Create INSTALL.md

doc/INSTALL.md

@@ -0,0 +1,79 @@
+# Installation
+
+DenseCap is implemented in [Torch](http://torch.ch/), and depends on the following packages:
+
+- [torch/torch7](https://github.com/torch/torch7)
+- [torch/nn](https://github.com/torch/nn)
+- [torch/nngraph](https://github.com/torch/nngraph)
+- [torch/image](https://github.com/torch/image)
+- [lua-cjson](https://luarocks.org/modules/luarocks/lua-cjson)
+- [qassemoquab/stnbhwd](https://github.com/qassemoquab/stnbhwd)
+- [jcjohnson/torch-rnn](https://github.com/jcjohnson/torch-rnn)
+
+After installing torch, you can install / update these dependencies by running the following:
+
+```bash
+luarocks install torch
+luarocks install nn
+luarocks install image
+luarocks install lua-cjson
+luarocks install https://raw.githubusercontent.com/qassemoquab/stnbhwd/master/stnbhwd-scm-1.rockspec
+luarocks install https://raw.githubusercontent.com/jcjohnson/torch-rnn/master/torch-rnn-scm-1.rockspec
+```
+
+### (Optional) GPU acceleration
+
+If have an NVIDIA GPU and want to accelerate the model with CUDA, you'll also need to install
+[torch/cutorch](https://github.com/torch/cutorch) and [torch/cunn](https://github.com/torch/cunn);
+you can install / update these by running:
+
+```bash
+luarocks install cutorch
+luarocks install cunn
+luarocks install cudnn
+```
+
+### (Optional) cuDNN
+
+If you want to use NVIDIA's cuDNN library, you'll need to register for the CUDA Developer Program (it's free)
+and download the library from [NVIDIA's website](https://developer.nvidia.com/cudnn); you'll also need to install
+the [cuDNN bindings for Torch](https://github.com/soumith/cudnn.torch) by running
+
+```bash
+luarocks install cudnn
+```
+
+### (Optional) Training
+
+There are some additional dependencies if you want to train your own model:
+
+- Python 2.7
+- Java JDK 1.5 or higher
+
+You'll also need the development header files for Python 2.7 and for HDF5; you can install these
+on Ubuntu by running
+
+```bash
+sudo apt-get -y install python2.7-dev
+sudo apt-get install libhdf5-dev
+```
+
+You'll need the following Python libraries:
+- numpy
+- scipy
+- Pillow
+- h5py
+
+You will also need DeepMind's [HDF5 bindings for Torch](https://github.com/deepmind/torch-hdf5) which you can install by running
+
+```bash
+luarocks install https://raw.githubusercontent.com/deepmind/torch-hdf5/master/hdf5-0-0.rockspec
+```
+
+You will need to download the pretrained VGG-16 model and the [METEOR](http://www.cs.cmu.edu/~alavie/METEOR/README.html)
+evaluation code; you can do this by running the following scripts from the root directory:
+
+```bash
+sh scripts/download_models.sh
+sh scripts/setup_eval.sh
+```