Annotate for Smarter AI models
Are you looking to streamline your AI training process and achieve more accurate results?
Look no further than OCLAVI.
Our tool is designed to provide accurate and consistent image annotations, ensuring that your AI models are trained on high-quality data.
High-quality training data
Build world-class computer vision models with our exceptional image labeling solution.
High-quality data for image annotation is essential for training accurate and effective AI models as they directly impact the performance of the models. High-quality data can be achieved through various types of annotations.
Efficient AI development
Reduce the time and cost of manual annotation, enabling AI developers to focus on other aspects of model development.
Automated annotation tools can annotate large datasets quickly and accurately, saving time and reducing costs.
Image annotation is essential for a range of applications, including object recognition, facial recognition, medical imaging, self-driving cars so on and so forth.
Accurate annotations are necessary to ensure the safety and reliability of these applications.
Cases of deployment
Some examples to spark your imagination
Image annotation is crucial in harnessing the full potential of drone technology in the industry.
Precise labelling of objects and features in images and videos, image annotation tools help to unlock valuable insights and information which enables more informed decision-making in various applications.
This tool helps robots perceive and understand their environment better.
Through image annotation, robots can identify and classify objects, navigate their surroundings, and perform tasks autonomously.
By labeling features such as objects, surfaces, and obstacles in robot vision images, image annotation tools enable robots to accurately interpret their environment and make informed decisions
Autonomous Vehicle (AVs)
Image annotation plays a pivotal role in the development and deployment of autonomous vehicles, enabling them to perceive and navigate their environment safely and efficiently.
It enables AVs to identify and classify objects, such as pedestrians, type of vehicles, traffic and road signs, driving conditions in real-time more accurately