pip install torch

.
├── efforts                              # Other models we tried
|   ├── Bottom-up-attention-imp          # Implementation of https://arxiv.org/abs/1708.02711 paper
|   ├── san-vqa-tensorflow               # Implementation of https://arxiv.org/pdf/1511.02274.pdf paper 
|   ├── Show_Attend_and_Tell_beam        # Implementation of https://arxiv.org/pdf/1502.03044.pdf paper 
|   └── show_attend_and_tell             # Implementation of https://arxiv.org/pdf/1502.03044.pdf paper 
|
├── resnet                              
|   ├── convert.py                       # Used to build resnet model
|   ├── convert2.py                      # Used to build resnet model
|   ├── resnet.py                        # Used to build resnet model
|   └── synset.py                        # Used to build resnet model
|
├── Visual-Question-Answering_Report.pdf # Project report 
├── config.py                            # Contains parameters for training the model
├── data.py                              # Data loaders for the dataset
├── demo.ipynb                           # Notebook to run the demo
├── dogs.jpg                             # Image used in demo
├── model.py                             # File to build the neural net in
├── preprocess-images.py                 # Extract features from images
├── preprocess-vocab.py                  # Do word embedding
├── tennis.jpg                           # Image used in demo
├── test_img.jpg                         # Image used in demo
├── train.py                             # To train the model
├── utils.py                             # Contains some utility functions
├── vocab.json                           # Vocabulary file created during training
└── README.md