Annotating Computer Vision Projects

Annotating Computer Vision Projects

Choosing the right images for training, validating, and testing computer vision algorithms will significantly affect your AI project’s success. To train an AI model for object detection, segmentation, and classification with human-like performance, each image in the dataset must be labeled thoughtfully and accurately. Annotation quality makes a significant difference in the performance of machine-learning models, so the better the annotations, the better the results. Image annotation is the process of labeling images in a dataset in order to train a machine learning algorithm. Photo and video annotations are manual, time-consuming, and very important. There are several tools available on the AIEX platform that make this process easier and faster. AIEX supports three main CV tasks: object detection, segmentation, and classification, and provides three different types of annotations.  Let’s review the supported annotation types.