Final Project of CSC249/449

Welcome to the final project of CSC249/449!

In this final project, you are going to build deep learning models for two tasks on A2D dataset. Please read final_project.pdf for more details of the project requirement.

Preparation

Before start working on a specific task, please do the following preparation on your Google Cloud.

• Clone the repository

  Please use the following command to clone this repository (please do not download the zip file):

  git clone --recursive https://github.com/rochesterxugroup/csc249_final_proj_2020.git

  If there is any updates of the repository, please use the following commands to update:

  git submodule update --remote --merge
  git pull --recurse-submodules

  cd to the cloned repo:

  cd csc249_final_proj_2020

• Environment Configuration

  1. Download and install miniconda from https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh (You can skip this step if miniconda is installed on your google cloud server.)

  2. Install the virtual enviroment and its dependencies by:

     conda env create -f env.yml

  3. Activate the virtual environment by (please remember to activate virtual environment everytime you login on google cloud):

     conda activate pytorch_0_4_1

  4. Then, install Pytorch 0.4.1 and torchvision. (You can try newer version of PyTorch, but we don't guarantee the code template can work with a different environment.)

     conda install pytorch=0.4.1 cuda92 -c pytorch
     conda install torchvision

  5. Install the ffmpeg via

     sudo apt install ffmpeg

• Download A2D dataset

  Please make sure you are at the csc249_final_proj directory.

  1. Download the A2D dataset

     wget http://www.cs.rochester.edu/~cxu22/t/249S19/A2D.tar.gz

     If wget is not install on the server, please install wget via

     sudo apt install wget
     

  2. Decompress the tar ball and remove tar ball.

     tar xvzf A2D.tar.gz
     rm A2D.tar.gz

  3. Extract frames from videos

     (Tip: Since it takes a long time to extract frames from video, you can execute the command in screen or tmux, in case the disconnection happens.)

     python extract_frames.py

Submission

Please read submission/README.md for more details of submission format.