A PyTorch implementation of the paper Using-Open-Surgery-Simulation-Kinematic-Data-for-Tool-and-Gesture-Recognition.
This implementation uses Python 3.6 and the following packages:
opencv-python==4.2.0.32
optuna==2.8.0
numpy==1.19.5
torch==1.8.1
pandas==1.1.5
wandb==0.10.33
tqdm==4.61.2
termcolor==1.1.0
We recommend to use conda to deploy the environment
To train and test the model on all the splits run:
python train_experiment.py
The visualization result is located in summaries/APAS/experiment_name,
Where experiment_name is a string describing the experiment: the network type, whether it is online, etc.
@article{DBLP:journals/cars/GoldbraikhVPL22,
author = {Adam Goldbraikh and
Tomer Volk and
Carla M. Pugh and
Shlomi Laufer},
title = {Using open surgery simulation kinematic data for tool and gesture
recognition},
journal = {Int. J. Comput. Assist. Radiol. Surg.},
volume = {17},
number = {6},
pages = {965--979},
year = {2022},
url = {https://doi.org/10.1007/s11548-022-02615-1},
doi = {10.1007/s11548-022-02615-1},
timestamp = {Thu, 02 Jun 2022 16:58:49 +0200},
biburl = {https://dblp.org/rec/journals/cars/GoldbraikhVPL22.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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