Annotation is the most critical part of a deep learning project. It is the determinant of the learning effect of the model. However, this is very tedious and time-consuming. One solution is to use an automatic image annotation tool, which cuts down the time considerably.
This article is part of the pyOpenAnnotate series, which includes the following.
1. A roadmap for image annotation using OpenCV.
2. pyOpenAnnotate workflow.
3. Deploy as a PyPi package.
Here we will discuss annotation tips and techniques in OpenCV. These methods will be used to build automatic annotation tools for single-class labeling.
1. Why use OpenCV to build a custom annotation tool?
In 2022, many annotation tools have numerous features to speed up annotation. RoboFlow and V7 Labs are good examples with AI-assisted annotation. However, outsourcing annotation may not always be the best option for the following reasons.
- Limited free service. Given the costs involved, these services may not be for everyone.
- Since annotation is the largest part of any deep learning project, outsourcing adds a huge overhead in terms of cost.
- There is also the issue of data privacy.
On the other hand, OpenCV has many