Data Annotation/Labeling — a real need for future of automotive Industry.

There are 7.8 billion people on our lovely earth and an estimated 1.4 billion cars on the road. By now, almost every 3rd person is well aware of what the automotive industry is going through!! You must be thinking it is fewer sales due to Corona Virus(Covid-19) gifted to us by China, or Electric Cars coming more and more. Still, it is not about this, and it is about every automotive industry racing towards fully Autonomous driving of their fleet.

This blog is not for beginners but for the advanced audience who understands Science & Technology and its implications in the automotive industry; however, I would like to shed light on autonomous driving basics.

The term Autonomous driving is usually used to describe self-driving vehicles or transport systems that move in a targeted manner without intervention by the human driver. In 2014, SAE International (Society of Automotive Engineers) defined the development stages for such a fully autonomous vehicle. The independent driving levels range from level 0 (no automation) to level 5 (driverless driving).

Now, let us get back to the original topic, and we see an overall picture of what is needed to make driver-less cars running over the speed of 120 KM/Hr. on the motorways. This job cannot be possible without Data annotation or, in the automotive term, Data Labeling. I will be using the time Data Labeling more in this article.

Data Annotation or Data Labeling:

Annotation is the process of labeling all objects in an image. The primary application of data labeling is the preparation of ground-truth data, which can be used to train machine-learning algorithms. Data labeling is a task mainly done by hundreds of thousands of humans sitting in Data Annotation factories mostly in South East Asia in Pakistan, India, and China.

Manual Data Labeling starts from Level 2 and ends till Level 4 of Automation, as you can see levels in the above picture. This is mainly done for OEMs (Original Equipment Manufacturer) or in R&D Labs of Tier-1, Tier-2, and Tier-3 suppliers of the automotive industry.

Data Annotation could be very difficult and hell a lot of expensive without a dependable partner who is easy to understand your needs, convert your data into meaningful data-annotation with no-compromise of quality.

What exactly do OEMs and Tier-1, 2, 3 supplier demands from Data-Labelers??

Creating machine learning and deep learning models for ground truth data such as object detection, image classification, and image segmentation is very important for Automotive Companies. Based on these models, they train the car to run without a driver.

A considerable amount of data is provided to data annotation partners, and this data is collected using several sensors, i.e., Radar and Lidar; these Companies require different types of precise data labeling; I will shortly discuss important and widely needed labeling type here,

Label with accuracy, just put two objects through any bounding box tool and draw rectangular boxes around them. The below image shows 2-d bounding boxes.

2. Semantic segmentation using Polygon

This is the higher category of labeling, and every image is assigned to a class. For example, the levels could be a car, bus, pedestrian, road, tree, bird, etc. This is done on pixel-level, where every pixel is annotated.

3. 3D Point Cloud Labeling

Point cloud annotation is the most needed labeling because Data Engineers or Machine Learning experts can then train their models based on this labeling. The ground-truth data is mainly gathered through the Lidar sensor, a widely used sensor in the automotive industry.

In this labeling, data is visualized with 3D objects and labeled accordingly. A 3D box is used for better object detection. High precision is required here.

Quality is the only reason you should be choosing the right annotation partner.

In our Data Annotation Factory at Ahdus Technology, we precisely annotate above all types and cover more scenarios like lane annotation, tags, and descriptions, key points, etc. The final quality control is run by our Data Engineers, considering the same methods of how a Machine Learning/Deep Learning Engineer will require the last prepared labeling image data.

Ahdus Technology is the first Data Science Company in Pakistan that has started Data-annotation for Automotive Industry, intending to provide precise and highest quality annotation services to its clients.

We could happily take your annotation work into our annotation factory and convert it to actionable annotation labeled images that your Data-Scientists could further use to make Level 5 automation in autonomous driving.

Apart from Data Annotation services, we are developing around Data Science, mainly machine learning, deep learning, and complex software development, while working under an agile and MVP mindset!

Originally published at https://ahdustechnology.com.

Dawood is a tech guy, having background in Computer Science and perusing his career in the field of IT and while working at AHDUS Technology as a Web Developer.