Image Annotation Services

iMerit delivers stellar image annotation services that power AI, Machine Learning, and data operation strategies.

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Polygon Annotation

What is image annotation?

Image Annotation is the process of labeling an image, which strategically involves human-powered work and sometimes, computer-assisted help. It is an important step in creating Computer Vision models for tasks like image segmentation, image classification, and object detection. Image annotation can range from annotating every group of pixels within an image to one label for an entire image.

What are the types of image annotation services?

iMerit provides various image annotation services that will cater to a client’s project needs, including bounding boxes, polygon annotations, keypoint annotation, LiDar, semantic segmentation, and image classification. iMerit’s team works with the client to calibrate the quality and throughput of the job and deliver the best cost-quality ratio as you iterate. We recommend running a sample batch to clarify instructions, edge cases, and approximate task times, before launching full batches.

iMerit’s Image Annotation Services

Bounding Box
Bounding Boxes

It is the most commonly used type of image annotation in computer vision. iMerit Computer Vision experts use rectangular box annotation to illustrate objects and train data, enabling algorithms to identify and localize objects during the ML processes.

Polygon annotation for aircraft detection in an airport, use case of Computer Vision
Polygon Annotation

Expert annotators plot points on each vertex of the target object. Polygon annotation allows all of the object’s exact edges to be annotated, regardless of shape.

Semantic segmentation to classify each pixel of a car, use case of computer vision
Semantic Segmentation

Images are segmented into component parts, by the iMerit team, and then annotated. iMerit Computer Vision experts detect desired objects within images at the pixel level.

LIDAR
LiDAR Annotation

iMerit teams label images and videos in 360-degree visibility, captured by multi-sensor cameras, in order to build accurate, high-quality, ground truth datasets for use cases including autonomous vehicles.

Image annotation to classify images on basis of land use category, for geospatial applications
Image Classification

iMerit annotators classify images or objects within images based on custom multi-level taxonomies, including land use, crops, residential property features, among others.

Image Annotation
Process

iMerit subject matter experts will guide you through the process to develop a customized end-to-end workflow.

1
Expert Consultation

Transformative, solution-based approach. Interdisciplinary Image Annotation problem solving. Agility and responsiveness, Time-To-Value enhancers.

2
Training

Targeted resources. Custom skilling. Focused and deep microlearning curriculum. Domain expertise. Rostering tools.

3
Workflow Customization

Alignment of Image Annotation tools and processes. Structured Development Milestones. Two-step production and QA annotation workflows.

4
Feedback Cycle

Transparency via analytics. Real Time Monitoring and Service Delivery Insights. Edge case Insights. Dynamic Model Improvement.

5
Evaluation

Assessment of deliverable. Appraisal of key metrics, quality control processes. Model reconsideration. Analysis of business outcome.

Image Annotation Use Case

keypoint annotation_baseball_computer vision_iMerit

Image annotation for sports AI

iMerit has developed a customized end-to-end workflow for its engagement with KinaTrax, leveraging its proprietary tools and technology as well as the expertise of its experienced Computer Vision teams. Our expert labelers extract still images from in-game video footage of the players captured from numerous angles. The images are annotated precisely based on KinaTrax’s requirements. 

“iMerit’s data annotation services enable us to build accurate models for hundreds of MLB pitchers and turn these models into actionable insights. We look forward to working with iMerit for seasons to come!” – Steven Cadavid, President, Kinatrax

Semantic Segmentation for Autonomous Vehicles

iMerit employs a team of visual data experts who have performed image Annotation on up to  100,000 street images for a client who is a leading global automobile manufacturer and a major contender in the autonomous vehicle segment. Our team has annotated the elements in the images into predetermined classes of objects, ultimately dividing the image into semantically meaningful parts, to train the machine learning algorithm not just to ‘see’ but also to understand and interpret its environment and accuracy.

Image Annotation in Numbers

2

Million

Images Annotated

95

%

Accuracy

We provide image annotation services to AI leaders

Getting Started with Image Annotation

The need for speed in high-quality image annotation has never been greater. iMerit combines the best predictive and automated annotation technology with world-class data annotation and subject matter experts to deliver the data you need to get to production, fast.

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