Combining artificial intelligence with the power of In-Sight
In-Sight ViDi is a powerful deep learning software platform designed specifically to solve applications that are too difficult, complex, or expensive for traditional machine vision systems. With an easy-to-use interface, In-Sight ViDi eliminates complex programming, making deep learning technology accessible for non-vision experts, and automates inline inspections previously only possible with human inspectors.
In-Sight ViDi Read Tool
The In-Sight ViDi Read tool deciphers badly deformed, skewed, and poorly etched codes using optical character recognition (OCR). It works right out of the box, dramatically reducing development time, thanks to the deep learning pretrained font library. Simply define the region of interest and set the character size. In situations where new characters are introduced, without vision expertise, this robust tool can be retrained to read application-specific codes that traditional OCR tools are not able to decode.
In-Sight ViDi Check Tool
The In-Sight ViDi Check tool uses artificial intelligence to reliably detect complex features and objects and verifies parts and kits are assembled correctly based on their location within a pre-defined layout. It can be trained to create an extensive library of components, which can be located in the image even if they appear at different angles or vary in size.
In-Sight ViDi Detect Tool
The In-Sight ViDi Detect tool is ideal for finding anomalies on complex parts and surfaces, even in situations where defects can be unpredictable in their appearance. It learns from images of good parts in order to identify defective parts. This allows the tool to detect a wide range of defects that do not need to be pre-defined at the time of training.
In-Sight ViDi Classify Tool
The ViDi Classify Tool uses deep learning to automatically identify and sort objects into classes. Within the same class of objects, this powerful classifier is capable of discerning visually similar, but different objects while tolerating natural variation. Classifying the type of defect enables better process control and allows developers to take corrective action to minimize scrap and reduce production of bad parts.