Data Labeling is the process of tagging objects with discrete labels that identify their features such as classifications or properties or characteristics within images or videos. This process involves data annotation, tagging, transcription, and processing.

Data Labeling helps to curate data for Artificial Intelligence and Machine Learning projects. It forms a crucial part of data preparation required for AI/ML Model building It helps to create labeled data or enriched data that trains your ML models for accurate predictions.

Why Data Labeling Matters?

Machines have faster processing speed and better knowledge storage capacity over humans and hence are replacing them in routine and manual jobs. By harnessing their speed, you can turn them into intelligent machines. But, they tend to fall short of humans when they have to analyze and work in real-time environments.  Here is where data labeling comes into the picture. It helps to produce labeled data that can be fed into machines. The labeled data provide the machines with relevant information that helps them to effectively mimic the human brain and process information faster.

Labeled data can be described as well-structured data that can sharpen your ML models. You will require huge amounts of datasets to train your models to predict with high accuracy.

Labeled data helps ML models or algorithms to discover relationships, comprehend, learn, and give sophisticated results. The quality as well as the quantity of the labeled data helps to determine the performance of AI/ML models.

To build a great model you will require labeled data at large scale and the data has to be tagged in such a way that will train your ML algorithm effectively. For instance, feeding an autonomous vehicular model is not enough, you should feed the model with labeled images where each object like a vehicle, pedestrian, street sign, and others have been annotated.

Types of Data Labeling Services

The data labeling services can be segmented into the following three categories

  • Image Labeling Services
  • Video Annotation Services
  • Text Annotation Services

Image Labeling Services

It includes labeling images and making them readable for machines. Image annotation services involve tagging an image entirely using a single label or tag every object in an image with numerous labels. Image labeling acts as a marking tool that highlights objects in an image by sketching around them.

Types of Image Annotation Services

Different types of data annotation techniques can be used as part of image labeling services.

Bounding Box

It involves sketching a box around objects of interest in an image. Bounding box annotation mainly involves drawing a box closer to the edges of objects in an image and mostly the image is tagged as per the custom requirements of data scientists. This image labeling technique aids in the detection, localization, and classification of objects in an image.

Cuboid Annotation

Cuboid Annotation is similar to bounding boxes and involves drawing of a box around objects of interest in images. Bounding box annotation depicts the width and length of objects whereas cuboid annotation depicts the width, length, and depth of objects by highlighting them in 3D

Landmark Annotation

It is also called as Dot Annotation and helps to detect the dissimilarities between objects and even counts miniature objects in images. It is mainly used to identify distant objects in satellite images, predict pedestrians’ motion for self-driving cars, and identify different poses of athletes.

Semantic Segmentation

Also called pixel-level labeling, Semantic Segmentation is more specific and precise. This type of image annotation involves annotating every pixel in an image whereas the other image annotation types mainly deal with highlighting the outer edges of an object in images.

Semantic Segmentation helps to divide the image into multiple segments which in turn depicts it in a meaningful way for the ML models. It is mainly used for training autonomous driving models, analyzing medical images, and classifying visible terrain in satellite images.

Polygonal Segmentation

Polygonal Segmentation is one of the fastest as well as the smartest image annotation types for training ML models. It helps to detect with precision the boundaries of an object and also aids in the detailed object recognition like facial features, logos, and street signs.

Video Annotation Services

Annotated videos can be used as training data to help ML models perform with accuracy and deliver precise results. Advanced techniques and tools are available to annotate any type of video.

Video annotation services are leveraged for training self-driving cars on object tracking. It helps the autonomous vehicular models to recognize sign boards, other vehicles, street lights, pedestrians, cyclists, and traffic signals. Live video annotations help the computer vision models track human poses easily and understand the facial expressions of humans while performing various tasks.

Text Annotation Services

We can divide text annotation services into the following three types:

  • Classification tasks where each text segment is assigned one or more labels.
  • Classification with sentiment involves assigning labels to text segments along with sentiment like positive or negative.
  • Entity extraction tasks involve assigning a labeler with a text segment and a set of labels and he or she will identify the start and end place of the text talking about each label.

Text annotation services can be used to develop and train virtual assistants and text moderation models. It helps the models to perform certain NLP tasks like document classification, intent recognition, entity recognition, and eCommerce tagging.

Use Cases of Data Labeling

RightClick.AI offers a diverse range of Data Labeling Services that can be availed for the following use cases;

Training Data for Computer Vision Models Powering Autonomous Vehicles


We are adept at creating a wide range of labeled datasets for training and validating the self-driving cars that enable them to develop safe driving techniques. RightClick.AI offers data annotation services for the following use cases of autonomous vehicular models:

Parking and Lane Area Detection – We offer labeled datasets that help to train your Computer Vision models in detecting lane markings and lanes, identify drivable and parking areas for safe driving on roads.

Object Recognition – Our training datasets help your self-driving cars to accurately detect nearby objects.

Semaphore Analysis – Using bounding boxes, we annotate traffic lights and signboards that helps to train your self-driving models to detect semaphores accurately.

Agriculture Redefined with World-class Data Labeling Services

RightClick.AI provides high-quality labeled datasets to improve the capabilities of your AI/ML models for precision agriculture. We have a team of experts who are adept at creating annotated and labeled images using bounding boxes and polygons that help to train your Computer Vision models at scale for precision agriculture.

Data Labeling Services for Precision Agriculture:

Pest & Disease diagnosis – We provide datasets to train your smart detection systems to identify pest attacks.

Crop Harvesting – RightClick.AI specializes in creating training datasets to help train and validate your ML models on crop harvesting.

Weed Control – Our training datasets will help train your Computer Vision models to identify individual plants and differentiate between desired crops and weeds.

Livestock Monitoring – Our data annotation services will help train your ML models to accurately account for cattle while letting in/out for grazing.

Accurate Labeled Datasets for Retail Space

We leverage a diverse range of Data Labeling services from bounding boxes and semantic segmentation to polygonal and cuboid to offer high-quality datasets for detecting different object types in retail outlets.

Cashier-less checkouts

We offer best-quality labeled images for training your Computer Vision models for counting products and detecting objects thereby enabling cashier-less checkouts.

Shelf Management

By leveraging our world-class image labeling services, we will help train your models to analyze item location, shelf space usage, and pricing thereby helping to optimize the allocation of shelf space.

Product recognition

RightClick.AI specializes in providing pixel-perfect product annotation services for retail outlets to enable the ML models to detect products accurately.

Wildlife Estimation and Assessment

In recent times, assessment and evaluation of wildlife status, distribution, and population trends have been done using Machine Learning tools. The use of motion-sensor cameras, aerial imagery, and other wildlife monitoring tools have provided rich datasets that help us understand and improve our ability to conserve wildlife.

We specialize in extracting information from the wildlife monitoring data and convert them into training labeled datasets that help our clients to develop and train ML/AI models for monitoring wildlife.

You can train your ML models using our high-quality datasets to do the following:

  • Studying the behavior of animals
  • Estimation of wildlife population trends
  • Conducting surveys on wildlife population
  • Detecting rare species in videos and images

Training Machines for Better Speech and Text Recognition

Machines have to be trained to understand human language that is complex and nuanced. Human-labeled data at large scales should be fed into machines to help them interpret various variables like context, references, situational constraints, and others to understand a string of words and reply back.

RightClick.AI is known for providing world-class audio and text labeling services for training Natural Language Processing models. Our high-quality labeled datasets help to train your ML models to perform the following human-like tasks:

  • Design Chatbot interactions
  • Understand and generate text
  • Deliver personalized interactions for virtual assistants
  • Recognize intent
  • Perform sentiment analysis
  • Perform pattern recognition for enhanced customer service

Train Facial Recognition Models with Enterprise-class Data Labeling Services

From fraud detection to security and surveillance to banking & finance to customer service, Facial Recognition technology provides a myriad of use cases. But these models require labeled face image data at large volumes to work accurately.

RightClick.AI offers pixel-perfect data labeling services that help to improve the accuracy of your facial recognition models. Our keypoints annotation services help to train and test ML models to perform emotion detection, facial recognition, and gesture labeling.


As one of the best data labeling companies, RightClick.AI offers world-class image, video, and text labeling services to train your ML-based Computer Vision models. Reach out to us at for state-of-the-art data labeling services.

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