fbpx Image Annotation Guide For Beginners
AI Tech

Image Annotation Guide For Beginners

Image annotation is the process of training image recognition models via deep learning in order to assign an accurate label to an image. Training a model for such a purpose can help alleviate some of the labor intensive responsibilities from carrying out the task manually.

What is image recognition?

Image recognition is the innovative ability of software to identify various different things in images. These can include objects, places, people, text, joint positioning and much more. In order to reach the point at which software can execute image recognition capabilities successfully, users have to train the model in a vigorous process. The good news is that nowadays there are many platforms available to help with this process as many individuals are not savvy with programming and coding. SentiSight.ai is a great example of a user-friendly platform with a wide range of features for users of all abilities.

How big a role does image annotation play in image recognition?

Image annotation, also commonly referred to as image labeling, plays a crucial role in the training process. It may be used for image classification (either single-label or multi-label classification models), object detection (assign labels via bounding boxes or polygons to the object of interest within an image), and image segmentation (usually split into semantic or instance image segmentation models).

There is no one way to executing image annotation when training your model. As alluded to above, the points of interest within your dataset might be of different shapes and sizes which is why the flexible choice of annotating images via bounding boxes, keypoints, polygons and bitmaps is important in order for accurate labels to be attributed to the desired part of the image.

What are the use cases as a result of image annotation?

When it comes to use cases, if image annotation has been correctly applied, you will eventually end up with a trained image recognition model ready for deployment. There is a huge variety of use cases including:

  • Medical imaging
  • Defect detection
  • Similar result section for online clothing sites
  • Pose estimation
  • Sorting photographs
  • Maximizing harvest yield within agriculture

If you’re interested in the field of image recognition then image annotation is definitely something that is required in order for you to reach your desired end goal.

Leave a Reply

Your email address will not be published. Required fields are marked *