Image and Video Annotation Service for Machine Learning
Let our expert annotators help you create training datasets with our precise annotation services.
Bounding Boxes
The usage of bounding boxes is one of the simplest and most used approaches for annotating pictures and videos to train computer vision models. By drawing boxes around objects of interest in the image, you may train object classification and localization models with the right amount of data and precise annotations.
And, to assist you in this area of AI, our team of professional annotators is ready to assure the greatest degree of precision for your image. They are thorough in their work and employ the newest tools and technology.
Cuboid Annotation
Cuboid Annotation is used to generate a 3D virtual environment from the 2D data acquired by cameras. The Cuboid Detection models, which assist find and estimate the poses of objects of interest in the actual world, are trained using 3D cuboidal training data.
Cuboid Annotation
Cuboid Annotation is used to generate a 3D virtual environment from the 2D data acquired by cameras. The Cuboid Detection models, which assist find and estimate the poses of objects of interest in the actual world, are trained using 3D cuboidal training data.
Polygonal Annotation
Labeling photographs with features is a simple way to add features to them. What about photographs with unusual forms, such as autos, people, animals, and so on? Polygon Annotation enhances photos by properly sketching polygons around photographs of odd forms. The approach is used to automate object detection for complex objects with high accuracy requirements.
Allow our annotators to assist you in accurately annotating your strangely shaped items from photographs right now!
Keypoint Annotation
If you’re looking for a way to track people’s movements, Keypoint Annotation is the way to go. It allows you to build movement-based algorithms for monitoring human motions by recognizing facial recognition or skeletal features of the human body.
Keypoint Annotation
If you’re looking for a way to track people’s movements, Keypoint Annotation is the way to go. It allows you to build movement-based algorithms for monitoring human motions by recognizing facial recognition or skeletal features of the human body.
Semantic Segmentation
This is an AI service that allows you to interpret an image at the pixel level. You may acquire a deep knowledge of a picture and even discern between distinct things in an image using semantic segmentation. This service can segment photos for use in autonomous driving, medical imaging, and a variety of other applications.
And, because of our cutting-edge technology, we can rapidly and efficiently generate high-quality, pixel-level masks for photos, allowing your AI to readily recognize and track objects in image data.
Linear Annotation
Lines and polylines let self-driving cars detect various lane types on a variety of routes, including city highways and streets. Line annotations provide boundaries between different parts of a photograph to help identify separate elements. Polyline markers, on the other hand, are used to identify road lane markings, lane lines, and drivable sections for autonomous vehicles.
You may immediately collaborate with us to integrate these best data sets for training!
Linear Annotation
Lines and polylines let self-driving cars detect various lane types on a variety of routes, including city highways and streets. Line annotations provide boundaries between different parts of a photograph to help identify separate elements. Polyline markers, on the other hand, are used to identify road lane markings, lane lines, and drivable sections for autonomous vehicles.
You may immediately collaborate with us to integrate these best data sets for training!
Chat with our team
Our team will get back to you with 24-48 hours to schedule an introductory meeting.