Enterprises need a continuous flow of accurately labeled datasets to train computer vision models. Generating such a dataset requires proper tools, experience, strict adherence to quality parameters, and compliance with data privacy laws. However, companies often fail to establish and manage such an infrastructure with the right technologies and resources within their budget.
At SunTec Data, we help you quickly build a reliable data pipeline through precise image annotation services. We meet all short and long-term data volume requirements through a dedicated team, advanced tools, and the latest technologies. To guarantee accuracy and data security, we employ multi-layer QA and double-pass annotation methodologies. Regardless of the project's complexity, we align our teams to deliver within deadlines.
Here's what we offer when you outsource 2D and 3D image annotation services to our team.
Bounding box annotation is a cost-efficient way to teach computer vision models where objects are located within an image, commonly used for detecting lane boundaries, stop signs, and pedestrians. We annotate images using rectangular boxes around target objects. This leads to accurate object detection for 2D images and helps extract training data according to the nature of your AI/ML models.
In 3D cuboid annotation, a cube is drawn around an object to read its height, width, and depth. Our experts use the cuboid annotation technique to classify 3D objects in indoor and outdoor environments, like images of moving traffic, pedestrians, and road signs.
This approach is useful for annotating target objects by plotting points on each vertex. Polygon annotation marks the exact borders of the object, regardless of its shape or size. We commonly use this technique to label road sign boards, human postures, and movements, and for mapping and analysis purposes.
Using semantic segmentation, we break an image into different segments through pixel-level classification and annotate them with information. For instance, in an image of moving traffic, we use semantic segmentation to identify classes like vehicles, humans, animals, road signs, etc.
LiDAR data comprises thousands of measurement points in the entire area. Through LiDAR annotation, we convert complex 3D data into training datasets for AI/ML models.
Also known as landmark annotation, we use this approach to annotate facial expressions, skeletal features, and movements of a human body. The process helps to generate optical flow representations of ground data and annotate key points around the chosen area in a 2D image/video frame.
Our experts draw precise lines to recognize different paths, orientations, and surfaces. The resultant dataset helps train a computer vision model to analyze terrain and structures by highlighting linear structures within image data.
The client (An AI-based solutions development company) needed a labeled dataset for its face recognition algorithm. They provided a database of facial images, including obscured and poorly visible photos. We omitted unusable photos from the dataset and tagged and categorized the rest as per client instructions. We delivered 1000+ annotated images within two weeks with 99% accuracy.
Our guarantee of precision and quality in annotated datasets are backed by a dedicated team of data annotators and image labeling experts with rich experience and background in this domain. Additionally, we also offer a customizable workflow so that the final result can be aligned with your expectations and the scope for errors is minimized.
We decided to go with SunTec Data because of their reputation in providing accurate, reliable annotation and training datasets. It is a pleasure to be working with this team. They are responsive, proactive, and extremely knowledgeable about their services.David Smith, Entrepreneur, USA
Using our data annotation and labeling services, you can achieve a wide range of use cases for an AI/ML model. Here are a few of them where our team can support you.
We create high-quality datasets to help self-driving cars better understand their environment by annotating their surroundings with bounding boxes.
Our medical data annotation experts annotate scanned medical images to help ML models in several purposes, like automated diagnosis, surgery assistance, and sample scanning.
We provide 2D and 3D image annotation for your trained model to identify the health of crops. These insights help reduce the cost of crop management.
Our image annotation services can help you develop best-in-class inventory management tools, chatbots, and product recommendation engines, among other AI-based eCommerce applications.
With accurate training datasets created by labeling barcodes, QR codes, and other logistics and supply chain data, we can help you improve process efficiency and accuracy.
We annotate drone-captured images to provide accurate datasets for object detection, road mapping, terrain detection, and such other applications.
Leverage our experience of 20+ years as an outsourcing support company. We tailor our workflow to meet your needs while keeping your data secure from leaks and other vulnerabilities. Our team ensures the best possible outcome in terms of quality, speed, and budget. Reach out to us at firstname.lastname@example.org to discuss your requirements or get a free sample.