Millions of real-world data samples are required to effectively train computer vision models to truly “see” the world. This crucial need for human-annotated data is absolutely necessary for mission-critical applications, such as autonomous vehicles or facial recognition, where images must often be labeled down to a single pixel.
At TaskUs, we provide clients with the highest-quality image, video, and sensor training data services to maximize recognition speed, accuracy, and reliability.
Our rigorous training and testing process enables Us to design custom, effective quality frameworks to both meet and exceed our clients’ data quality standards.
Flexible Labeling Tools
Our use of industry-leading tools, tech, and solutions enables Us to label image and video data quickly and at scale, supporting a wide range of computer vision projects.
Project Management Expertise
We continuously demonstrate our expertise in executing complex, large-scale programs catered to our partners’ computer vision data labeling needs.
Data Security
We continuously and diligently provide enterprise-level security options for sensitive data or compliance needs, from on-site staffing solutions to ISO-certified facilities.
Computer Vision Services
Train and power computer vision models through our wide and effective range of sensor, image, and video annotation types.
We support a wide range of image annotation types including bounding boxes, polygon annotation, and semantic segmentation.
Video Annotation
We feed your computer vision models with accurately annotated video datasets. Collect and classify videos, classify individual frames and events, detect and track specific objects, and more with Us.
Point Cloud Annotation
We employ high-precision labeling tools to meticulously annotate point cloud data from a variety of sources, including cameras, LiDAR, and radar sensors.
Image Transcription
We identify and extract text from images, PDFs, and more to increase the accuracy of optical character recognition (OCR) models. We support all image transcription projects regardless of content type, subject matter, or scale.
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