ipyannotator VS ghapi

Compare ipyannotator vs ghapi and see what are their differences.

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ipyannotator ghapi
1 1
34 514
- 1.6%
0.0 5.3
about 1 year ago 17 days ago
Jupyter Notebook Jupyter Notebook
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

ipyannotator

Posts with mentions or reviews of ipyannotator. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-11-08.

ghapi

Posts with mentions or reviews of ghapi. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-31.

What are some alternatives?

When comparing ipyannotator and ghapi you can also consider the following projects:

fastai - The fastai deep learning library

PublicDataReader - 공공 데이터 조회를 위한 오픈소스 파이썬 라이브러리

label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format

PyKakao - 카카오 API를 사용하기 위한 오픈소스 파이썬 라이브러리

Universal Data Tool - Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app.

nbdev - Create delightful software with Jupyter Notebooks

hoosieree

cvat - Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/opencv/cvat]

fastcore - Python supercharged for the fastai library

cvat - Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/cvat-ai/cvat]