Take the Scenic Route

Implemention of Take the Scenic Route: Improving Generalization in Vision-and-Language Navigation

Initialize the repo

git clone --recursive VLNActionPriors.git

get pybind as submodule

git submodule add -b master [email protected]:pybind/pybind11.git

Create environment for installation

conda env create -f environment.yml

source activate AcP

Install pytorch:

conda install pytorch=1.0.0 cuda100 -c pytorch

Compile the Matterport3D environment

mkdir build && cd build
cmake ..
make

Dataset Download

R2R data:

bash download_r2r.sh

Pre-computed image features:

mkdir -p img_features/
cd img_features/
wget https://www.dropbox.com/s/o57kxh2mn5rkx4o/ResNet-152-imagenet.zip?dl=1 -O ResNet-152-imagenet.zip
unzip ResNet-152-imagenet.zip
cd ..

Download pre-trained speaker model (following Speaker Follower repo)

bash download_speaker_release.sh

Train the model/agent using Random Walk Data Augmentation

bash run_w_params.sh