How To Get Training Data for Self-Driving Cars or Autonomous Vehicles?

Autonomous driving systems are used to develop the self-driving cars that can operate itself without human instructions. It seems an amazing to see if a vehicle moves automatically while following the traffic rules and regulations for safe driving.
But developing such autonomous driving systems is not possible until and unless the model learns everything is visible on the roads. Actually, there are multiple types of objects also addressable on streets and automated cars must detect that from certain distance to take next action like slowing down the speed, barking the vehicle or taking a turn.
So, question posted right here from where autonomous driving systems get their training data to develop a full-functional model for such projects. 
 

Types of Training Data Required for Autonomous Driving
Training data consists mainly the visual objects for computer vision to recognize various types of things on the road. And for computer vision, images in various formats are used to train the machine that can store such data into its memory for future reference.

3D point annotation helps to create the training data for LiDARs used in self-driving. Similarly, polyline annotation is used to create the training data for lane detection while polygons based annotation is used to detect the road marking by the vehicles.

Likewise, Bounding Box, 3D Cuboid and Semantic Segmentation are the types of annotations helps to generate the visual training data that helps to recognize and classify the objects like other vehicles with more precise dimensions.

Acquiring such data at huge level is difficult task, as there are varied types objects like street lights, traffic signals, humans, buildings, barricades, street signs, other vehicles, street lanes and visible while on the roads need to be recognizable to computer vision.
How to Get Training Data for Autonomous Driving?
Such data is created by collecting the camera generated images and label or annotate them to highlight the object that a computer can recognize and train the machine. And each image containing the different types of objects are annotated using the certain annotation technique making the object recognizable in different scenario. 
And there are many companies providing the training data for autonomous vehicles to train the autonomous driving model. And AI developers can obtain such data from these companies to meet their requirements. The training data for self-driving cars are available in different annotation formats for different types of objects detection.
Anolytics is one the leading data annotation companies, providing the high-quality image annotation service for autonomous vehicle driving, healthcare, retail and robotics and various other fields with best accuracy. It can produce and supply huge quantity of datasets for machine learning, deep learning and AI model training available at very affordable cost.

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