| Software Requirements | Install | Update | Citation |
Dear TagLab community, we are looking for a Post-doc researcher The grant duration is two years; starting from September, 2023, candidates will work at the Visual Computing Lab at ISTI-CNR in Pisa, Italy, please contact us for more info.
TagLab was created to support the activity of annotation and extraction of statistical data from ortho-maps of benthic communities. The tool includes different types of CNN-based segmentation networks specially trained for agnostic (relative only to contours) or semantic (also related to species) recognition of corals. TagLab is an ongoing project of the Visual Computing Lab.
TagLab allows to :
We are working hard to create a web site with detailed instructions about TagLab. Stay tuned(!)
TagLab runs on Linux, Windows, and MacOS. To run TagLab, the main requirement is just 64bit Python 3.8.x, 3.9.x or 3.10.x.
GPU accelerated computations are not supported on MacOS and on any machine that has not an NVIDIA graphics card. To use them, you'll need to install the NVIDIA CUDA Toolkit, versions 10.2, 11.3, 11.6 and 11.7 are supported. If you don't have a NVida graphics card (or if you use MacOS), CPU will be used.
See the instructions on the wiki.
If you already installed TagLab and you need to update to a new version, you can just run the update.py
script from the terminal (be sure to be into the TagLab main folder, see step 2):
python3 update.py
or, on Windows:
python.exe update.py
The script will automatically update TagLab to the newest version available in this repository.
NOTE: If some package is missing, after an update, re-launch install.py .
If you are updating TagLab from 0.2 version, in order to download also the new networks, please run the update.py
script twice:
python3 update.py
python3 update.py
If you use TagLab, please cite it.
@article{TagLab,
author = {Pavoni, Gaia and Corsini, Massimiliano and Ponchio, Federico and Muntoni, Alessandro and Edwards, Clinton and Pedersen, Nicole and Sandin, Stuart and Cignoni, Paolo},
title = {TagLab: AI-assisted annotation for the fast and accurate semantic segmentation of coral reef orthoimages},
year = {2022},
journal = {Journal of Field Robotics},
volume = {39},
number = {3},
pages = {246 – 262},
doi = {10.1002/rob.22049}
}