef524401945b493f14f8b5b8aa76cc7d71a9
+   We use Boost.Python library to link tensorflow with the c++ code. Make sure you have it in your Boost. The tested Boost version is 1.66.0.
 
+   1. Change hard coded pathes in lib/synthesize/CMakeLists.txt of boost and add sophus paths manually or via find_script. Uncomment line #add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0) to fix potential compatibility issues with tf.
+   2. Uncomment ${CUDA_TOOLKIT_ROOT_DIR}/samples/common/inc from include dirs because of this issue: https://github.com/stevenlovegrove/Pangolin/issues/268
+   3. Surpress these warnings so you see errors better.
+   ```add_definitions(-Wno-sign-compare)
+      add_definitions(-Wno-unused-result)
+      add_definitions(-Wno-unused-but-set-variable)
+      add_definitions(-Wno-unused-variable)
+      add_definitions(-Wno-reorder)
+      add_definitions(-Wno-deprecated-declarations)
+   ```
+   4. Adapt boost_python and boost_numpy in Cmake line 98/99 to your library name when using boost and python 3.5 it is boost_python27 and boost_numpy27 or symlink these to boots_python and boost_numpy.
+   5. Create folder data and models under data/LOV and add or symlink the data and models into there
+
+### Building
+   1. Build kinect_fusion
+
+    ```Shell
+    cd $ROOT/lib/kinect_fusion
+    mkdir build
+    cd build
+    cmake ..
+    make
+    ```
+   2. Build synthesize
+
     ```Shell
     cd $ROOT/lib/synthesize
     mkdir build
     cd build
     cmake ..
     make
     ```
+   3. Compile the new layers under $ROOT/lib we introduce in PoseCNN.
+    ```Shell
+    cd $ROOT/lib
+    sh make.sh
+    ```
+
+   4. run python setup ```python setup.py build_ext --inplace```
+
+   5. Add pythonpaths
 
     Add the path of the built libary libsynthesizer.so to python path
     ```Shell
-    export PYTHONPATH=$PYTHONPATH:$ROOT/lib/synthesize/build
+    export PYTHONPATH=$PYTHONPATH:$ROOT/lib:$ROOT/lib/synthesize/build
     ```
 
 ### Required environment