kvananth / SceneDetection

Detecting Scene Breaks in Videos using Deep CNN

Installation

You need to install:

• Torch7
• cunn for training on GPU
• cudnn for faster training on GPU
• tds for some data structures
• display for graphs

You can install all of these with the commands:

# install torch first
git clone https://github.com/torch/distro.git ~/torch --recursive
cd ~/torch; bash install-deps;
./install.sh

# install libraries
luarocks install cunn
luarocks install cudnn
luarocks install tds
luarocks install https://raw.githubusercontent.com/szym/display/master/display-scm-0.rockspec

Model

Imagenet pretrained VGG16 - modified to do binary classification

Data Setup

Check iPython notebook to preprocess data assuming you already extracted frames from the video.

After you create this file, open main.lua and change data_list to point to this file. You can specify a data_root too, which will be prepended to each filename.

Training

Finally, to start training, just do:

$ CUDA_VISIBLE_DEVICES=0 th main.lua

During training, it will dump snapshots to the checkpoints/ directory every epoch. Each time you start a new experiment, you should change the name (in opt), to avoid overwriting previous experiments. The code will not warn you about this (to keep things simple).

Evaluation

To evaluate your model, you can use the eval.lua script. It mostly follows the same format as main.lua. It reads your validation/testing dataset from a file similar to before, and sequentially runs through it, calculating the accuracy.

Graphics, Logs

If you want to see graphics and the loss over time, in a different shell on the same machine, run this command:

$ th -ldisplay.start 8000 0.0.0.0