Even when raw data is in video format, teams still work with images due to the complexity of handling videos at scale. First, around 90% of the companies work with image data (vs. In order to understand challenges facing teams tasked with building CV applications and products, we met with leaders at over 120 companies. In contrast, we believe most tools for storing, analyzing, navigating, and managing visual data still lack features essential for computer vision projects.
Tools for building models now include high-level libraries (TensorFlow, PyTorch), model hubs ( Model Zoo, TensorFlow Hub ), and low-code tools ( Matroid ).
We’ve spent the last decade building AI models for computer vision applications in manufacturing, automotive and consumer applications. While many companies are collecting visual data, much of that data has yet to be properly utilized or analyzed due to a lack of access to tools and a skills gap. Nevertheless, computer vision applications are still in their infancy. The rise of visual sensors and the availability of AI models that can unlock visual data, have led to an explosion in demand for CV talent and applications. Globally, there are over 250,000 people in the private sector who list computer vision skills or tools on their Linkedin profiles. Many novel use cases are emerging, for example autonomous vehicles, 3D reconstruction of homes from images, robots that perform many different tasks, etc. IntroductionĪ decade after deep learning systems first topped key computer vision ( CV ) benchmarks, computer vision applications and use cases can be found across all sectors. To start addressing this we analyzed numerous state-of-the-art computer vision datasets and found that common problems such as corrupted images, outliers, wrong labels, and duplicated images can reach a level of up to 46%!Īs a first step in solving this problem, we introduce a simple new tool that quickly and accurately detects ALL outliers and duplicates in your dataset.
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As a consequence, companies and researchers are losing product reliability, working hours, wasted storage, compute and most importantly, the ability to unlock the full potential of their data. Visual data management systems are lacking in all aspects: storage, quality (deduplication, anomaly detection), search, analytics and visualization.
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Introducing a new free tool for curating image datasets at scale.īy Amir Alush, Danny Bickson, Ben Lorica.
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