python==3.6 pytorch==0.4.0 anaconda recommended
install additional requirements with
pip install -r requirements.txt
clone roi_align (anywhere you like)
git clone https://github.com/longcw/RoIAlign.pytorch.git
cd RoIAlign.pytorch
modify the -arch argument in install.sh to suite your GPU.
See https://arnon.dk/matching-sm-architectures-arch-and-gencode-for-various-nvidia-cards/ for more information
sh install.sh
sh test.sh # to see if it's correctly installed
download glove 6B word embeddings from http://nlp.stanford.edu/data/glove.6B.zip
unzip in a folder
make a soft link under data/
download the GQA dataset from https://cs.stanford.edu/people/dorarad/gqa/download.html
make a soft link under data/
make sure you have:
cd $VRE_ROOT
tree data/gqa -L 1
data/gqa
├── images - all the image files extracted in this folder
├── objects - object features (.h5 files and the .json)
├── questions12 - v1.2 question json files
└── scene_graphs - scene graph json files
tree data/glove -L 1
data/glove
└── glove.6B.300d.txt
preprocess data:
cd $LSVRD_ROOT
sh scripts/prepare_data.sh
$LSVRD_ROOT
├── cache
├── configs # configuration files
├── data
│ ├── glove -> /path/to/glove/
│ └── gqa -> /path/to/gqa/
├── lib
│ ├── data
│ │ ├── dataset.py
│ │ ├── h5io.py
│ │ └── sym_dict.py
│ ├── evaluate.py # evaluation function
│ ├── loss
│ │ ├── consistency_loss.py
│ │ ├── triplet_loss.py
│ │ └── triplet_softmax_loss.py
│ ├── model
│ │ ├── language_model.py
│ │ ├── loss_model.py
│ │ └── vision_model.py
│ ├── module
│ │ ├── backbone.py
│ │ ├── entity_net.py
│ │ ├── relation_net.py
│ │ └── similarity_model.py
│ ├── train.py
│ └── utils.py
├── main
│ └── train.py
└── scripts
You can optionally use scripts/pre_extract_features.py to extract ResNet-101 feature maps as
preprocessing.
example:
python main/train.py \
--config configs/resnet101-512-14-7-7-GRU-300d-1layer-5-0-256-128-0.2-0.2-1.0-1001-gt-311-100000-1e-4-0.8.json \
--n_epochs 5 \
run python main/train.py --help for other options.
To extract features on GQA, use main/infer.py
example:
python main/train.py \
--config configs/
--lckpt path/to/language/model.pth
--vckpt path/to/vision/model.pth
--dataset gqa
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