the-stellar-summarizers-sp22

Setup

Make sure you have the correct file permission and environment

conda env create -f environment.yml # creates a conda env with the name "acmai"
conda activate acmai # activate conda environment
chmod a+x ./tools/vid2frame.sh # give executing permission to the bash script

To download and unzip SumMe dataset

python ./tools/fetch_dataset.py

To convert videos into .jpg frames in identically titled subfolders

./tools/vid2frame.sh

To read and convert labels into annotation.txt to facilitate data loading into pytorch

python ./tools/readmat.py

If you want to use colab or other platforms that require you to upload files on to a remote server the following allows you to convert the .jpg frames from each video into single frames.hdf5 file.

python ./tools/hdf5.py

Note: our dataloader is NOT yet compatible with this file format

TODO:

• implement loss history plotting
• clean up `annotation.txt (possibly make it relative to each video for easier coding)
• keep requirements.txt / environment.yml up to date
• collect all the scripts into a util folder / unified script
• look into a different file format of faster dataset upload to gdrive (hdf5?)
• write scripts to standardize video resolution (downsample) (explore options: opencv? pytorch? ffmpeg?)
• make sure the scripts work cross-platform (currently macos is ok)
• fix label association of the data image