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SICK 2D Machine Vision, SICK AppSpace SensorApps
Price
$1,263.00 CAD
Stock
22 In Stock
The Intelligent Inspection SensorApp from SICK ensures easy object classification that is not possible with traditional rule-based machine vision. The SensorApp is powered by deep learning technology and available as a licensed option when ordering InspectorP6xx 2D vision sensors from SICK.
The example-based approach and easy-to-use user interface makes it quick to learn and paves the way for simplified solution development.
The user can easily collect training data to be used in the neural network training, and deploy the trained network directly on the sensor without the need for any extra equipment.
In addition, traditional rule-based machine vision software tools are included.
At a glance
- Classification of objects powered by deep learning technology
- Runs on InspectorP6xx 2D vision sensors
- Easy-to-use user interface in web browser
- Traditional rule-based machine vision software tools included
- Quick customization with SICK Nova Tools
- Simplified solution development in complex machine vision applications not possible with traditional rule-based machine vision
- Example-based approach and easy-to-use user interface that makes it quick to learn without the need for a vision expert
- Low cost of total ownership as deep learning network runs directly on the camera without additional hardware
- Reliable inspection to reduce waste, avoid production downtime, and improve productivity
- The SICK Nova Tools plug-in support with source code access offers customization capabilities to all SICK AppSpace developers
Specifications
Brand
Task
- Classification
- Quality Inspection
- Presence Inspection
- Measuring, 2D
Technology
- 2D Snapshot
- Image Analysis
- Deep Learning
Supported Product
- InspectorP61x
- InspectorP62x
- InspectorP63x
- InspectorP64x
- InspectorP65x
Screen Resolution
- Minimum 1,366 px x 768 px
Supported Browser
- Google Chrome (Version 49 or Higher)
- Naturally grown objects
- Objects with complex or irregular shapes
