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python

A Python Ecosystem for Harvesting Datasets information from Amazon S3 via INTAKE catalog and Cultivating STAC-Metadata.

Please have a look at https://intake2stac.readthedocs.io for the documentation.

A Python Ecosystem for Harvesting Time Series data information from SensorthingsAPI (STA) and Cultivating STAC-Metadata.

Please have a look at https://sta2stac.readthedocs.io/ for the documentation.

A Python package to provide seamless functionality for INSerting, UPDating, and DELeting STAC-Metadata toward either pgSTAC or STAC-API.

Please have a look at https://insupdel4stac.readthedocs.io for the documentation.

A Python Ecosystem for Harvesting Datasets information from Thredds Data Server and Cultivating STAC-Metadata.

Please have a look at https://tds2stac.readthedocs.io for the documentation.

graphical interface that allows the simultaneous collection of data coming from a Pressure sensor, PL spectrometer, and camera.

Terminal-based Python scripts to automate processing and classifying of xylem cavitation and optical dendrometry image sequences.

Ultralytics YOLO with DEEPaaS API

Mirror of https://gitlab.cern.ch/geoff/geoff-app/

Mirror of https://gitlab.cern.ch/geoff/cernml-coi/

Mirror of https://gitlab.cern.ch/geoff/cernml-coi-optimizers/

Mirror of https://gitlab.cern.ch/geoff/cernml-coi-utils/

A python package to analyse LSM and DGVM outputs

WDCC-compliant NetCDF Creation Example in Python for HMG NetCDF chapter https://hmg-netcdf.readthedocs.io/en/v1.0.0/examples/example-wdcc-minimal-standard.html

Data Science and analysis project on freshwater discharge on the eastern shoreline of Greenland for the department of Marine Carbon Cycling, Institute of Carbon Cycles at Hereon (KCK, Claudia Schmidt).

This PAS is a GUI-based collection of tools that helps users discover and run Python scripts from a folder and its subfolders. It provides a convenient way to execute Python and Pythonw files directly from a graphical interface, with additional features like automatic library installation and organized program listing. Included are scripts to analyze different data types.

A framework leveraging the Functional Mock-up Interface (FMI) to train, validate, and assess Deep Reinforcement Learning agents in complex multi-physical environments.

Tree Crown Segmentation and Analysis in Remote Sensing Imagery with PyTorch -- https://deeptrees.de