Computer Vision Annotation Tool: Difference between revisions

Revision as of 18:18, 8 January 2021

Revision as of 18:30, 8 January 2021

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CVAT supports the primary tasks of [[Supervised learning|supervised machine learning]]: [[object detection]], [[image classification]], and [[image segmentation]]. CVAT allows users to annotate data for each of these cases.<ref>{{Cite web|url=https://software.intel.com/en-us/articles/computer-vision-annotation-tool-a-universal-approach-to-data-annotation|title=Computer Vision Annotation Tool: A Universal Approach to Data Annotation|date=2019-03-04|website=software.intel.com|language=en|access-date=2019-08-13}}</ref>

CVAT has many powerful features, including [[interpolation]] of bounding boxesshapes between key frames, semi-automatic annotation using [[Deep learning|Deep Learning]] models both in [https://software.intel.com/en-us/openvino-toolkit Intel OpenVINO] and [[TensorFlow]] Object Detection API formats, shortcuts for most critical actions, a dashboard with a list of annotation projects and tasks, [[Lightweight Directory Access Protocol|LDAP]] and [[basic access authentication]], etc.<ref>{{Citation|title=User's guide of Computer Vision Annotation Tool|date=2019-08-13|url=https://github.com/opencv/cvat/blob/develop/cvat/apps/documentation/user_guide.md|publisher=OpenCV|access-date=2019-08-13}}</ref>

CVAT is written mainly in [[JavaScriptTypeScript]], [[HTMLReact (web framework)|React]], [https://ant.design Ant Design], [[Cascading Style Sheets|CSS]], [[Python (programming language)|Python]], and [[Django (web framework)|Django]]. It is distributed under the [[MIT License]], and its source code is available on [[GitHub]].

==See also==