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TU Dublin Quotes

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.

Quotes
TU Dublin
Kyle Hamilton

Kyle Hamilton

PhD Researcher at TU Dublin

Trusted by ML Professionals

Trusted by ML Professionals

Image Annotation Services

Get pixel-accurate image annotation with custom formats and seamless cloud integration

RUN FREE PILOT

Trusted by 100+ Customers

ABB – ASEA Brown Boveri
Uipath
Yale
Bizerba
George Washington University
Toptal
Miami University
Hypatos
NEX
ABB – ASEA Brown Boveri
Uipath
Yale
Bizerba
George Washington University
Toptal
Miami University
Hypatos
NEX
ABB – ASEA Brown Boveri
Uipath
Yale
Bizerba
George Washington University
Toptal
Miami University
Hypatos
NEX

Use Cases for

ML Engineers

ML Engineers

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

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Dealing with time-consuming in-house image annotation workflows

Dataset Business

Dataset Business

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Selling annotated image datasets to clients

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Need high-quality image annotations delivered quickly

AI-Powered Business

AI-Powered Business

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Using ML models for image recognition or automated inspections

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Overwhelmed by growing image datasets needing annotation

Academic Researchers

Academic Researchers

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Need annotated image datasets for peer-reviewed research

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Struggling with limited time for manual image annotation

Discuss your challenges

Check Your Image Annotation Needs

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 Object detection
Facial recognition Facial recognition
Vehicle detection Vehicle detection
Product identification Product identification

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

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 Autonomous driving
Satellite imagery Satellite imagery
Medical imagery Medical imagery

Making detailed shapes when accuracy is critical.

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 Autonomous vehicles
Robotics Robotics
Spatial mapping Spatial mapping

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

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 Facial landmarks
Human pose estimation Human pose estimation
Emotion recognition Emotion recognition
Hand gesture tracking Hand gesture tracking

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

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 Road segmentation
Medical imaging Medical imaging
Land use classification Land use classification

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

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 Crowd analysis
Counting objects Counting objects

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

An example of a panoptic segmentation in data annotation

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

Rectangles

Rectangles

svg
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 Object detection
Facial recognition Facial recognition
Vehicle detection Vehicle detection
Product identification Product identification

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

Polygons

Polygons

svg
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 Autonomous driving
Satellite imagery Satellite imagery
Medical imagery Medical imagery

Making detailed shapes when accuracy is critical.

Cuboids

Cuboids

svg
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 Autonomous vehicles
Robotics Robotics
Spatial mapping Spatial mapping

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

Keypoints

Keypoints

svg
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 Facial landmarks
Human pose estimation Human pose estimation
Emotion recognition Emotion recognition
Hand gesture tracking Hand gesture tracking

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

Semantic segmentation

Semantic segmentation

svg
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 Road segmentation
Medical imaging Medical imaging
Land use classification Land use classification

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

Instance segmentation

Instance segmentation

svg
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 Crowd analysis
Counting objects Counting objects

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

Panoptic segmentation

Panoptic segmentation

svg
An example of a panoptic segmentation in data annotation

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

How It Works

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 line

1 Select annotation method
2 Specify how many objects to process
3 Check the approximate total cost
4 Run free pilot
Select Annotation Method
Amount
0 1M
Estimated Cost
$ x entities
$
RUN FREE PILOT

Send your sample data to get the precise cost FREE

Reviews

What Our Clients Say

Stars "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.

Stars "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.

Stars "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.

Stars “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.

Stars "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.

Stars "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.

Why Projects Choose Label Your Data

No Commitment

No Commitment

Check our performance based on a free trial

Flexible Pricing

Flexible Pricing

Pay per labeled object or per annotation hour

Tool-Agnostic

Tool-Agnostic

Working with every annotation tool, even your custom tools

Data Compliance

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

Email is not valid.

Email is not valid

Phone is not valid

Some error text

Referrer domain is wrong

Thank you for contacting us!

Thank you for contacting us!

We'll get back to you shortly

TU Dublin Quotes

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.

Quotes
TU Dublin
Kyle Hamilton

Kyle Hamilton

PhD Researcher at TU Dublin

Trusted by ML Professionals

Trusted by ML Professionals

FAQs

Do I need to commit to a long-term contract?

Not at all. We offer 3 flexible pricing options:

Short term for one-off projects like academic research
On-demand for seasonal projects when you need additional workforce
Long term for a streamlined data annotation workflow

What is your pricing?

We calculate according to how much time is spent on your object annotation. That’s why the pilot project is also valuable for us – we get to calculate the expenses

When can I start the free pilot?

As soon as we clarify details on your dataset. You’ll get a reply within this or the next work day.

Do you work with our labeling tools?

Absolutely! We’re flexible with any tools you want us to work in.

How can I trust you with my confidential data?

We earned several data compliance certificates to prove our dedication to data security:

PCI DSS Level 1
ISO:27001
GDPR
CCPA

After we sign the NDA, we make sure to anonymize your data for our employees to prevent any data leaks.

What is image annotation?

It’s a servImage annotation is the process of labeling or marking specific objects within an image to make them recognizable for machine learning models. At Label Your Data, this process is conducted with pixel-level accuracy, ensuring that every detail is captured.

Our expert team focuses on delivering precise annotations, offering full transparency throughout the process by providing clients complete access to our tool.ice where people annotate/tag/label visual or text data. The clients use this data to sell it or train an Al model.

What are the best practices for image annotation?

Best practices for image annotation involve achieving high precision, using custom output formats, and ensuring efficient data handling. At Label Your Data, we prioritize pixel-level accuracy to create high-quality annotations.

We also offer custom output formats, including JSON, XML, and masks, tailored to your specific needs. Additionally, our seamless cloud storage integration options, such as API and S3, ensure smooth data transfers, making the annotation process efficient and secure.

RUN FREE PILOT