Metadata-Version: 2.1
Name: robotathome
Version: 0.3.3
Summary: This package provides a Python API that assists in loading and parsing the annotations in Robot@Home Dataset
Home-page: https://github.com/goyoambrosio/RobotAtHome_API
Author: G. Ambrosio-Cestero
Author-email: gambrosio@uma.es
License: MIT
Description: # Robot@Home Dataset API #
        
        ![GitHub tag (latest by date)](https://img.shields.io/github/v/tag/goyoambrosio/RobotAtHome_API?style=plastic)
        
        The Robot-at-Home dataset (Robot@Home, paper
        [here](http://mapir.uma.es/papersrepo/2017/2017-raul-IJRR-Robot_at_home_dataset.pdf))
        is a collection of raw and processed data from five domestic settings compiled
        by a mobile robot equipped with 4 RGB-D cameras and a 2D laser scanner. Its main
        purpose is to serve as a testbed for semantic mapping algorithms through the
        categorization of objects and/or rooms.
        
        This package provides the Python API that assists in loading, parsing, and
        visualizing the annotations in Robot@Home. Please visit http://mapir.isa.uma.es/
        for more information on Robot@Home, including for the data, paper, and
        tutorials. The exact format of the annotations is also described on the
        [Robot@Home website](http://mapir.isa.uma.es/mapirwebsite/index.php/mapir-downloads/203-robot-at-home-dataset.html).
        
        In addition to this API, please [download](https://zenodo.org/record/4495821)
        the Robot@Home Dataset in order to run the demos and use the API (also, you'll
        be able to download it using the API).
        
        To install
        
        ```
        pip install robotathome
        ```
        
        or under conda environment
        
        ```
        conda config --append channels gambrosio
        conda install robotathome
        ```
        
        Be careful with the opencv library because the pip installation is based on an
        unofficial opencv-python package, while the conda installation is based on the
        official opencv, usually at an earlier stage than the unofficial one.
        
Keywords: semantic mapping object categorization object recognition room categorization room recognition contextual information mobile robots domestic robots home environment robotic dataset benchmark
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
