Taglab relies mainly on CUDA and Python . Be sure to install Python and the NVIDIA CUDA Toolkit before to install the other packages required. THe CUDA version supported are 9.2, 10.1 and 10.2. TagLab has been successfully tested with Python 3.6.x and Python 3.7.x. We report problems with Python 3.8.x.
The simplest way to install the required packages is through the Python package manager (pip):
| Package | Command |
|---|---|
| (*) pytorch 1.5+ | pip install torch==1.5.1 torchvision==0.6.1 -f https://download.pytorch.org/whl/torch_stable.html |
| pyqt5 5.15+ | pip install pyqt5 |
| scikit-image | pip install scikit-image |
| scikit-learn | pip install scikit-learn |
| pandas | pip install pandas |
| opencv-python | pip install opencv-python |
| matplotlib | pip install matplotlib |
| albumentations | pip install albumentations |
| (**) rasterio 1.1.5+ | pip install rasterio |
| (**) GDAL 3.1.2+ | pip install gdal |
(*) The right command to install pytorch depends on the version of CUDA installed on your system. Go on the Get Started web page of the Pytorch web site, select your system, select Pip, and select your CUDA version to get the command to launch.
(**) On Windows these packages cannot be installed directly using pip. We recommend to install them by getting the
unofficial binaries here. For example, if you are installing
Taglab on a 64-bit Windows system with Python 3.6 you can download and install the GDAL‑3.1.2‑cp36‑cp36m‑win_amd64.whl
wheel for GDAL and the rasterio‑1.1.5‑cp36‑cp36m‑win_amd64.whl wheel for Rasterio.