A Benchmark for Interpreting Grounded Instructions for Everyday Tasks
ALFRED
ALFRED (Action Learning From Realistic Environments and Directives), is a new benchmark for learning a mapping from natural language instructions and egocentric vision to sequences of actions for household tasks. Long composition rollouts with non-reversible state changes are among the phenomena we include to shrink the gap between research benchmarks and real-world applications.
What more? Checkout ALFWorld – interactive TextWorld environments for ALFRED scenes!
Quickstart
Clone repo:
$ git clone https://github.com/askforalfred/alfred.git alfred
$ export ALFRED_ROOT=$(pwd)/alfred
Install requirements:
$ virtualenv -p $(which python3) --system-site-packages alfred_env # or whichever package manager you prefer
$ source alfred_env/bin/activate
$ cd $ALFRED_ROOT
$ pip install --upgrade pip
$ pip install -r requirements.txt
Download Trajectory JSONs and Resnet feats (~17GB):
$ cd $ALFRED_ROOT/data
$ sh download_data.sh json_feat