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Deep Learning Gets Easier + Code Generation Software for Image Processing

 

Welcome back to ClearView Blog. Over the next few articles, we will be discussing the important current machine vision trends, not just thinking about technological advancement, but also focusing on global factors that are impacting the world of machine vision and the industries we support.

This week we are taking a look at how software advancements are making deep learning more powerful and easier to deploy, and how MIL CoPilot is revolutionising code generation for image processing functions.

 

The Role of Deep Learning in Industrial Automation

Industrial automation is the core pillar of Industry 4.0. As the demand for skilled labourers increases along with production rates in factory settings, deep learning-based approaches can serve as a stop-gap to reduce labour time and increase efficiency.

For more information on deep learning in industrial automation, check out our dedicated blog post.

 

Why is Deep Learning Better than Traditional Algorithms?

Compared to standard rule-based algorithms, the major advantage with a deep learning neural network is its ability to get good results without the requirement of heavy coding.

 

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Cumbersome coding can bog down a project and impact momentum.

 

In terms of programming, since you don’t have to write code to describe in detail what is considered as a defect, the development of deep learning-based applications is easier and much faster. As a result it’s much easier to deploy deep learning, and as improvements to the AI-based approach keep coming, this will only continue to be the case.

The advantage only gets stronger when it comes to the practice of maintaining and evolving such applications.

Let us consider an application which detects defective products and identifies the type of defect.

 

Scratch Defect

Defect detection in Matrox Imaging Library (MIL) X.

 

Imagine we have to upgrade this application to detect a new type of defect. With a deep learning-based approach, this evolution simply requires adding images of this new defect into the dataset, then training the neural network with the upgraded dataset. After this point, our neural network will now be taking this new defect into account without the modification of a single line of code.

If you needed to apply the same evolution to an application based on a conventional algorithm, you would need to be prepared to rewrite a significant portion of your code.

 

Deep Learning Software Advancements

This inherent lack of coding now not only makes deep learning easier, but fundamental image processing functions themselves have been made far simpler in this way as well. And it’s all down to revolutionary software advancements from Matrox Imaging, making deploying vision systems easier than ever.

 

Training Set

Organising and labelling the training set using Matrox Imaging Library (MIL) CoPilot.

 

Matrox have recognised that working with a programming library to assess the feasibility and best approach to developing a vision application can be both intimidating and time consuming. That’s why they have removed the bulk of this burden with the introduction of MIL CoPilot, an interactive environment for the Matrox Imaging Library (MIL); a field-proven software development kit (SDK) with a comprehensive set of tools for vision application development.

 

Point-and-Click Code Generation for Image Processing Functions with MIL CoPilot

MIL CoPilot is great for facilitating inference and training deep learning datasets. But what happens when you can’t go any further without writing code for your vision application?

Well, MIL CoPilot doesn’t just enable users to select and fine-tune operations before including them in a particular vision application – it offers these capabilities without you having to write any code. All the work done within a session is conveniently held together in a workspace for future reference or sharing with colleagues. A live preview allows users to experiment freely before committing to an operation. The best part is, MIL CoPilot will generate clear, functional code for immediate integration.

 

 

Apply image processing functions to your workspace easily with MIL CoPilot.

 

MIL CoPilot will produce code for any MIL-supported language (C++, C#, CPython, and VB.Net). This provides even the most experienced developers with a faster, easier and more efficient approach to jump-start vision application development.

 

MIL Service Pack Update

The latest MIL X service pack update also delivers a range of new features and functionality, including the training of deep neural networks for image-oriented classification; detection using image-oriented classification based on deep learning; a revamped plus augmented 3D display, processing, and analysis offer; and support for High-Dynamic-Range (HDR) imaging. A companion update also introduces many enhancements to the MIL CoPilot interactive environment including, most notably, support for training a deep neural network.

This means that the almost limitless potential of deep learning functions can be harnessed without the need to be bogged down by endless code.

 

Software & Deep Learning Solutions from ClearView Imaging

Want to find out more about revamping your vision system or automating your industrial processes? Look no further – get in touch with us.

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Also, be sure to check out our great range of smart cameras and machine vision software over in our products section!

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Machine Vision Software

Here at ClearView, we have a broad range of knowledge and machine vision expertise to help you decide on the right solution for your project.

We offer friendly expertise and a huge range of industry-standard quality machine vision components for printing and packaging, robotics, industrial automation, medicine, life sciences, and the automotive industry, just to name a few.

Our experts are happy to help no matter what your question or problem may be. Feel free to get in touch with us and one of our machine vision experts will be ready to help you get going with your project!

 

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