Metadata-Version: 2.1
Name: imantics
Version: 0.1.12
Summary: Python package for managing image annotations
Home-page: https://github.com/jsbroks/imantics
Author: Justin Brooks
Author-email: jsbroks@gmail.com
License: MIT
Classifier: Environment :: Web Environment
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Multimedia :: Sound/Audio :: Capture/Recording
Classifier: Topic :: Multimedia :: Graphics :: Capture
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=2.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: opencv-python>=3
Requires-Dist: lxml
Requires-Dist: xmljson

# Image Semantics

<p align="center">
  <a href="/jsbroks/imantics/stargazers">
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  </a>
  <a href="https://travis-ci.org/jsbroks/imantics">
    <img src="https://travis-ci.org/jsbroks/imantics.svg?branch=master">
  </a>
  <a href="https://imantics.readthedocs.io/en/latest/?badge=latest">
    <img src="https://readthedocs.org/projects/imantics/badge/?version=latest">
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Image understanding is widely used in many areas like satellite imaging, robotic technologies, sensory networks, medical and biomedical imaging, intelligent transportation systems, etc. Recently semantic analysis has become an active research topic aimed at resolving the gap between low level image features and high level semantics which is a promoting approach in image understanding.

With many image annotation semantics existing in the field of computer vision, it can become daunting to manage. This package provides the ability to convert and visualize many different types of annotation formats for object dectection and localization.

Currently Support Formats:

- COCO Format
- Binary Masks
- YOLO
- VOC

<p align="center">If you enjoy my work please consider supporting me</p>
<p align="center">
  <a href="https://www.patreon.com/jsbroks">
    <img src="https://c5.patreon.com/external/logo/become_a_patron_button@2x.png" width="120">
  </a>
</p>

## Installing

```
pip install imantics
```
