Computer vision a field of study that seeks to develop techniques to help computers see and understand the content of digital images such as photographs and videos and Our work in Computer Vision & Machine Learning powers innovation in the area of various sectors through Accurate & high quality labeled Data from our Professional & well-trained annotators.
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a) LIDAR Annotation and Labeling
LIDAR stands for Light Detection and Ranging. It is a remote sensing technology emitting light which travels around the object and back to the receiver creating points everytime it hits the object building a 3D map of the entire scene. We help annotate or label cars, pedestrians, bicyclist, trees, animals, traffic lights, bill board, garbage bin’s etc in this map by drawing bounding boxes or cuboids precisely to train the machine learning algorithms to interpret the world.
b) Bounding box annotation
Bounding boxes for object detection, classification, and localization in images and videos. In Bounding box annotation we train algorithms to detect the various objects on the streets like lanes, traffic, potholes, signals, and other objects. Bounding boxes are imaginary boxes drawn on an image, shape, or text and then we label the contents of the box to help a model recognize it as a distinct type of object. Bounding boxes are one of the most common ways that video or image annotation is done.
c) Polygon annotation
Human-powered polygon annotation for both irregularly shaped and coarse object training data in images and video. Learning Spiral is providing quality polygon annotation service that helps to annotate objects in angled photos and polygon shapes. Our annotators help to detect the exact shape of an object by drawing pixel-perfect polygons to meet your specifications.
d) Keypoint and Skeletal annotation
Our workforce annotates facial and motion to train the machine learning algorithms. Where we label the objects in an image using points to determine the shape of it. Key point annotation is used to label facial/skeletal features, automotive parts, etc.
f) Semantic Segmentation
Semantic Segmentation a classic Computer Vision problem that involves taking as input some raw data (2D, 3D images) and label the regions of interest highlighted. Under Semantic Segmentation, we do the process of clustering various parts of images together belonging to the same object class. Leverage our fully-managed human-powered pixel-level image segmentation and annotation to build pixel-perfect semantic segmentation tasks at scale.
g) Geospatial imaging
Geospatial imagery encompasses aerial, drone imagery, satellite images. We help them built-in image analysis to assess and make business-critical decisions about their business. Whether that be their mapping farm, construction site, mine, real estate project, roof or crop insurance, disaster recovery situation, or forest.
Learning Spiral is here to Empower your algorithm with our human data labeling. Our ISO 27000 certified facilities are equipped to handle the most secure data, and our training data expertise helps reduce ramp time and increase quality.