Image Annotation Services

Outsource your image annotation process to DIGI-TEXX and receive high-quality training data sets for your AI model within your desired timeline

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Different image annotation projects may have slightly different requirements. We have served many clients just like you.

There are various types of image annotation services used for computer vision in machine learning and AI. The quality and accuracy of your computer vision model’s training data significantly impact its performance. This training data includes videos, images, and other types of data.

To ensure the success of an image annotation project, a team of trained and professionally managed annotators is necessary. Functional and user-friendly annotation methods and tools are the backbone of every successful image annotation project.

We use modern capturing tools to annotate different types and sizes of images, making them recognizable for machines or computer vision. Our team uses the latest tools and techniques to annotate images, providing a training data solution for machine learning in various subfields.

Image annotation services

We provide accurate and cost-effective industry-optimized image labeling services to streamline your business processes. Our experienced and professional staff ensures high-quality and accurate data. Here’s a brief overview of our services:

BOUNDING BOX BACKGROUND DATA ANNOTATION

2D BOUNDING BOXES

Bounding box improves machine learning algorithms’ ability to detect and classify the object that they’re required to look for. Our highly-trained Computer Vision teams have the best practices for annotating with bounding boxes for faster and more accurate labeled objects.

This technique has various applications, but one of its popular uses is for detecting different object statuses or patterns. Some of the bounding box common use cases are insurance claims for car accidents, object detection for self-driving cars, detecting the progress of viruses and bacteria for the healthcare industry, and image labeling for e-commerce and retail.

Polygon

POLYGONS

Another type of image annotation is polygonal segmentation, and the theory behind it is just an extension of the theory behind bounding boxes.

For labeling objects with irregular shapes, polygon annotation guarantees a pixel-perfect annotation with no irrelevant objects ruining the quality of the annotated area.

Polygon is applied to detect objects with complex shapes for high accuracy data, such as human poses in sports analytics, architectures & buildings, detect objects for drone and satellite imagery, and other objects of your interest.

Keypoints

KEYPOINT OR LANDMARK ANNOTATION

Key point annotation is a technique that allows annotators to mark the main parts or “key” locations on an image using different dots in annotation tools. This helps machines differentiate between similar objects.

This annotation type is especially useful for tracking variations between objects that typically appear with the same structure, such as human figures, facial recognition, and buildings.

To use the landmarks technique, the annotators must label key points at specified locations. These labels are commonly used to annotate anatomical elements for facial and emotion detection.

3D CUBOIDS

3D CUBOIDS

With 3D cuboid annotation, annotators can measure the depth of specific objects like vehicles (motorbikes, cars, trucks, etc.) with precise dimensions and attributes. Cuboid “teaches” machine learning algorithms to visualize 3D simulated versions of 2D images captured by cameras.

This technique of annotating enables AI machines to better recognize furniture and infrastructures in construction. Automobile and warehouse industries apply cuboid techniques to help their robots become familiar with objects in reality.

TEXT ANNOTATION BACKGROUND

SEMANTIC SEGMENTATION

This technique annotates every pixel in an image with information and divides it into segments for recognition by a computer vision algorithm. Semantic Segmentation associates each pixel with a labeled image like a car, road, or pedestrian. It is used in industries such as automotive, healthcare, agriculture, and retail to demonstrate how visual systems work and their limitations.

With semantic segmentation, people can enhance algorithmic efficiency and boost the accuracy of labeled data.

2D BOUNDING BOXES

Bounding boxes

Bounding box improves machine learning algorithms’ ability to detect and classify the object that they’re required to look for. Our highly-trained Computer Vision teams have the best practices for annotating with bounding boxes for faster and more accurate labeled objects.

This technique has various applications, but one of its popular uses is for detecting different object statuses or patterns. Some of the bounding box common use cases are insurance claims for car accidents, object detection for self-driving cars, detecting the progress of viruses and bacteria for the healthcare industry, and image labeling for e-commerce and retail.

POLYGONS

Polygon

Another type of image annotation is polygonal segmentation, and the theory behind it is just an extension of the theory behind bounding boxes.

For labeling objects with irregular shapes, polygon annotation guarantees a pixel-perfect annotation with no irrelevant objects ruining the quality of the annotated area.

Polygon is applied to detect objects with complex shapes for high accuracy data, such as human poses in sports analytics, architectures & buildings, detect objects for drone and satellite imagery, and other objects of your interest.

KEYPOINT OR LAND MARK ANNOTATION

Keypoints

Key point annotation is a technique that allows annotators to mark the main parts or “key” locations on an image using different dots in annotation tools. This helps machines differentiate between similar objects.

This annotation type is especially useful for tracking variations between objects that typically appear with the same structure, such as human figures, facial recognition, and buildings.

To use the landmarks technique, the annotators must label key points at specified locations. These labels are commonly used to annotate anatomical elements for facial and emotion detection.

3D CUBOIDS

3D CUBOIDS

With 3D cuboid annotation, annotators can measure the depth of specific objects like vehicles (motorbikes, cars, trucks, etc.) with precise dimensions and attributes. Cuboid “teaches” machine learning algorithms to visualize 3D simulated versions of 2D images captured by cameras.

This technique of annotating enables AI machines to better recognize furniture and infrastructures in construction. Automobile and warehouse industries apply cuboid techniques to help their robots become familiar with objects in reality.

SEMANTIC SEGMENTATION

Segmentation Annotation

This technique annotates every pixel in an image with information and divides it into segments for recognition by a computer vision algorithm. Semantic Segmentation associates each pixel with a labeled image like a car, road, or pedestrian. It is used in industries such as automotive, healthcare, agriculture, and retail to demonstrate how visual systems work and their limitations.

With semantic segmentation, people can enhance algorithmic efficiency and boost the accuracy of labeled data.

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Managers from many kinds of businesses turn to DIGI-TEXX to enhance their client’s digital experiences.

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Our Deployment Models

Chart Business Model Data Annotation and Labeling

Our annotator supervisor works directly with your data science team, fostering collaboration and guaranteeing the highest standards of accuracy and precision in the annotated data. We believe in a comprehensive project management process that encompasses effective communication, well-defined timelines, thorough documentation, and the scalability of our delivery capacity. Moreover, our experienced team of experts will diligently analyze your project requirements and propose tailored enhancements to optimize the performance and sustainability of your AI model.

frequently asked questions

Our data labeling consultancy utilizes customer-centric design to facilitate efficient business transformation.

Image annotation for machine learning is the process of labeling or classifying an image using text, drawing tools, or both to show the data features you want your model to recognize on its own.

Image annotation is sometimes called data labeling, tagging, transcribing, or processing.

Images and multi-frame images, such as videos, can be annotated for machine learning. Videos can be annotated continuously as a stream or frame by frame.

The most common types of data used with image annotation are:

  • 2D images and video (multi-frame), including data from cameras or other imaging technology, such as an SLR (single lens reflex) camera or an optical microscope.
  • 3D images and video (multi-frame), including data from cameras or other imaging technology, such as electron, ion, or scanning probe microscopes.

Image annotation involves the use of one or more of these techniques: bounding boxes, landmarking, masking, polygons, polylines, tracking, or transcription. Your annotation tool will support these techniques. Annotation tools provide feature sets with various capabilities that can be used by your workforce to annotate images or videos.

To scale your process, we have image annotation solutions that can provide crowdsourced or managed-team solutions.

How does our image annotation methodology work?

We specialize in developing customized image annotation services that leverage the latest technologies to help you efficiently achieve your business goals. Our team of experts can assist your organization in exploring and implementing new possibilities while minimizing disruption and cost.

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Industries we cater to

We assist businesses in improving their performance by utilizing advanced database fleet diagnostics and tuning methods to troubleshoot issues and optimize performance.

E-commerce

We assist e-commerce companies in enhancing their product categorization, customer experience, marketing, inventory management, and fraud detection by providing accurately labeled data for their AI and ML models.

Construction

In the construction industry, we enhance our clients’ AI systems to forecast potential dangers, monitor construction progress, and reduce the number of wasted materials.

Accounting

At DIGI-TEXX, our image annotation can help accounting businesses improve their data quality, accuracy, security, and efficiency.

Retail

DIGI-TEXX helps in labeling and categorizing products accurately, enabling retailers to offer personalized and relevant recommendations to customers

Automobile

Our annotated datasets enable machine learning algorithms to recognize and interpret various objects and scenarios on the road, such as traffic signs, pedestrians, and other vehicles. Accurate annotations facilitate the development of safe and reliable autonomous vehicles.

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What makes us a suitable image annotation service provider for you?

As a leading image annotation outsourcing company and are committed to providing our expertise, technology, and infrastructure to support businesses across the world. We thoroughly understand your concern and provide reliable support services on your behalf. See below:

Flexible pricing model

We offer flexible pricing models based on your requirements. You can select the model that best fits your business and yearly budgeting.

Data accuracy

At DIGI-TEXX, we understand that data accuracy is the first and critical component/standard of the data quality framework. We combine AI technologies and our specialists to ensure the highest accuracy rate.

Data security

Confidential information will remain secure and be restricted from outside exposure with a reliable information security management system (ISMS) based on the ISO 27001 standard with GDPR compliance.

Experienced and on-demand workforce

We have more than 20 years of experience building a team specialized in scalable projects with a quick turnaround time to meet different clients’ needs.

Cost Optimization

Outsourcing transforms fixed costs into variable costs and allows you to prevent large expenditures for business in the early stages and long-term run.

Round-the-clock support

Our dedicated project management team ensures your concerns are in control 24/7.

Scalability and flexibility

Our service can adapt quickly to fluctuating volumes without compromising productivity and processing quality.

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