Image Annotation Services

Get pixel-accurate results with image annotation outsourcing, custom formats, and cloud integration.

Trusted by 100+ Customers

Who Benefits from Our Image Annotation Services

ML Engineers

Building image-based ML models for tasks like object detection and classification

Dealing with time-consuming in-house image annotation workflows

Dataset Business

Selling annotated image datasets to clients

Need high-quality image annotations delivered quickly

AI-Powered Business

Using ML models for image recognition or automated inspections

Overwhelmed by growing image datasets needing annotation

Academic Researchers

Need annotated image datasets for peer-reviewed research

Struggling with limited time for manual image annotation

Discuss your challenges

Types of Image Annotation Services We Offer

Rectangles

Rectangles

Polygons

Polygons

Cuboids

Cuboids

Keypoints

Keypoints

Semantic segmentation

Semantic segmentation

Instance segmentation

Instance segmentation

Panoptic segmentation

Panoptic segmentation

An example of object detection depicted as a bird in a rectangle annotation

An example of an annotated facial recognition image, where the face is in the rectangle

An example of an annotated vehicle detection image, where the bus is in the rectangle

An example of an annotated product identification image, where the product is in the rectangle

Object detection

Facial recognition

Vehicle detection

Product identification

Localizing and classifying objects quickly, works for well-defined objects.

Pick the service you need

An example of an annotated autonomous driving image, where the car and traffic lights are annotated using polygons.

An example of an annotated satellite imagery, where the landfill is annotated using polygons.

An example of an annotated medical imaging, where the heart is annotated using polygons

Autonomous driving

Satellite imagery

Medical imagery

Making detailed shapes when accuracy is critical.

Pick the service you need

An example of an annotated autonomous vehicles image, where the cars are annotated using cuboids.

An example of an annotated robotics image, where the warehouse boxes are annotated using cuboids.

An example of an annotated spatial mapping image, where the room is annotated using grid and cuboids.

Autonomous vehicles

Robotics

Spatial mapping

Working with 3D objects and environment to label data in three dimesions.

Pick the service you need

An example of an annotated facial landmark image, where the face is annotated using keypoints.

An example of a human pose estimation, where the person’s body is annotated using keypoints.

An example of an annotated emotion image, where the face is annotated using keypoints.

An example of an annotated hand gesture image, where the hands are annotated using keypoints.

Facial landmarks

Human pose estimation

Emotion recognition

Hand gesture tracking

Tracking fine details such as facial features, skeletal structures, or joint positions.

Pick the service you need

An example of annotated road segmentation image, where the road is processed via semantic segmentation

An example of annotated medical imaging where it is processed via semantic segmentation

An example of annotated land use classification, where the landfill is processed via semantic segmentation

Road segmentation

Medical imaging

Land use classification

Making precise pixel-level classification when it is important, but individual object distinction is not needed.

Pick the service you need

An example of annotated crowd analysis image, where it is processed via instance segmentation

An example of 5 annotated apple images to learn the model how to count, where it is processed via instance segmentation

Crowd analysis

Counting objects

Segmenting when you need to differentiate between individual objects that belong to the same category.

Pick the service you need

An example of a panoptic segmentation in data annotation

Segmenting when you need both pixel-level classification and individual instance differentiation in complex scenes.

Pick the service you need

Rectangles

Rectangles

An example of object detection depicted as a bird in a rectangle annotation

An example of an annotated facial recognition image, where the face is in the rectangle

An example of an annotated vehicle detection image, where the bus is in the rectangle

An example of an annotated product identification image, where the product is in the rectangle

Object detection

Facial recognition

Vehicle detection

Product identification

Localizing and classifying objects quickly, works for well-defined objects.

Pick the service you need

Polygons

Polygons

An example of an annotated autonomous driving image, where the car and traffic lights are annotated using polygons.

An example of an annotated satellite imagery, where the landfill is annotated using polygons.

An example of an annotated medical imaging, where the heart is annotated using polygons

Autonomous driving

Satellite imagery

Medical imagery

Making detailed shapes when accuracy is critical.

Pick the service you need

Cuboids

Cuboids

An example of an annotated autonomous vehicles image, where the cars are annotated using cuboids.

An example of an annotated robotics image, where the warehouse boxes are annotated using cuboids.

An example of an annotated spatial mapping image, where the room is annotated using grid and cuboids.

Autonomous vehicles

Robotics

Spatial mapping

Working with 3D objects and environment to label data in three dimesions.

Pick the service you need

Keypoints

Keypoints

An example of an annotated facial landmark image, where the face is annotated using keypoints.

An example of a human pose estimation, where the person’s body is annotated using keypoints.

An example of an annotated emotion image, where the face is annotated using keypoints.

An example of an annotated hand gesture image, where the hands are annotated using keypoints.

Facial landmarks

Human pose estimation

Emotion recognition

Hand gesture tracking

Tracking fine details such as facial features, skeletal structures, or joint positions.

Pick the service you need

Semantic segmentation

Semantic segmentation

An example of annotated road segmentation image, where the road is processed via semantic segmentation

An example of annotated medical imaging where it is processed via semantic segmentation

An example of annotated land use classification, where the landfill is processed via semantic segmentation

Road segmentation

Medical imaging

Land use classification

Making precise pixel-level classification when it is important, but individual object distinction is not needed.

Pick the service you need

Instance segmentation

Instance segmentation

An example of annotated crowd analysis image, where it is processed via instance segmentation

An example of 5 annotated apple images to learn the model how to count, where it is processed via instance segmentation

Crowd analysis

Counting objects

Segmenting when you need to differentiate between individual objects that belong to the same category.

Pick the service you need

Panoptic segmentation

Panoptic segmentation

An example of a panoptic segmentation in data annotation

Segmenting when you need both pixel-level classification and individual instance differentiation in complex scenes.

Pick the service you need

How Our Image Annotation Services Work

Step 1

Free Pilot

Send your image dataset for free annotation and experience our service firsthand.

Step 2

QA

Examine the pilot results to ensure they match your quality requirements and budget.

Step 3

Proposal

Get a customized proposal based on your image annotation needs and goals.

Step 4

Start Labeling

Start the image annotation process with our expert team to enhance your model.

Step 5

Delivery

Get your annotated images delivered promptly to maintain your project timeline.

Calculate Your Cost
Estimates

1 Select annotation method

2 Specify how many objects to process

3 Check the approximate total cost

4 Run free pilot

Pick Application Field

Select Annotation Method

Keypoints

Rectangles

Polygons

Cuboids

Amount

0 1M

Estimated Cost

$ x entities

$

Send your sample data to get the precise cost FREE

Reviews

What Our Clients Say

Clutch

Clutch

ClutG2 Crowdch

ClutG2 Crowdch

"We were impressed by the labeled data quality as well."

Label Your Data makes significant progress toward the goal of enhancing the client’s algorithm performance. The team works quickly to deliver annotations and annotators with extensive experience in the field. Their project management is straightforward, making for a smooth engagement.

Roman Lutsyshyn

Roman Lutsyshyn

CEO, NLP Development Company

"They’re willing to drop everything to fulfill our needs and keep us happy."

Demonstrating a profound dedication to the project, Label Your Data consistently provides near-perfect deliverables at a cost-effective price. Thanks to their help, the client has been able to be more flexible with their work. Their impressive turnaround time further enhances the solid partnership.

Jack Hopkins

CTO, Raveler Ltd

"Their flexibility and ability to work with multiple languages are impressive."

LYD showed high quality and flexibility and convinced us from day one with their high passion for delivering a great service. We currently evaluate further possibilities to further involve them in our initiatives and projects.

Luca van Skyhawk

Luca van Skyhawk

VP of Customer Success, Hypatos GmbH

“I’m impressed with how easy our communication with the team is and how simple and effective the processes are."

Label Your Data’s support has been crucial in developing the client’s computer vision perception algorithms.

Piotr Swierczynski

Piotr Swierczynski

Director of Engineering, NODAR

"The Label Your Data team was always available for questions."

Label Your Data provided the client with high-quality annotations and added to the number of annotations in the client’s portfolio. The team was consistently available for questions or updates that needed to be added to the data set.

Josha Bharadwa

Software Architect, Searidge Technologies

"They are flexible, dedicated, and their processes are well organized."

Label Your Data sends out weekly data annotation for the client to review. So far, the platform hasn’t had any issues and they are focusing on enhancing the platform since it was launched in November 2020. Their expertise shows productive results as the project progresses.

Asad Lesani

CEO, Blue City Technology

Why Projects Choose Label Your Data

No Commitment

Check our performance based on a free trial

Flexible Pricing

Pay per labeled object or per annotation hour

Tool-Agnostic

Working with every annotation tool, even your custom tools

Data Compliance

Work with a data-certified vendor: PCI DSS Level 1, ISO:2700, GDPR, CCPA

Start Free Pilot

fill up this form to send your pilot request

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Label Your Data were genuinely interested in the success of my project, asked good questions, and were flexible in working in my proprietary software environment.

Kyle Hamilton

PhD Researcher at TU Dublin

Trusted by ML Professionals

FAQs

What factors affect the accuracy of image annotation services?

Several factors influence annotation quality, including clear guidelines, annotation method selection, and workforce expertise. Inconsistent labels, unclear object boundaries, or subjective annotations can lower model performance. Establishing rigorous quality control measures, inter-annotator agreement, and AI-assisted validation helps maintain high accuracy.

What are the most common mistakes in image annotation?

Errors in image annotation often stem from inconsistent labeling, boundary inaccuracies, and class ambiguity. Annotators may also introduce bias if guidelines lack clarity.

To minimize these issues, projects should implement standardized annotation protocols, periodic QA reviews, and dataset audits to ensure consistency and reliability.

How do I choose the right image annotation outsourcing provider?

A reliable provider should offer high accuracy, security compliance, and scalable workflows. Look for multistep validation processes, automation-assisted tools, and proven experience in your specific annotation needs. Transparency in workflow, pricing, and annotation quality assurance is also essential for long-term success.

What role does automation play in improving image annotation?

Automation accelerates annotation by handling bounding box creation, segmentation, and object tracking. However, it requires human validation to correct edge cases, fine-tune object boundaries, and ensure contextual accuracy. The best results come from a hybrid approach.

Why should I use an image annotation service for my project?

Using image annotation services saves time and ensures high-quality, consistent data for training AI models. These services provide expertise in handling large datasets, support various annotation types (e.g., bounding boxes, polygons, or semantic segmentation), and can scale to meet project demands. They are ideal for industries like autonomous driving, healthcare, and e-commerce.