Polyline Annotation Services

Polyline Annotation is the most commonly used technique to label linear structures such as road lanes, crop lines, railway tracks, etc making them easily recognizable by the AI & ML Models

What Is Polyline annotation?

Polyline annotation is an annotation technique that involves drawing small lines along the object of interest. The technique is used to define linear structures in open-shaped objects such as roads, pipelines and rail tracks.

Polyline annotation technique marks road lanes for training machine learning models used in autonomous vehicles to detect and locate themselves within the road system. Polyline annotations are also used to train machine learning models used in automated trains to navigate and follow rail tracks without human intervention.

POLYLINE ANNOTATION FOR OBSTACLE & LANE DETECTION

Polyline Annotation For Obstacle & Lane detection

Typically road lanes are straight, making polyline annotation the most appropriate annotation technique. Lane detection is at the core of the operation of autonomous vehicle perception models. The models need to understand the different road markings on the road surface, such as lane diversions, bicycle and traffic flow. Using polyline image annotation, self-driving cars are trained for precise lane detection necessary to achieve trouble-free driving.

 

Autonomous cars need to learn to avoid obstacles on the road. These include avoiding veering into other lanes, such as stopping lanes where collisions with other vehicles could happen or going the road edges and hitting road barriers. Polyline annotations provide an easy way to mark the road easily without providing too much unnecessary detail and making the road surface marking recognizable to autonomous vehicles.

Training Robots For Warehouse Operations

Robots are increasingly used in different industries to carry out routine and specific tasks. As robots are more efficient, they allow companies to save time and money. However, the robots need to be trained to carry out their activities and where to place different objects.

Polyline annotation creates “target zones” within the warehouse where the robots should place different objects. That is achieved by drawing two or more polylines and training the robot only to put the objects inside the polyline markings.

TRAINING ROBOTS FOR WAREHOUSE OPERATIONS
POLYLINE ANNOTATION FOR AGRICULTURE INDUSTRY

Polyline Annotation For Agriculture Industry

 In agriculture, segmentation is the most commonly used annotation technique. However, in some instances, the level of detail provided in segmentation is unnecessary. For example, when the focus is to train AI to detect crop rows, the level of detail should be as minimal as possible.

Therefore line annotation, including splines, is used to annotate the crop rows. Besides, line annotation is also useful when the focus is to detect pests’ position on the crop’s stem. Here the legs of the pest are annotated using polylines to create datasets used to train computer vision models to detect such pests easily.

Your go-to solution for polygon annotation services

Annotation Box provides unrivalled image annotation services. Our team of experts have experience using different annotation tools. They can annotate your raw data with accurate polylines, line and spline annotations to create high-quality training datasets for training your self-driving car model. Give us your raw data, and our team of experts will deliver accurately annotated, high-quality training datasets to you at an affordable cost.

Global Presence

Global Presence

At Annotation Box, we work with experts worldwide to ensure a diversity of ideas and dynamism. Our globally distributed workforce ensures we can scale our services to respond to client needs effectively.

INDUSTRY-SPECIFIC SOLUTIONS

Industry-specific solutions

Regardless of your needs, our experts will provide high-quality datasets. Our image annotation services will provide accurate annotations for 2D images, while our video experts will annotate individual frames to deliver high-quality video training data for your self-driving car model.

99% high accuracy

95% Accuracy

Our annotation experts have experience with different labeling tools. They will create huge data sets, either video or image, for your project with a guaranteed 95% accuracy.

Why Choose Us?

At Annotation Box, we maintain the highest regard for clients’ goals and dreams in any project. We strive to deliver high-quality annotation services, offering technical help where necessary and providing a conducive team environment to achieve the project objectives.

500+ Employees-01

1000+

Trained Experts

9+ Accuracy-01

95%+

Accuracy

50+ happy clients-01

50+

Happy Clients

450+successful project-01

450+

Successful Projects

Learn How We Can Help You Train Your AI & ML Models With Our Professional Polyline Annotation Services

At Annotation Box, our polyline annotation service will help alleviate the problem of finding high-quality training data sets for your self-driving cars. Our professional team of annotation experts can deliver well-labeled datasets using thousands of polylines, splines and line annotations with guaranteed accuracy.

With our quality datasets, your machine-learning models for autonomous vehicles will efficiently and accurately detect and differentiate between various lanes and obstructions. Get in touch with our experts to learn how our services can help speed the process of training your machine-learning model for self-driving vehicles.

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.

DONT FALL BEHIND! Subscribe to latest research now

1 + 15 =