- Download requirements
cd TMLGA
sh ./downlad.sh
- Download pretrained weights here and move them to
TMLGA/checkpoints/charades_sta
- To test that everything works, run
python main.py --config-file=experiments/charades-sta.yaml
- Download the VGG16 checkpoint and C3D checkpoint and put them in
VideoQA/util
- Download the word embeddings trained over 6B tokens (glove.6B.zip) from GloVe, unzip them, and put the 300d file in directory
VideoQA/util
pip install -r PSAC/requirements.txt
- Download the MSVD-QA dataset and place it in
PSAC/MSVD-QA
- Download the youtube videos from the MSVD dataset (YouTubeClips.tar in the downloads section) and unzip them into
PSAC/MSVD-QA/video
- Convert video names from garbled YouTubeClips video names into their corresponding video IDs, using this file as the mapping between YouTubeClips.tar name and the real ID
- Delete problematic videos with IDs:
- 451
- 745
- 1106
- 1120
- 1258
- 1357
- 1475
- 1595 (TODO: LATER -- Figure out how to deal with these)
- Pre-process the videos by running:
python preprocess_msvdqa.py PSAC/MSVD-QA