Update install example to avoid directory assumptions (#451)

The previous instruction examples assumed that the directory `~/github` existed, and did not include any check to create it if the directory did not exist. I updated to install in whatever directory the user is current in. 

I also updated to make it clear how the CUDA version is specified, and fixed a typo in activating the conda env.

INSTALL.md

@@ -18,7 +18,7 @@
 # right path. From a clean conda env, this is what you need to do
 
 conda create --name maskrcnn_benchmark
-source activate maskrcnn_benchmark
+conda activate maskrcnn_benchmark
 
 # this installs the right pip and dependencies for the fresh python
 conda install ipython
@@ -28,22 +28,23 @@ pip install ninja yacs cython matplotlib
 
 # follow PyTorch installation in https://pytorch.org/get-started/locally/
 # we give the instructions for CUDA 9.0
-conda install pytorch-nightly -c pytorch
+conda install pytorch-nightly cudatoolkit=9.0 -c pytorch
 
+export MASKRCNN_BENCHMARK_INSTALL_DIR=$PWD
 # install torchvision
-cd ~/github
+cd $INSTALL_DIR
 git clone https://github.com/pytorch/vision.git
 cd vision
 python setup.py install
 
 # install pycocotools
-cd ~/github
+cd $INSTALL_DIR
 git clone https://github.com/cocodataset/cocoapi.git
 cd cocoapi/PythonAPI
 python setup.py build_ext install
 
 # install PyTorch Detection
-cd ~/github
+cd $INSTALL_DIR
 git clone https://github.com/facebookresearch/maskrcnn-benchmark.git
 cd maskrcnn-benchmark
 # the following will install the lib with
@@ -52,6 +53,8 @@ cd maskrcnn-benchmark
 # re-build it
 python setup.py build develop
 
+unset MASKRCNN_BENCHMARK_INSTALL_DIR
+
 # or if you are on macOS
 # MACOSX_DEPLOYMENT_TARGET=10.9 CC=clang CXX=clang++ python setup.py build develop
 ```
@@ -69,4 +72,4 @@ Build image with other CUDA and CUDNN versions:
 Build and run image with built-in jupyter notebook(note that the password is used to log in jupyter notebook):
 
     nvidia-docker build -t maskrcnn-benchmark-jupyter docker/docker-jupyter/
-    nvidia-docker run -td -p 8888:8888 -e PASSWORD=<password> -v <host-dir>:<container-dir> maskrcnn-benchmark-jupyter
+    nvidia-docker run -td -p 8888:8888 -e PASSWORD=<password> -v <host-dir>:<container-dir> maskrcnn-benchmark-jupyter
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