Why do you think Labeling matters?

It matters as it improves accuracy and allows you to build a custom prediction model. Labeling helps you with enhanced accuracy as the machine learning models reflect user data and tailor the model to your specific business needs such as website or app. Moreover, a fully professional labeling solution provides the relevant type of labels according to the requirement of the brand or the software that prints the right labels effortlessly.

Why labeling solution is a critical component? 

• Simplified Compliance

A professional labeling solution creates label changes very easily and helps in ensuring compliance. A centralized management portal and remote maintenance also make it easier for updating the label formats. This helps the companies cut costs of expensive fines or recalls.

• Branding Standards

An advanced labeling solution offers a better chance of productivity and accurate labels on which brands could easily rely on which could be quite costly as well as unreliable in terms of supply. Hence, you need your labeling to reflect your brand needs properly. This includes a company’s certification, patents, trademarks, or other critical data expected from your label.

• Enhanced Responsiveness and Flexibility 

Labeling solutions provide multi-language capabilities and other simple label changes that make the work of the employees easier. This would allow you to personalize your labels for your clients from other regions and deliver unique branding needs respectively.

There are several types of labels available, and based on your requirement you could utilize them.

Such as bounding boxes, Polygons, points, text, select, semantic segmentation, and more. All these data labeling are used for various user-specific purposes.

However, while setting up a project of object detection, you might have to choose the annotation tool. And one of the most commonly used tools in artificial intelligence and machine learning projects are bounding boxes. Apart from that, Polygons exist. Let’s discuss which one you should choose when you have an object detection project to handle.

Bounding Boxes Vs Polygon

Bounding boxes are rectangles drawn by the annotators. Just like any rectangle, a bounding box is defined by two points. The user has to click at the given point and drag it to the second point while drawing a bound box. In other cases, a bounding box is sufficient for defining the position of an object on an image. But, when images are not rectangle-shaped, bounding boxes failed to detect it precisely, so you need something else.

While a Polygon tool is refined but, complex to draw. As Polygons have an arbitrary number of points they can accurately cover an object on an image. The only catch is, it is difficult to draw a Polygon and even more complex for an annotator to use.

Bounding boxes are apt for most cases, you could utilize them efficiently and it simple to draw. Moreover, it has been proved that utilizing Polygons for rectangular objects does not lead to the enhancement of the model’s performance. Hence, Polygons should be used for projects where objects do not fit in a rectangular box. This might be due to the irregular shape or orientation in the picture. Here are two use cases of Polygons, one is geospatial data and the other is autonomous driving. Geospatial data mostly comes from drones or satellites. It is one of the common tasks of annotators where the use of Polygon is a must. In the case of autonomous driving, multiple objects have asymmetric shapes and cannot be annotated with a bounding box.

If you are about to begin an annotation project, it is crucial to define the best tool for annotation. Most of the machine learning models provide good accuracy with bounding boxes and some require Polygons for best results.

Here’s how Data Labelers could help you:

Data Labeler specializes in building quality-labeled datasets for artificial intelligence and machine learning projects. We provide highly accurate labeled datasets, optional real-time bidding, effective guidance on labeling, and sophisticated workforce management software.

Contact us for seamless data labeling and annotation services – sales@datalabeler.com