Get labels and tags expertly labeled accurate each pixel to get best performance from your models to detect objects, recognize patterns, and make predictions. With our attention to detail and commitment to quality, you can trust us to deliver the annotations you need to take your computer vision and AI applications to the next level.
TagX specializes in providing high-quality data annotation services for AI and ML projects. We understand the importance of accurate and thorough data labeling in order to train and develop effective models. Our team of experienced annotators use a combination of manual and automated techniques to ensure the highest level of precision and consistency in the data labeling process.
Our services include image annotation, video annotation, text annotation, and more, to suit the specific needs of our clients. We also offer flexible turnaround times and the ability to scale up or down as needed. Trust TagX to deliver the labeled data your AI and ML projects require for success.
It involves drawing a rectangular box around the object of interest and assigning a label to it. Bounding box annotation is used to train AI models for object detection, recognition, and tracking.
At TagX, we provide precise bounding box annotation services for various AI applications, including autonomous vehicles, surveillance systems, medical imaging, and more.
Polygon annotation allows annotating a free-form shape around the object of interest, providing a more accurate representation of the object. It can be more suitable in situations where objects have complex or irregular shapes, or where multiple objects or occlusion or overlapping are present.
Whether you need polygon annotation for self-driving car technology, satellite imaging, or other computer vision applications, we can provide the precise annotations you need to train your algorithms and achieve accurate results.
It is used to mark the boundary of an object or a region of interest that is not well-defined by a rectangular or polygonal shape. Polylines consist of a series of connected line segments that can be curved or straight, allowing for more precise and detailed annotations to highlight specific features or regions within an image.
Polyline annotation is generally used in use cases such as road marking, building footprint, or for any other object that has a distinct boundary in the image.
It involves dividing an image into multiple segments and assigning each segment a label based on its content, such as object classes or categories. It is preferred over other methods as it provides more accurate and detailed information about the image. This technique has practical applications in several industries like autonomous driving, medical imaging, and satellite imagery.
At TagX, we provide high-quality semantic segmentation annotation services for various AI applications, helping businesses achieve better accuracy and performance in their computer vision models.
This is useful for various computer vision applications, such as face recognition, pose estimation, and tracking. Keypoint annotation is preferred for these applications because it provides more accurate and detailed information about the location and orientation of specific objects or body parts in an image or video.
At TagX, we provide precise and reliable key point annotation for different AI applications. Some other applications of keypoint annotation include human activity recognition, gesture recognition, and autonomous driving.
It is a technique of creating a 3D bounding box around objects in an image or a video. It provides depth information along with the x, y, and z-axis coordinates of objects in a 3D space. 3D cuboid annotation is used for a wide range of applications, including autonomous vehicles, robotics, and augmented reality.
By accurately determining the size and position of objects in a 3D space, 3D cuboid annotation is crucial for object detection, tracking, and pose estimation in these applications. We provide high-quality 3D cuboid annotation services for different AI applications, helping our clients develop advanced computer vision models for their business needs.
LiDAR (Light Detection and Ranging) annotation is a process of labeling 3D point cloud data captured by LiDAR sensors for AI applications such as autonomous driving, robotics, and environmental monitoring. LiDAR annotation involves identifying and labeling objects, such as cars, pedestrians, traffic signs, and road markings, in the 3D point cloud data.
We have a team of skilled annotators who have expertise in LiDAR data annotation and can deliver accurate and consistent annotations. Our LiDAR annotation services include object detection and classification, 3D object tracking, semantic segmentation, and more.
TagX provides comprehensive data services that support every step of the Machine Learning (ML) and Artificial Intelligence (AI) data pipeline. We understand that data is the foundation of any successful ML or AI project and therefore, we work closely with our clients to provide services that cover the entire data pipeline.
TagX gathers data from various sources such as internal systems, external APIs, and public data sets. We also provide web scraping services to extract relevant data from the web.
Data is curated and cleaned ensuring its relevance to the project. Preprocessing is also done extract features and engineering to make the data usable for Machine Learning and Artificial Intelligence.
TagX provides annotation services at scale to label the data and make it usable for training ML/AI models. We have a team of experts who are well-versed in various annotation techniques such as image annotation, text annotation, and video annotation.
Data is very accessible and ready for analysis. We follow best industry practices to ensure data is well organized and protected. With our services, you can be sure that your data is of the highest quality and ready for analysis, allowing you to gain valuable insights and make informed decisions.
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