Deep Learning classification library
© EURESYS S.A. - Subject to change without notice
11/30/2023 Datasheet Deep Learning classification library /--/uploads/2023/11/EasyClassify.png)
Main benefitsOther benefitsSpecificationsSoftware
Ordering Information
Offices
|
We offer you a free evaluation of your vision application by our team of product specialists, using Open eVision's Deep Learning libraries and tools.
Submit my projectEasyClassify 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.
EasyClassify, EasySegment and EasyLocate can be purchased as part of the Deep Learning bundle or individually as inference only licenses.
DownloadOpen 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. For EasySegment, Deep Learning Studio integrates an annotation tool and can transform prediction into ground truth annotation. It also allows to graphically configure the tool to fit performance requirements. For example, after training, one can choose a tradeoff between a better defect detection rate or a better good detection rate.
Open eVision is a set of 64-bit libraries that require an Intel compatible processor with the SSE4 instruction set or an ARMv8-A compatible processor.
Open eVision can be used on the following operating systems:
Microsoft Windows 11, 10, 8.1, 7 for x86-64 (64-bit) processor architecture
Linux for x86-64 (64-bit) and ARMv8-A (64-bit) processor architectures with a glibc version greater or equal to 2.18
Remote connections
Remote connections are allowed using remote desktop, TeamViewer or any other similar software.
Virtual machines
Virtual machines are supported. Microsoft Hyper-V, Oracle VirtualBox and libvirt hypervisors have been successfully tested.
Only the Neo Licensing System is compatible with virtualization.
Minimum requirements:
2 GB RAM to run an Open eVision application
8 GB RAM to compile an Open eVision application
Between 100 MB and 2 GB free hard disk space for libraries, depending on selected options.
Supported programming languages :
The Open eVision libraries and tools support C++, Python and the programming languages compatible with the .NET Framework (C#, VB.NET)
C++ requirements: A compiler compatible with the C++ 11 standard is required to use Open eVision
Python requirements: Python 3.11 or later is required to use the Python bindings for Open eVision
.NET requirements: .NET Framework versions 4.8 or later are supported
Supported Integrated Development Environments:
Microsoft Visual Studio 2017 (C++, C#, VB .NET, C++/CLI)
Microsoft Visual Studio 2019 (C++, C#, VB .NET, C++/CLI)
Microsoft Visual Studio 2022 (C++, C#, VB .NET, C++/CLI)
QtCreator 4.15 with Qt 5.12
PC4187 Open EasyClassify for USB dongle
PC4337 Open eVision EasyClassify
PC4192 Open EasyClassify Inference for USB dongle
PC4342 Open eVision EasyClassify Inference
PC4182 Open Deep Learning Bundle for USB dongle
PC4332 Open eVision Deep Learning Bundle
Please use Open eVision instead for new developements.
In order to be able to work on your project, we need as much information as possible about what you are trying to achieve. What are your requirements in terms of accuracy and processing time? Which platform (CPU / GPU, Windows / Linux, Intel / ARM) do you plan to use? How are your images captured? How are they annotated / labelled, etc.