Overeasy Introduces IRIS: An AI Agent that Automatically Labels Your Visual Data with Prompting to Help Develop Computer Vision Models Faster

Over 300,000 photos in earlier massive datasets like COCO have over 3 million annotations. Models may now be trained on datasets with a 1000x increase in scale, such as FLD-5B, which contains over 126 million photos annotated with five billion+ words. Annotation speed can be increased by a factor of 100 with synthetic annotation pipelines, all while keeping label quality the same. Leading models in the field, such as LLama 3.1 and SAM2, have demonstrated the importance of robust synthetic data pipelines for achieving cutting-edge performance.

Meet Overeasy, a cool startup that is introducing IRIS. IRIS is an AI tool that can simplify the tagging of visual data. Data annotation is much easier and faster thanks to this tool, which can interpret and react to picture-related commands.

How does IRIS work?

Although IRIS’s architecture is kept under wraps, its capabilities allow us to deduce its general operating principle.

Understanding the Prompt: IRIS analyzes each prompt to determine its unique requirements. For example, when instructed to “Identify all animals in the image,” IRIS will prioritize detecting and categorizing things that resemble animals.

Next, IRIS uses its training data to examine the input image and identify possible items, scenes, or actions.

Bounding Box and Label Generation: IRIS uses its knowledge of the image and the prompt to make bounding boxes and labels for the things it finds.

Quick-annotate many images: Based on your application, IRIS will automatically choose the optimal zero-shot models.

Benchmarks

A zero-shot object detection model that Overseas has been developing is breaking new ground. Regarding COCO and LVIS, IRIS’ zero-shot object detection is top-notch.

In Conclusion

Custom end-to-end pipelines for tasks like Bounding Box Detection, Classification, and Segmentation can be easily created with Overeasy by chaining zero-shot vision models. Big training datasets don’t have to be collected or annotated to accomplish all of this. Combining pre-trained zero-shot models to construct strong custom computer vision solutions is simple using Overeasy. Also, launched by Overeasy, IRIS is an exciting artificial intelligence agent with game-changing potential in computer vision. It speeds up model development, improves data quality, and decreases expenses by automating the time-consuming data labeling process. IRIS is an AI agent that can label visual data with prompting. It can also generate bounding boxes around objects in images.