Awesome
Image Semantics
<p align="center"> <a href="/jsbroks/imantics/stargazers"> <img src="https://img.shields.io/github/stars/jsbroks/imantics.svg"> </a> <a href="/jsbroks/imantics/issues"> <img src="https://img.shields.io/github/issues/jsbroks/imantics.svg"> </a> <a href="https://tldrlegal.com/license/mit-license"> <img src="https://img.shields.io/github/license/mashape/apistatus.svg"> </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"> </a> <a href="https://pypi.org/project/imantics/"> <img src="https://img.shields.io/pypi/v/imantics.svg"> </a> <a href="https://pypi.org/project/imantics/"> <img src="https://img.shields.io/pypi/dm/imantics.svg"> </a> </p>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
Installing
pip install imantics