Open Source Python Libraries

To use precompiled wheels: 1) go to releases (Files) and download tarball needed; 2) install it with command: python3 -m pip install /path/to/wheel.whl Or simply use URL in pip: python3 -m pip install https://sourceforge.net/projects/gdal-wheels-for-linux/files/GDAL-3.1.4-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl/download URL may be found under "View details" button (i) To use GDAL in C/C++ project you need to link gdal lib AND all libs located at dir GDAL.libs (usually this folder resides inside python site-packages) To compile your own wheels see information given at forefather project: https://github.com/youngpm/gdalmanylinux Usually this is done via command `make wheels` GDAL wheels for Windows are provided by Christoph Gohlke at https://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal Built with PROJ (proj.db is included), GEOS, EXPAT. See Dockerfile.wheels for additional components.

This Python program/library is designed to handle GD-ROM image (GDI) files. It can be used to list files, extract data, generate sorttxt file, extract bootstrap (IP.BIN) file and more. This project can be used in standalone mode, in interactive mode or as a library in another Python program (check the 'addons' folder to learn how). For your convenience, you can use the gditools.py GUI program supplied in the Files section (optional). To use this project you must install the Python 2.7.x branch release binaries. See the README.TXT file for more informations.

This project includes the implementation of a neural network MLP, RBF, SOM and Hopfield networks in several popular programming languages. The project also includes examples of the use of neural networks as function approximation and time series prediction. Includes a special program makes it easy to test neural network based on training data and the optimization of the network.

ffnet is a fast and easy-to-use feed-forward neural network training solution for python. Many nice features are implemented: arbitrary network connectivity, automatic data normalization, very efficient training tools, network export to fortran code. Now ffnet has also a GUI called ffnetui.