We provide training code that can use OxIOD or EuRoC MAV datasets.
- Download the desired dataset and unzip it into the project folder (the path should be
"<project folder>/Oxford Inertial Odometry Dataset/handheld/data<id>/"
for OxIOD and"<project folder>/<sequence name>/mav0/"
for EuRoC MAV) - Run
python train.py dataset output
, wheredataset
is eitheroxiod
oreuroc
andoutput
is the model output name (output.hdf5
).
Pretrained models can be downloaded here:
We provide code for trajectory prediction and visual comparison with ground truth trajectories from OxIOD or EuRoC MAV datasets.
- Download the desired dataset and unzip it into the project folder (the path should be
"<project folder>/Oxford Inertial Odometry Dataset/handheld/data<id>/"
for OxIOD and"<project folder>/<sequence name>/mav0/"
for EuRoC MAV) - Run
python test.py dataset model input gt
, where:
dataset
is eitheroxiod
oreuroc
;model
is the trained model file path (e.g.6dofio_oxiod.hdf5
);input
is the input sequence path (e.g."Oxford Inertial Odometry Dataset/handheld/data4/syn/imu1.csv"
for OxIOD,"MH_02_easy/mav0/imu0/data.csv\"
for EuRoC MAV);gt
is the ground truth path (e.g."Oxford Inertial Odometry Dataset/handheld/data4/syn/vi1.csv"
for OxIOD,"MH_02_easy/mav0/state_groundtruth_estimate0/data.csv"
for EuRoC MAV).
We provide code for computing trajectory RMSE for testing sequences from OxIOD or EuRoC MAV datasets.
- Download the desired dataset and unzip it into the project folder (the path should be
"<project folder>/Oxford Inertial Odometry Dataset/handheld/data<id>/"
for OxIOD and"<project folder>/<sequence name>/mav0/"
for EuRoC MAV) - Run
python evaluate.py dataset model
, wheredataset
is eitheroxiod
oreuroc
andmodel
is the trained model file path (e.g.6dofio_oxiod.hdf5
).