Object detection in torch

Implementation of some object detection frameworks in torch.

Dependencies

It requires the following packages

• xml
• matio-ffi.torch
• hdf5
• inn

To install them all, do

## xml
luarocks install xml

## matio
# OSX
brew install libmatio
# Ubuntu
sudo apt-get install libmatio2

luarocks install matio

To install hdf5, follow the instructions in here

Running this code

First, clone this repo

git clone https://github.com/fmassa/object-detection.torch.git

The zeiler pretrained model is available at https://drive.google.com/open?id=0B-TTdm1WNtybdzdMUHhLc05PSE0&authuser=0. It is supposed to be at data/models. If you want to use your own model in SPP framework, make sure that it follows the pattern

model = nn.Sequential()
model:add(features)
model:add(pooling_layer)
model:add(classifier)

where features can be a nn.Sequential of several convolutions and pooling_layer is the last pooling with reshaping of the data to feed it to the classifer. See models/zeiler.lua for an example.

To finetune the network for detection, simply run

th main.lua

To get an overview of the different parameters, do

th main.lua -h

The default is to consider that the dataset is present in datasets/VOCdevkit/VOC2007/. The default location of bounding boxes .mat files (in RCNN format) is supposed to be in data/selective_search_data/.