Deep Learning Bundle

Convolutional Neural Network-based inspection libraries

At a glance
  • Includes EasyClassify and EasySegment
  • Supports data augmentation and masks
  • Compatible with CPU and GPU processing
  • Includes the free Deep Learning Studio application for dataset creation, training and evaluation



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What Is Deep Learning ?

Neural Networks are computing systems inspired by the biological neural networks that constitute the human brain. Convolutional Neural Networks (CNN) are a class of deep, feed-forward artificial neural networks, most commonly applied to analyzing images. Deep Learning uses large CNNs to solve complex problems difficult or impossible to solve with so-called conventional computer vision algorithms. Deep Learning algorithms may be easier to use as they typically learn by example. They do not require the user to figure out how to classify or inspect parts. Instead, in an initial training phase, they learn just by being shown many images of the parts to be inspected. After successful training, they can be used to classify parts, or detect and segment defects.


EasySegment Description
EasySegment Description

EasySegment is the segmentation tool of Deep Learning Bundle. EasySegment performs defect detection and segmentation. It identifies parts that contain defects, and precisely pinpoints where they are in the image. When using its unsupervised mode, EasySegment works by learning a model of what is a “good” sample (i.e. a sample without any defect). This is done by training it only with images of “good” samples. Then, the tool can be used to classify new images as good or defective and segment the defects from these images. By training only with images of good samples, the unsupervised mode of EasySegment is able to perform inspection even when the type of defect is not known beforehand or when defective samples are not readily available.


Developed with the support of the DG06 Technology Development Department
Developed with the support of the DG06 Technology Development Department


Why Choose Open eVision’s Deep Learning Bundle?
Why Choose Open eVision’s Deep Learning Bundle?

  • Deep Learning Bundle has been tailored, parametrized and optimized for analyzing images, particularly for machine vision applications.
  • Deep Learning Bundle has a simple API and the user can benefit from the power of deep learning technologies with only a few lines of code.
  • Try before you buy: Deep Learning Bundle comes with the free Deep Learning Studio training and evaluation application.
EasyClassify and EasySegment cannot be purchased separately. They are only available as part of the Deep Learning Bundle.
Download and evaluate Deep Learning Bundle using Deep Learning Studio today, and feel free to call Euresys’ support should you have any question.


<a target="_blank" href="https://www.euresys.com/Products/Machine-Vision-Software/Open-eVision-Studio/Open-eVision-Studio"  >Deep Learning Studio</a>
Deep Learning Studio

Open eVision includes the free Deep Learning Studio application. This application assists the user during the creation of the dataset as well as the training and testing of the deep learning tool.


EasyClassify Description
EasyClassify Description

EasyClassify is the classification tool of Deep Learning Bundle. EasyClassify requires the user to label training images, that is to tell which ones are good and which ones are bad, or which ones belong to which class. After this learning/training process, the EasyClassify library is able to classify images. For any given image, it returns a list of probabilities, showing the likelihood that the image belongs to each of the classes it has been taught. For example, if the process requires setting apart bad parts from good ones, EasyClassify returns whether each part is good or bad, and with what probability.


Performance
Performance

Deep Learning generally requires significant amounts of processing power, especially during the learning phase. Deep Learning Bundle supports standard CPUs and automatically detects Nvidia CUDA-compatible GPUs in the PC. Using a single GPU typically accelerates the learning and the processing phases by a factor of 100.


Software
Host PC Operating System
  • Windows 10 (64-bits)
  • Windows 8 (64-bits)
  • Windows 7 (64-bits)
APIs
  • Supported Integrated Development Environments and Programming Languages:
    • Microsoft Visual Studio 2008® SP1 (C++, C#, VB .NET, C++/CLI)
    • Microsoft Visual Studio 2010® (C++, C#, VB .NET, C++/CLI)
    • Microsoft Visual Studio 2012® (C++, C#, VB .NET, C++/CLI)
    • Microsoft Visual Studio 2013® (C++, C#, VB .NET, C++/CLI)
    • Microsoft Visual Studio 2015® (C++, C#, VB .NET, C++/CLI)
    • Microsoft Visual Studio 2017® (C++, C#, VB .NET, C++/CLI)
Ordering Information
Product code - Description
Optional accessories
Presence Check

Presence / Absence check

EasyImage gray-scale analysis functions are used for simple presence/absence checks
Surface

Surface analysis

EasyImage is used to reveal the surface defects, and the blob analysis functions of EasyObject is able to segment and measure them.
Code Verification

Code quality verification for label printing machines