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docs/source/index.rst

@@ -5,58 +5,12 @@ ChainerCV
 
 ChainerCV is a **deep learning based computer vision library** built on top of `Chainer <https://github.com/chainer/chainer/>`_. 
 
-
-Install Guide
-=============
-
-Pip
-~~~
-
-You can install ChainerCV using `pip`.
-
-.. code-block:: shell
-
-    pip install -U numpy
-    pip install chainercv
-
-
-Anaconda
-~~~~~~~~
-
-Build instruction using Anaconda is as follows.
-
-.. code-block:: shell
-
-    # For python 3
-    # wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh;
-    wget https://repo.continuum.io/miniconda/Miniconda2-latest-Linux-x86_64.sh -O miniconda.sh
-
-    bash miniconda.sh -b -p $HOME/miniconda
-    export PATH="$HOME/miniconda/bin:$PATH"
-    conda config --set always_yes yes --set changeps1 no
-    conda update -q conda
-
-    # Download ChainerCV and go to the root directory of ChainerCV
-    git clone https://github.com/chainer/chainercv
-    cd chainercv
-    conda env create -f environment.yml
-    source activate chainercv
-
-    # Install ChainerCV
-    pip install -e .
-
-    # Try our demos at examples/* !
-
-
-Reference Manual
-================
-
 .. toctree::
-   :maxdepth: 3
+   :maxdepth: 1
 
-   reference/index
+   install
    tutorial/index
-
+   reference/index
 
 
 Indices and tables

docs/source/install.rst

@@ -0,0 +1,41 @@
+Installation Guide
+==================
+
+Pip
+~~~
+
+You can install ChainerCV using `pip`.
+
+.. code-block:: shell
+
+    pip install -U numpy
+    pip install chainercv
+
+
+Anaconda
+~~~~~~~~
+
+Build instruction using Anaconda is as follows.
+
+.. code-block:: shell
+
+    # For python 3
+    # wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
+    wget https://repo.continuum.io/miniconda/Miniconda2-latest-Linux-x86_64.sh -O miniconda.sh
+
+    bash miniconda.sh -b -p $HOME/miniconda
+    export PATH="$HOME/miniconda/bin:$PATH"
+    conda config --set always_yes yes --set changeps1 no
+    conda update -q conda
+
+    # Download ChainerCV and go to the root directory of ChainerCV
+    git clone https://github.com/chainer/chainercv
+    cd chainercv
+    conda env create -f environment.yml
+    source activate chainercv
+
+    # Install ChainerCV
+    pip install -e .
+
+    # Try our demos at examples/* !
+