AI applications such as machine learning have made great strides in tasks such as speech recognition, traffic forecasting, and detecting online fraud, significantly enhancing our daily lives. Computer vision, a machine learning application, allows machines to “see” and understand their environment much like humans. However, obtaining images annotated to your specifications can be challenging, which can impede your project and slow your time to market, even as your image data volume and variety continue to grow. It is critical to consider your online image annotation techniques, resources, and workforce decisions carefully.
How can you annotate an image online in Saiwa?
Here is a step-by-step guide to using the Saiwa Online image annotation tool:
What is image annotation online?
Image annotation online is the process of adding metadata or labels to digital images using online tools or platforms. The goal of image annotation is to improve the understanding of the content of an image by providing additional information such as object recognition, object detection, segmentation, and categorization. Image annotation can be done manually by human annotators or through automated methods using computer algorithms. Online image annotation is becoming increasingly popular due to the availability of online tools and platforms that allow for collaborative and efficient annotation of large datasets. This process is widely used in various industries such as healthcare, e-commerce, automotive, and entertainment.
Online Image annotation techniques at Saiwa
Machine vision applications often use three different sorts of image labeling online: classification, object identification, and image segmentation. Saiwa offers three annotation services—classification annotation, bounding box annotation, and boundary annotation—to handle these three types of annotations.
- Classification: A whole online image annotation that categorizes the characteristics that are found in the input images is known as classification. Applications for image classification include scene detection, medical detection, surface defect detection, and texture classification. Classification annotation is the simplest and fastest among frequently used image labelling online types.
The Saiwa classification annotation service provides an easy-to-use interface for specifying complete image tags. The user can apply multiple tags to a single image in order to use a set of tags for various applications.
- Object detection: Finding and locating objects of interest in an image are the goals of object detection annotation. The annotator in Saiwa offers tools to draw bounding boxes around all instances of objects in addition to labels. Among of the different types of image annotation, bounding box annotation is the most prevalent. In contrast to image classification, where the entire image is tagged with one class, the label location is an additional parameter in this case.
- Image segmentation: The Saiwa Bounding Box online image annotation Service provides all the necessary tools for a machine learning specialist to classify photos quickly. Several bounding boxes within an image can be defined with a few clicks. One or more labels are added to each bounding box. This service also offers fine granularity and any desired degree of bounding box overlap.