Top 5 Thrilling Image Annotation Cases

At Mindy Support, our team members understand the importance of image annotation in training computer vision algorithms. This is why we place a great deal of importance on quality and attention to detail to make sure all of the annotation work is done correctly. We assembled the top five image annotation customer cases our team members enjoyed working on. 

Detecting Damage Caused to Cars

Our client was working on an AI solution that could help drivers detect damage caused to cars but also provided the clients with additional services such as submitting a claim, appraising the damage, predicting the type of repair required, and a lot of other useful information. When actualizing this project, it was important that we maintain high-quality standards since any deviation could change the nature of the damage. We needed to annotate 36,000 images with 2D bounding boxes to detect all of the various types of car damage after accidents (scratches, crashes, broken parts, etc.) and classify them by the required taxonomy. 

We assembled a team that could annotate all of the needed images with the needed quality level. In fact, we were able to achieve a quality score of 98% quality score achieved with minimal calibration on the annotation approach by the client. Learn more about our work with this project in our case study. 

Helping To Develop Cutting-Edge ADAS Technology 

ADAS technology plays a critical role in driver safety, and our client was working on a system that could detect, localize and categorize all landmarks and pavement defects (pots, cracks, water, etc.) on the road to make existing cars safer and facilitate the development of autonomous vehicles. In order to increase the accuracy of the model, they needed to annotate a dataset of 0,000 images containing various landmarks and pavement defects, such as pots, cracks, water, etc., on the road. 

Since Mindy Support’s team members have plenty of experience with image annotation, they had no trouble annotating the entire dataset in 1.5 months. The speed did not sacrifice the quality since a quality score of 95%+ was achieved. Check out how we were able to achieve these outstanding results in our case study.

Playing a Crucial Role in Training Autonomous Vehicles

Autonomous vehicle technology is advancing every year, and Mindy Support is happy to play a part in helping clients develop the self-driving cars of tomorrow. In this project, the client needed some quality assurance (QA) work to be done on the services provided by another vendor. For this project, we needed to annotate images of driving conditions with many different attributes that dynamically change depending on the situation on the road, the landscape, car position, and other parameters.However, we performed this task so well that the client decided to transfer the entire data annotation project over to us. 

As a result, we ended up performing both QA and data annotation work for the client working with large amounts of 2D image sequences with the instance segmentation method. Thanks to our extensive expertise, we were able to increase the quality score from 92% to 98%. Want to learn more about how we achieved such spectacular results? Get all of the details in our case study. 

Facilitating Recycling Efforts 

The environmental issues facing the planet are huge, and we were happy to play a part in helping our client improve recycling efforts. They were working on an AI solution that could detect what kind of waste is being disposed of in the containers of businesses (their customers). In addition to this, the AI system needed to track how well the companies’ recycling efforts are going and make sure that the waste sorting rules are kept to ensure safety.

The client needed to annotate a training dataset with a polygon, and the relative class had to be applied. Image segmentation requires a high level of training and attention to detail on behalf of the data labeling team. In this project, we were not only able to meet but also exceed the client’s expectations. To be more specific, we achieved a quality score of 98%, which exceeded the client’s expectations by +3%. Our case study has more detailed information about how we achieved these extraordinary results. 

Monitoring the Pace of Construction 

There are many uses of AI in construction, and monitoring the course of how the project is developing is one of the biggest uses. Our client developed a product that monitors the progress of construction over time. To improve the accuracy of the product, they needed to annotate images of construction sites from various years.

Our team was skilled at using all kinds of data annotation tools, and we had no issues completing the work using QGIS at the request of the client. The output needed to be in GeoJSON format, which is used for encoding a variety of geographic data structures. We completed more than 1,000 hours of quality annotation work to help keep the client’s project on schedule. Check out our case study to learn more about the work on this project. 

Trust Mindy Support With All of Your Data Annotation Needs

Mindy Support is a global data annotation provider, trusted partner by Fortune 500 and GAFAM companies. With more than 10  years of experience under our belt and offices and representatives in Cyprus, Poland, Romania, The Netherlands, India, UAE, and Ukraine, Mindy Support’s team now stands strong with 2000+ professionals helping companies with their most advanced data annotation challenges.