# Create python environment (optional)
conda create -n vsd python=3.7
source activate vsd
# Install python dependencies
pip install -r requirements.txt
# For captioning evaluation
python -c "import language_evaluation; language_evaluation.download('coco')"
# To run the SPICE evaluation, you need switch the JDK to 1.8

# Store images, features, and annotations
./datasets
# Image feature extraction
./feature_extraction
# Train VL-T5
./VLModel/
    src/
        modeling_t5.py modeling_bart.py                       <= VL-T5/VL-BART model classes
        caption_sp.py, vrd_caption.py                         <= fine-tuning
        param.py                                              <= (argparse) configuration
        tokenization.py                                       <= custom tokenizer
        utils.py, dist_utils.py                               <= utility functions
    snap/                                                     <= store weight checkpoints

gdrive download 1_SBj4sZ0gUqfBon1gFBiNRAmfHv5w_ph --recursive

## When all the data, pretrained models, and image features get ready, you can train the model:
bash ./baseline.sh gpu_num