image_to_gravity

Overview

This repository presents a deep neural network which estimates a gravity direction from a single shot.

Datasets

Some datasets are available at ozakiryota/dataset_image_to_gravity.

Usage

The following commands are just an example.
Some trained models are available in image_to_gravity/keep.

Regression

Training

$ cd ***/image_to_gravity/docker/docker
$ ./run.sh
$ cd regression
$ python3 train.py

Inference

$ cd ***/image_to_gravity/docker/docker
$ ./run.sh
$ cd regression
$ python3 infer.py

Inference with MC-Dropout

Preparing...

MLE

Training

$ cd ***/image_to_gravity/docker/docker
$ ./run.sh
$ cd mle
$ python3 train.py

Inference

$ cd ***/image_to_gravity/docker/docker
$ ./run.sh
$ cd mle
$ python3 infer.py

Inference with MC-Dropout

Preparing...

Citation

If this repository helps your research, please cite the paper below.

@ARTICLE{ozaki2021,
	author = {Ryota Ozaki and Yoji Kuroda},
	title = {EKF-based real-time self-attitude estimation with camera DNN learning landscape regularities},
	journal = {IEEE Robotics and Automation Letters (RA-L)},
	volume = {6},
	number = {2},
	pages = {1737--1744},
	year = {2021}
}

The implementation used when it was published is available at Commit 2f66928.

Related repositories

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