The In-Sight D900 puts the power of power of Deep Learning at your fingertips
The In-Sight D900 is a smart camera powered by In-Sight ViDi software designed specifically to run deep learning applications. This embedded solution helps factory automation customers easily solve challenging industrial OCR, assembly verification, and random defect detection applications anywhere on the line that have gone uninspected because they are often too difficult to program with traditional, rule-based machine vision tools.
In-Sight ViDi applications are deployed on the In-Sight D900 smart camera without the need for a PC, making deep learning technology accessible to non-programmers. It uses the familiar and easy-to-use In-Sight spreadsheet platform which simplifies application development and factory integration.
Decodes challenging OCR applications in minutes
The In-Sight D900 deciphers badly deformed, skewed, and poorly etched codes using optical character recognition (OCR). The In-Sight ViDi Read tool 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.
Performs fast and accurate assembly verification
The In-Sight D900 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. The In-Sight ViDi Check tool 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.
Analyzes complex defect detection tasks
The In-Sight ViDi Detect Tool learns from images of good parts in order to identify defective parts. ViDi Detect is ideal for finding anomalies on complex parts and surfaces, even in situations where defects can be unpredictable in their appearance.
In-Sight spreadsheet guides application development
In-Sight ViDi takes advantage of the intuitive In-Sight spreadsheet interface to quickly set up and run deep learning applications without programming. The In-Sight spreadsheet simplifies application development and streamlines factory integration with a full I/O and communications function set. It also enables the ability to combine traditional Cognex rules-based vision tools (like PatMax Redline) and deep learning tools in the same project, leading to quicker deployments and faster cycle times. Since In-Sight ViDi requires vastly smaller image sets and shorter training and validation periods, deep learning applications are quick and easy to set up, teach, and deploy.
Deployed on powerful, customizable vision systems
In-Sight ViDi applications on the In-Sight D900 can be deployed without a PC. This highly-modular, IP67-rated deep learning vision system includes field-changeable lighting, lenses, filters, and covers that can be customized to match your exact application requirements. It also includes an embedded inference engine that is specifically designed to solve complex deep learning applications at production line speeds.
The In-Sight D900 vision system offers mobile, platform independent visualization for accessing HMIs (human machine interfaces) through In-Sight ViDi software. A simple point-and-click interface allows customers to build highly interactive, web-based HMIs remotely accessible via a web browser over the network.
Combining power, accessibility and ease of use, the In-Sight D900 inspects the previously uninspectable, ensuring:
- Quicker deployments and a faster time to value
- Consistent and accurate inspection results at scale
- Better quality products by catching more potential issues
For more information, visit www.cognex.com/d900 or call +44 121 296 5163
Cognex UK Ltd
Suite 1A, 1. Floor, Partis House, Davy Avenue
Knowlhill, Milton Keynes
Phone : +44-121-296-5163
Email : email@example.com