Build Your Own Image Segmentation Annotation Tool in 5 Minutes | by Florian Trautweiler | January, 2025
How to label an image dataset with OpenCV and Python
Anytime machine learning is used to solve a problem, in some way the goal is to fit ua model to others data. In order for your model to work well and integrate unobserved data, you need to make sure that you are using a high-quality dataset for training. Especially in a supervised learning setting, you need to make sure your data is labeled accurately.
Data is the most important part of machine learning.
No matter how big you make your model, how many billions of parameters you throw at it or how much data you put in, a wrong fit will not don't magically turn into high-quality output.
Depending on the task you are trying to solve, there is not always an adequate public data set available. In these cases, you may need to create your own dataset. However, at first your data is probably unlabeled. Let me show you, how we can build a simple, fast annotation tool to classify your image data from an unlabeled dataset.
Image data set
To demonstrate the annotation tool, I will use a set of image data from my phone recording, where the aim is to classify…
