Image Annotation Services

Image annotation services help label images needed for the training of AI models.

The image shows a AI robot and talks about image annotation services by AnnotationBox

What Is Image Annotation Services?

Image annotation Services are the process by which images are labeled, tagged, or annotated to make it easy to train machine learning models. The image annotation process involves identifying data of interest in the annotation picture and then applying different image annotation techniques to mark it to make it easily recognizable by the AI model.
The purpose of annotating images is to make it possible for the ML model to identify the information of interest in an annotated picture without human input. Depending on project needs, image annotation could be simple or complex.

 

Different Types Of Image Annotation Techniques

AI and ML models are as good as the training data used to train them. That makes it essential to have training data that is annotated accurately. Depending on the ML/AI model’s intended end use, annotation images must be annotated using different techniques. Our annotation experts can help you achieve your desired results with accurately annotated images regardless of the data annotation technique.

The image shows several cars on road and 2D bounding box around the cars

2D Bounding Box

It is a commonly used data annotation technique where an annotator draws a box around the annotation picture to resemble the object of interest inside the box. The bounding box is tight and should be drawn along the edges of the target object without cutting out any parts of the object. A 2D bounding provides information about the length and width of the objects of interest. The annotation technique is used for objects that are relatively symmetrical and when the AI training data needed has little focus on the shape of the detection object.

The image shows a few cars labeled in green showing polygon/contour annotation by AnnotationBox

Polygon/Contour Annotation

This annotation technique involves marking the vertices of the target object with points and then joining these points to create an annotation along the object’s exact edges, thus reproducing the precise shape of the target object. It is used when annotating images where the object’s shape is essential, especially for irregular objects such as vegetation and houses. With polygon annotation, a machine learning model is trained to detect, identify and differentiate between objects based on their shape variations.

The image shows a few people, cars, and busses on road referring to semantic segmentation by AnnotationBox

Semantic Segmentation

Semantic segmentation Services work at the pixel level. It includes pixel-wise annotation of the target objects in an image and associating each marked pixel with a predetermined label, class, or category. The class labels assigned to each annotated image represent real-world objects. All objects of a particular type are given the same class and a different color. This image annotation technique is handy in dense detection, where computer vision models must distinguish between objects in an image with multiple objects.

The image shows a few cars and buses on road showing 3D cuboid annotation

3D Cuboid Annotation

3D Cuboid annotation, unlike 2D, goes further by adding the depth of an object in a given image. That creates a 3D perception of the natural world, making objects more perceptible by computer vision models. 3D cuboid annotation is useful when training computer vision algorithms to understand the depth of individual objects such as houses, cars, persons, etc.

The image shows road with lanes referring to polyline annotation

Polyline Annotation

Polyline annotation is an image annotation technique widely implemented in creating training datasets for autonomous vehicles. It involves plotting one or more continuous line segments on an image of interest. It is used with open-shape images such as roads, sidewalks, or power lines to train autonomous vehicles to identify road lanes and other surrounding features along the road. In computer vision, they are used to train drones to avoid power lines.

The image shows Sachine Tendukar’s picture being annotated by AnnotationBox by key point annotation

Key point Annotation

Key point annotation is used to plot characteristics in the data to help train computer vision models to detect particular features of interest. It involves placing points on the key points of interest, such as eyes and ears. Key point annotation helps detect specific features, such as those needed in facial recognition to detect facial features, expressions, and emotions. It is also implemented in computer vision and object detection in sports to detect body position relative to other objects.

The image shows a land annotation by image classification done

Image Classification

Image classification is how AI models can analyze and assign correct labels to an image. It is also the process through which human annotators add labels to images to make them easily understandable to machines. The labels provide a level of detail that makes it possible for machines to quickly identify and classify different objects. Image classification is implemented in autonomous vehicles that need to detect and classify the various objects in their environment.

The image shows lidar annotation referring to using laser to scan environment

Lidar Annotation

Lidar annotation uses a 3D laser to scan the environment and identify objects. Thousands of infrared light pulses are sent into the environment, and the car’s photodetectors record the reflection time. The reflection time determines the proximity to the object. The method allows the vehicle to navigate its environment with high accuracy and reliability. Let our team of experts work on your annotation project, and you are guaranteed high-accuracy annotations for your 360-degree images.

Image annotation services for Machine learning & Computer vision models With Pixel Perfection

The success of an AI model depends on the quality of the AI training data. Poorly annotated image data results in an inaccurate ML model.
Here at Annotation Box, we provide high-quality image annotation services that are bespoke to the needs of your annotation project. Contact us and outsource your data annotation project now.

The doodles shows bullseye referring to 95% accuracy in AnnotationBox’s audio annotation services

99% high accuracy

Accuracy is king, and we are its subjects. We assure our clients nothing short of 99% accuracy.

The doodle shows AnnotationBox is cost-effective

cost-effective pricing

We provide competitive prices customized to offer value for your money. Our prices are diverse depending on your annotation project needs.

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data security

We guarantee that any data shared with us remains with us. We leave no room for data leaks; all our experts sign NDAs to keep your data safe.

Image Annotation Use Cases Across Various Industries

Image annotation is used to create training data for AI in different fields. Using annotated images, AI/ML and computer vision models are trained to identify objects in the real world and make critical decisions.
The doodle shows a car referring to annotation service for autonomous vehicles

autonomous vehicles

Image Annotation for Autonomous vehicles relies on object detection to navigate the environment. That means they must be trained to identify varied objects in their environment. Annotated images are used to create an image dataset that is then used to train the vehicle’s computer vision algorithms to identify and distinguish between different objects.

The doodle shows healthcare sector using AnnotationBox’s image annotation services to enhance productivity

healthcare

Image Annotation for Healthcare is used in the medical field to develop and train medical AI algorithms to detect and identify anomalies in the body. With image annotation, medical AI is trained to identify between, for instance, normal and cancerous cells or to distinguish between a normal bone and a fractured bone.

The doodle shows retail and ecommerce sector using AnnotationBox’s image annotation services to enhance accuracy

retail & e-commerce

Image Annotation for Retail and e-commerce sectors is applying image annotation to help customers find items easily and make recommendations. Through image annotation, AI can classify similar objects together, making it easy for users to find them when browsing. It also allows users to search for objects using images by detecting images identical to the search item and displaying the results to the clients.

The doodle shows operations and chain supply sector using AnnotationBox’s image annotation services to enhance precision

Operations and Chain Supply

Companies are using image annotation to optimize operations along the supply chain lines. AI algorithms are increasingly used to detect the level of materials or resources in supply chain hubs. That allows companies to make timely decisions, thus improving the efficiency of the supply chains.
The doodle shows agriculture sector uses AnnotationBox’s image annotation services to enhance productivity

agriculture

Image annotation for Agriculture plays a significant role in the Agriculture Industry. Annotated images train computer vision models to identify and categorize crop conditions. For instance, with annotated images, drones are trained to detect unhealthy crops, while agricultural robots are trained to carry out autonomous harvesting of fruits.

The doodle shows drone & satellite imagery enhances productivity in various industries

drone & Satellite imagery

Image Annotation for Drone & Satellite Imagery is actively used to train AI models to interpret images captured by drones and satellites. Machine learning models are trained to analyze the captured images and provide insight using different image annotation techniques, such as segmentation. They are also trained to detect foreign objects, such as in border images where illegal immigration can be monitored using satellite imagery.

The doodle shows security sector using image annotation services by AnnotationBox to enhance security

security

Image annotation for Security industry is one of the main applications of image annotation. Computer vision models are trained using annotated datasets to identify different human actions in specific settings. In particular, computer vision, aiding in facial recognition, has become a mainstay in security to identify criminals and provide round-the-clock security in high-security environments.

The geospatial sector uses image annotation services by AnnotationBox

geospatial technology

Resource planning is an essential activity in any country. Image Annotation for Geospatial technology allows stakeholders to identify and map resources. With the help of image annotation, ML models are trained to interpret geospatial images and maps and make inferences helpful to decision-makers. For instance, AI can analyze patterns not identifiable by human eyes.

The insurance industry uses Image annotation services for claims

insurance

Image Annotation for Insurance industry uses image annotation to train ML models to weed out bogus claims. That is achieved by training the model to spot claim inconsistencies, including identifying fake accidents. With this technology, insurance companies can cut the number of fraudulent claims often resulting from staged incidents.

Why Choose Us?

At Annotation Box, we value the goals and vision encompassed by each annotation project. We strive to provide holistic and accurate data annotation services bespoke to the client’s requirements. We ensure constant communication and provide working suggestions where necessary.

500+ Employees-01

1000+

Trained Experts

9+ Accuracy-01

95%+

Accuracy

50+ happy clients-01

50+

Happy Clients

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450+

Successful Projects

The doodle shows a PC and different annotation by AnnotationBox

Get Us Onboard For Image Annotation Services

At Annotation Box, we assure you of a fast turnaround, a team environment, and exceptional communication throughout the annotation project.

How We Work

Get your data annotated in just 5 simple steps.

step

STEP : 1

 Project Assessment

Upon receiving the inquiry we assign experts to understand your project requirements. After in-depth research by our experts and assessing your requirements, we deploy the best data annotation solution for you.

step

STEP : 2

Sample Data Labeling

After deploying data annotation solution. We begin our work. The first step is to ask for your samples. Once we receive your samples, we run sample data labeling. We label the samples and send you back for your review.

step

STEP : 3

Training

Once you’re satisfied with our sample. We deploy a training module for the team to impart an in-depth understanding of the project.
Our Quality analyst keeps checking for the desired quality output with our annotators.

step

STEP : 4

Production

Our dedicated project manager will oversee the team and monitor them constantly to ensure the annotators are meeting the desired output quality set initially and completing the project on time. Annotation Box puts accuracy first and foremost.

step

STEP : 5

Evaluation

We believe in transparency and high-quality data annotation. Through our continuous feedback cycle, we make sure the annotation is done correctly. Our flexible workforce enables us to scale up production at any time.

RIVEW

STEP : 1

 Project Assessment

Upon receiving the inquiry we assign experts to understand your project requirements.

After in-depth research by our experts and assessing your requirements, we deploy the best data annotation solution for you

step

STEP : 2

Sample Data Labeling

One of the finest translation agencies I have come across lately. The friendly experts know what is required and deliver better than expected.They were receiving all my calls during the process. The best part is they are affordable

step

STEP : 3

Training

Once you’re satisfied with our sample. We deploy a training module for the team to impart an in-depth understanding of the project.Our Quality analyst keeps checking for the desired quality output with our annotators

step

STEP : 4

Production

Our dedicated project manager will oversee the team and monitor them constantly to ensure the annotators are meeting the desired output quality set initially and completing the project on time. Annotation Box puts accuracy first and foremost

step

STEP : 5

Evaluation

We believe in transparency and high-quality data annotation. Through our continuous feedback cycle, we make sure the annotation is done correctly. Our flexible workforce enables us to scale up production at any time

Image Annotation Services – FAQs

How do I choose an image annotation services provider for my Annotation Project?

Selecting your image annotation service provider can make or break your annotation project. Ensure that you outsource to a company that fully comprehends your project needs, has a proven track of delivering, and is within your budget.

Do i need to provide my annotation tools?

Using generic or bespoke annotation tools depends on the project’s needs. Some annotation services may offer their image annotation tool, while others may ask the client to offer or recommend their preferred tool. Consider your project and decide whether using off-the-shelf tools will impact the project’s outcome.

How much SHOULD THE IMAGE annotation services Cost?

There is no definite answer regarding how much an image annotation project should cost. Prices vary based on numerous factors, including the annotation technique, delivery period, volume of data to annotate, and the human workforce needed. Therefore it is imperative to work with an outsourcing company that is flexible in its pricing.

Is my data Safe WITH DATA annotation services?

Data security is critical. Ensure that your outsourcing company has robust measures to keep your data safe and private.

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