Mech-DLK SDK
Welcome to Mech-DLK SDK User Manual. Let’s get started!
Overview
Mech-DLK SDK is a secondary development software kit specifically designed to be used with Mech-DLK. Its main purpose is to help developers easily do deep learning inference in their software systems. With Mech-DLK SDK, developers can rapidly deploy deep learning models and flexibly integrate deep learning functionality into their own applications without reliance on Mech-Vision. You can use the provided APIs to build applications in C and C# languages.
You can apply Mech-DLK SDK for the inference based on models exported from Mech-DLK (version 2.4.2 or above).
Release notes
Mech-DLK SDK 2.0.1
New features
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Added C# APIs for secondary development in C# language. See C# API Reference.
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Provided samples using C# APIs and realized collaborative development with OpenCV and HALCON. See the sample list and running prerequisites.
Configuration adjustment
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Changed the ways of adding environment variables for running samples provided in Mech-DLK SDK. For more details, see the Add environment variables parts in the sample usage guide.
Bug fix
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Fixed the result parsing problem that occurred during inference using the defect segmentation model.
Contents
This manual consists of the following chapters. Click to view the details according to your needs:
No. | Chapter | Content |
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1 |
View the system requirements and obtain Mech-DLK SDK and the third-party libraries and resources it depend upon. |
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2 |
Learn to use Mech-DLK SDK for inference with a defect segmentation model. |
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3 |
Learn about the types of samples and prerequisites to run these samples and build and run these samples. |
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4 |
View APIs and structures in C and C# languages. |
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5 |
View the frequently asked questions. |