Image Annotation
Image annotation is the process of labeling or tagging images with metadata, such as bounding boxes, polygons, keypoints, or semantic segmentation masks, to create training data for machine learning models, particularly in computer vision. It involves marking objects, regions, or features within images to provide ground truth data that algorithms can learn from. This is essential for tasks like object detection, image classification, and autonomous driving systems.
Developers should learn image annotation when working on computer vision projects that require supervised learning, as it enables the creation of labeled datasets for training models like convolutional neural networks (CNNs). It is crucial in industries such as healthcare for medical imaging analysis, retail for product recognition, and automotive for developing self-driving car technologies. Using annotation tools improves model accuracy by providing precise, human-verified data.