Polygon Annotation Services

Make irregular objects in images or videos recognizable for computer vision

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Applications of Polygon Annotation

This is an ideal technique for handling complex shapes and is used in object detection, instance segmentation, and other applications having complicated shapes like medical imaging or autonomous vehicles.

Detecting Irregular Shapes for Computer Vision

Detecting Irregular Shapes for Computer Vision

This involves detecting irregular shaped objects in images and videos as training data for AI models. It is ideal in object detection including road sign boards, logos, and diverse postures of humans in sports analytics or other objects of interest with best accuracy.

Polygon Annotation for Asymmetrical Semantic Segmentation

Polygon Annotation for Asymmetrical Semantic Segmentation

This helps in improving the accuracy level of models and is applicable in autonomous vehicles and robotics. It permits computer vision to comprehend real-world situations and is a more precise labeling technique for avoiding white spaces and extra noise.

Localizing Objects for Drone and Satellite Imagery

Localizing Objects for Drone and Satellite Imagery

Use the polygon annotation tool to get a better approximate idea about the contour of objects via distant cameras using drones or satellite. This assists in precise localization of objects like rooftops, pools, and trees..

Tools for Polygon Annotation

Polygon Annotation can be done both manually and automatically. Manual method involves a human annotator drawing the polygon by hand whereas the automated method involves using algorithms for automatically generating polygons as per certain criteria.

#1

Using brush alike tools

The annotator uses a brush-like tool here for creating a polygon by clicking around the perimeter of the object. It is quite a quick and easy method, but prone to errors in the event the annotator is negligent.

#2

Using point-based tools

The annotator places individual points around the perimeter of the object and the algorithm connects the points to create the polygon. This is a more accurate method than brush-like, however it’s time-consuming in cases where the object has a complicated shape.

#3

Algorithmic tools

This involves the automatic detection of edges of the object and creating a polygon around it. The algorithms can be trained on a dataset of annotated images for improving their precision and accuracy.

Use Cases of Polygon Annotation

Retail

Retail

Used for training algorithms to identify and classify products in online catalogs and storefront images. This enables retailers to instantly organize their products and make them searchable for improving the customer experience and boosting sales.

Medical & Drug Development

Medical & Drug Development

Used for training algorithms for detecting and diagnosing diseases in medical images. For instance, it can be used by a doctor for outlining a tumor in a CT scan. This will thereby assist in training an algorithm to detect tumors in future scans.

Automotive

Automotive

Used for training algorithms for detecting and classifying objects in images and videos from self-driving cars. It permits the algorithms to comprehend its surroundings and take decisions regarding safe navigation.

Drones and Satellites

Drones and Satellites

Used for training algorithms for identifying and classifying various types of land use like forests, agriculture, and urban areas. The information thus obtained can be utilized for a range of purposes which include monitoring of environmental changes and planning land use.

Security & Surveillance

Security & Surveillance

Used for training algorithms in detecting and classifying objects in surveillance footage. It is used to instantly alert security personnel of possible threats like intruders or suspicious items.

Robotics

Robotics

Used for training algorithms for robots to comprehend and interact with its environment. For instance, robots can use this to spot and pick up particular objects including bottles or boxes.

Frequently Asked Questions

Polygon annotation is a technique used in data annotation for labeling and identifying particular regions of an image or video. It requires drawing some line segments around the object or area to create an enclosure known as a polygon. The shape is then appropriately labeled.

Polygon annotation requires a specialized software or tools which permit one to draw the polygons and label them as per appropriate class. Both free and paid options are available in the market. Common examples are Labelbox, VGG Image Annotator, Labellmg, etc. After the polygons are annotated and labeled, this structured dataset can be used for training machine learning models for tasks including object detection or semantic segmentation.

In certain scenarios, drawing a polygon may be quite time-consuming in comparison to bounding boxes. It is also not the most suited method for particular kinds of objects or features. For instance, it might not be an effective approach for annotating objects having lots of small or closely spaced details or objects with smooth or curved surfaces.

Why should you outsource to Anolytics?

You can trust us in offering quality text annotation work because we offer:

Quality With Accuracy
Quality With Accuracy

Get the best-in-class quality services with highest accuracy level delivering an excellence in image annotation through multiple stages of auditing and reviewing of labeled data.

Security With Privacy
Security With Privacy

We are certified with SOC 2 TYPE 1 Company for maintaining the high standards of data security with privacy while working with our clients to ensure their confidentiality.

Fully Scalable Service
Fully Scalable Service

Working with hundreds of workforce to annotate pictures as per the demand providing a completely scalable solution with turnaround time to meet the different client’ needs.

Cost-effective Pricing
Cost-effective Pricing

Image annotation outsourcing to us means our clients get a cost-effective data labeling service helping them to minimize the cost of their project with best efficiency.

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