RectLabel was released in 2017 by the developer Ryo Kawamura.
In the previous company, he was working on face and face landmark detection.
The technology was patented and started be used by Nintendo Mii Studio in 2011.
After quitting the previous company in 2013, he started working on human body detection.
To label human body images, he was using open source image annotation tools including web applications.
But he realized that he should develop more simple, easy to work with, and no network connections image annotation tool.
This is the beginning of RectLabel.
To support our users, we set up a support page on Github and started supporting researchers and developers.
Our users have given us great ideas to improve UX design and add new features.
We have responsively updated RectLabel and obtained hundreds of stars for the support page.
Some researchers have cited RectLabel on their papers and the research domain ranges from deep sea, forest conservation, medical, and so on.
MBARI(Monterey Bay Aquarium Research Institute) researchers posted their paper on nature.com and listed RectLabel in their citations.
The merit of using RectLabel is no network connections.
Our users can label images offline, for example, on the airplane.
RectLabel is a common tool used on macOS for generating new training datasets.