Skip to main content

A Python package for track and forecasting.

Project description

HydroTrack - Python Framework for Tracking and Forecasting Clusters

stable pypi conda Documentation Colab Example Downloads Contributors License

Overview

HydroTrack is a Python package designed to identify, track and analyze hydrological phenomena with various data formats. Using time-varying 2D input frames along with user-specified threshold value parameters, HydroTrack is able to detect objects (clusters) and associate their displacement in time.

Algorithm Workflow

The algorithm is divided into three main modules and form the tracking workflow.

  1. Feature detection: Focuses on identifying individual clusters detection from individual frame of data and extraction of features and statistics.
  2. Spatial Operations: Involves spatial operations (intersection, union, difference, etc) between objects (clusters) from consecutive time steps (t and t-1).
  3. Trajectory Linking: Link objects of consecutive time steps based on the spatial association.
  4. Documentation

    For a more detailed information of hydrotrack package please read the user guide available click here.

    Installation

    To install the Hydrotrack package, it is highly recommended to use virtual environments such as: Anaconda3, Miniconda, Mamba, or etc. And to download the package from githu you can do it using the command::

    git clone https://github.com/hydrotrack-project/hydrotrack/
    

    Create environments and install the dependencies from environment.yml file::

    cd hydrotrack
    conda env create -n hydrotrack --file environment.yml
    conda activate hydrotrack
    

    or install package from local file::

    cd hydrotrack
    pip3 install -r requirements.txt
    

    And it is also possible to install directly from the python package repositories (pip or conda-forge)::

    pip3 install hydrotrack
    
    conda install -c conda-forge hydrotrack
    

    Example Gallery

    Open In Colab <https://colab.research.google.com/github/hydrotrack-project/hydrotrack/blob/main/examples/1_Introducing-Hydrotrack.ipynb>_.

    Support and Contact

    For support, email helvecio.neto@inpe.br, alan.calheiros@inpe.br

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

fortracc-1.0.0rc0.tar.gz (2.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

fortracc-1.0.0rc0-py3-none-any.whl (2.5 kB view details)

Uploaded Python 3

File details

Details for the file fortracc-1.0.0rc0.tar.gz.

File metadata

  • Download URL: fortracc-1.0.0rc0.tar.gz
  • Upload date:
  • Size: 2.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.2

File hashes

Hashes for fortracc-1.0.0rc0.tar.gz
Algorithm Hash digest
SHA256 5ce7e596afe8da668acc93313b8e20ff4fb4de087b59727481e5f1e24795778e
MD5 062d50dc6f1c4e83f26c7ebc9915aa76
BLAKE2b-256 bc29bd812055c59a58baa3fa411a78fa62ba61929ee215ea7c21e87acfcc3962

See more details on using hashes here.

File details

Details for the file fortracc-1.0.0rc0-py3-none-any.whl.

File metadata

  • Download URL: fortracc-1.0.0rc0-py3-none-any.whl
  • Upload date:
  • Size: 2.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.2

File hashes

Hashes for fortracc-1.0.0rc0-py3-none-any.whl
Algorithm Hash digest
SHA256 e4c0412332a10a0f978891c056a096db86d50c773345d686a83217f8cce74da5
MD5 94a6a3cffb8878a73fa20d7b89a11669
BLAKE2b-256 65f854b4e6df9a8a4387e2f9849090c0d6f1c8969622a021900ca0dfbd122d96

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page