DCSAM sonar_oculus dino-vit-features (see below)
[paper] [project page]
@article{amir2021deep,
author = {Shir Amir and Yossi Gandelsman and Shai Bagon and Tali Dekel},
title = {Deep ViT Features as Dense Visual Descriptors},
journal = {arXiv preprint arXiv:2112.05814},
year = {2021}
}
Their code is developed in pytorch
on and requires the following modules: tqdm, faiss, timm, matplotlib, pydensecrf, opencv, scikit-learn
.
They use python=3.9
but the code should be runnable on any version above 3.6
.
They recommend running their code with any CUDA supported GPU for faster performance.
Setup the running environment via Anaconda by running the following commands:
$ conda env create -f env/dino-vit-feats-env.yml
$ conda activate dino-vit-feats-env
Otherwise, run the following commands in your conda environment:
$ conda install pytorch torchvision torchaudio cudatoolkit=11 -c pytorch
$ conda install tqdm
$ conda install -c conda-forge faiss
$ conda install -c conda-forge timm
$ conda install matplotlib
$ pip install opencv-python
$ pip install git+https://github.com/lucasb-eyer/pydensecrf.git
$ conda install -c anaconda scikit-learn