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Scale your image and video annotation with expertly-trained and professionally-managed data annotators.
Training machines to interpret and understand the visual world requires a high volume of accurately labeled training data. Sure, you could toss your labeling project to an unknown crowd, an inflexible outsourcer, or a faceless platform API. But your project and training data needs are unique. We can help.
From bounding boxes and object tracking to semantic segmentation and keypoint annotation, our skilled data analysts apply best practices developed from annotating millions of images and videos to deliver best-in-class data labeling for computer vision leaders around the world.
A fully managed, end-to-end data annotation service for one, inclusive price. All of the software and workforce is included, simplifying your experience so you can focus on innovation.
If you already have a data annotation tool or prefer to bring your own, our team of data analysts is ready to work. We become an extension of your own team, seamlessly supporting your data labeling workflow with consistent, high-quality image and video data annotation. We scale the process for you.
From object recognition and tracking to semantic segmentation and 3-D point cloud annotations, we bring a greater understanding of the visual world with detailed, accurately labeled images and videos to improve the performance of your computer vision models.
Drawing a box around a target object in visual data. Bounding boxes can be 2-D or 3-D.
Plotting characteristics in the data, such as eyes and nose in an image used for facial recognition.
Using a more complex version of landmarking to annotate geometric features, straight lines, and their intersections to assemble 3-D structures within a scene.
Applying semantic or instance segmentation to conceal areas in an image and reveal other areas of interest. Image masking makes it easier to focus on certain areas of an image over other areas.
Drawing 3-D bounding boxes to annotate and/or measure many points on an external surface of an object. These typically are generated using 3-D laser scanners, RADAR sensors, and LiDAR sensors.
Outlining the highest vertices, or points, of the target object to reveal its edges. Polygons are used when objects are irregular in shape, such as homes, areas of land, or topographical details.
Plotting lines composed of one or more segments when working with open shapes, such as road lane markers, sidewalks, or power lines.
Identifying and tracking an object’s movement across more than one frame of video.
Capturing the text that occurs in images or video so it may be labeled.
Our vetted, managed teams have served hundreds of clients across thousands of use cases that range from simple to complex.
Our proven processes securely and quickly deliver accurate data and are designed to scale and change with your needs.
Contract terms that include all you need to succeed and predictable hourly pricing that removes the risk of hidden costs.
With the help of CloudFactory, we’re being a lot more ambitious with our data sets. We have the freedom now to spend 400 hours annotating a large data set, because it isn’t taking up the time of internal resources.
CloudFactory helped Luminar launch a product that dramatically increases autonomous vehicle perception.
Sensor-as-a-service start-up finally finds an annotation solution that can help them expand.
Medical AI company stays ahead of the curve by labeling 24,000 images in 6 months.
We’d love the opportunity to answer your questions or learn more about your project. Let us know how we can help.
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