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Azure Cognitive Services–Experience Image Recognition using Custom Vision (Build an Harrison Ford Classifier)

December 23, 2018 Algorithms, Artificial Intelligence(AI), Azure AI, Cognitive Services, Compuer Vision Service, Computer Vision API, Custom Vision API, Custom Vision Service, Emerging Technologies, Machine Learning(ML) No comments

Custom Vision Service as part of Azure Cognitive Services landscape of pretrained API services, provides you an ability to customize the state-of-the-art Computer Vision models for your specific use case.

Using custom vision service you can upload set of images of your choice and categorize them accordingly using tags/categories and automatically train the image recognition classifiers to learn from these images and come up with image recognition predictions when you supply an input image. Later consume this service as an API in your existing applications.

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For example:  Here is how an image of Hollywood Actor – Harrison ford being accurately predicted by the custom model through training using a series of pictures of Harrison Ford through different ages and shapes.

I build this sample during Global AI Bootcamp Letterkenny– Hands on Labs, and will take you further through this article. Harrison Ford is my all time favourite actor.

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Another example, Harrison Ford was one among 3 in a photo. Here is how the results would look like.

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Here is how Harrison Ford’ sons picture is being predicted as Harrison Ford, due to similar facial characteristics. |f we further train this model, we can improve it’s capabilities to come up with accurate predictions.

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Now let us see, how it was implemented.

In this article I am going to use a set of Harrison Ford images found on Google Images and then upload them to Custom Vision service like below. For more accuracy, I tried to collect images of Harrison Ford through different stages of his life, so that computer vision model could evolve to predict more accurate results.

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Getting Started with Custom Vision:

The Azure Custom Vision API is a cognitive service that lets you build, deploy and improve custom image classifiers. An image classifier is an AI service that sorts images into classes (tags) according to certain characteristics. Unlike the Computer Vision service, Custom Vision allows you to create your own classifications. The Custom Vision service uses a machine learning algorithm to classify images.

Classification and object detection

Custom Vision functionality can be divided into two features. Image classification assigns a distribution of classifications to each image. Object detection is similar, but it also returns the coordinates in the image where the applied tags can be found.

To get started with our example,  first you need to have a Microsoft Account and Register/Login to https://www.customvision.ai

There going to be five steps of activities we are going to do:

1. Setup a Custom Vision Project

Create a new Project by selecting ‘New Project’ button

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Specify the naming as the followed:

  • Name: HarrisonFordClassifier
  • Description: HarrisonFordClassifier
  • Resource Group: Leave it default to ‘Limited Trial’
  • Project Types: Classification
  • Classification Types: Multi Label (this is essential, we are going to add multiple tags per image in this example: for say ‘Actor’, ‘Person’ and ‘Harrison Ford’
  • Domain: General (for now)

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2. Upload the Images

a.) Prepare Images

I have gathered a set of images you can download it from here, and extract the HF-Demo-Images.zip in to a folder of your choice.

There are two folders in it  first folder(harrisonford) contains all reference images for training the model and second folder(hf-quicktest) contains all the quick test images we are going to use for evaluating the model.

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b.) Create Tags

Select ‘+’ icon to create a new tag and create the following tags

  • Actor
  • Hollywood
  • Harrison Ford
  • Person
  • Male

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Enter Tag Name and click on ‘Save

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c.) Upload Images

Now that we created all the tags, lets upload the images and tag them with respective tags.

Click on ‘Add Images’ button and select the images from “harrisonford” folder to upload.

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d.) Assign Tags

Now specify the associated tags in My Tags section, selecting from the drop down

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Then click on Upload

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Have a review of the images uploaded

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3. Train

Now let us train the model by selecting the green train button on top right hand side of the page

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This initiates the first automatic training(Iteration 1) based on the tags you assigned and images associated to it.

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Once that step is completed let us review the output of the training.

It shows a precision and Recall of 100% indicates our image classification model is trained now to provide Precision of 100% and Recall of 100%.

PS: Recall means out of the tags which should be predicted correctly, what percentage did our model correctly find?

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4. Evaluate the Model

Now that our classifier is trained, let us evaluate the accuracy. For that we are going to use the sample images from “hf-quicktest” folder.

a.) First click on Quick Test button on top – image

b.) Select a local image or select an image URL

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Lets try another image

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Next let us try to upload an image of Ben Ford (Harrison Ford’s son)

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5. Active Learning

Now that we have couple of accurate predictions, Active Learning involves training the model again from the prediction samples we used. This would make the model evolve to provide us more accurate predictions, for example we correcting the model as it identified that Ben Ford also as Harrison Ford based on similar facial features. In real world, he is a different entity other than his father.

Ben Ford is a Chef by profession. So I am going to upload some of his pictures and tag them as Ben Ford. Also couple of images of both father and son together, and then initiate the training again. Hope they would not feel agitated.

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Now if you look at training performance, Precision and Recall values came down a bit, we can realize it is because we have two persons being tagged with some common tags etc.

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Let us do a Quick Test with the previous image of Ben Ford again. voilà!, we have some accurate prediction.

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Similarly, we can repurpose some of the previous prediction images from Predictions tab and add them with right Tags. Then retrain the model again to evolve the model.

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The End:

Now that you have learned how you can train Custom Vision API with set of images and retrain them again for more accuracy. Once your training is completed and you are happy with the performance, you can integrate the logic in to your existing apps using Custom Vision REST APIs. You can follow the HOL that covers the integration topic here.

Custom Vision Services provides you state-of-the-art Classification and object detection capabilities to customize it for your specific need with quick and easy steps. This help you reduce your time to market and increase ROI (Return of Investment) for your product lines or ideas.

Start learning today using the below reference links.

References:

Disclaimer: All the images referenced in this article are available on the public domain and there is no way any private images are been included in this examples. We respect Harrison Ford and his family privacy, this article is just an attempt to prove the capabilities of Azure Custom Vision Services, no way intended to insult or invade Mr.Harrison Ford’s privacy.I am a big fan of you sir.

Azure DevOps–Community Launch-Letterkenny (08-January’ 2019)

December 21, 2018 .NET, .NET Core, .NET Framework, Announcements, Azure, Azure DevOps, Azure DevOps Server, Azure DevOps Services, Community, LKMUG, Microsoft No comments

Inviting you all to Azure DevOps Community Launch in Letterkenny on 08th Jan 2019. Few months back Microsoft Visual Studio Team Services has been rebranded as Azure DevOps.

Azure DevOps is now a suite of separate but integrated services for managing software projects, source control, build and release management and automation testing to enhance your productivity and team performance in whatever development and deployment environment you choose.

Martin Woodward: The Principal GPM for @AzureDevOps and Vice-President of the .NET Foundation would be joining us in Letterkenny for this event.

To know more about Martin Woodward:

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What we’ll cover:
 Introduction to Azure DevOps
 Azure Pipelines: Fully managed CI/CD platform that works with any language, platform, and cloud
 Azure Repos: Source code repositories (Git/TFVC)
 Azure Test Plans: Manual and Automated Testing
 Azure Boards: Plan, track, and discuss work across your teams
 Azure Artifacts: Package management

Additionally, We’ll also cover how to use Azure Pipelines for Continuous builds with your GitHub projects.

If you are interested to learn how to plan smarter, collaborate better and ship faster, sign up now and RSVP/Share it: https://www.meetup.com/lk-mug/events/255764767/ 

Please follow us on:

Azure Master of the Month–December 2018 (Nithin Mohan T K)

December 13, 2018 Azure Certifications, Azure Master, Azure Master of the Month, Azure Master Program, Recognitions No comments

With extreme happiness and delightment I am sharing that I have been selected as the Azure Master of the Month. My journey with Azure Master program started in April’2017 and I have an Intermediate level master badge as of today. This program requires you to keep on updating the related events to be on the leader board.

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Little About Azure Master Program:

Azure Master Program is a recognition program organized by Microsoft to identify and engage with passionate and influential cloud computing focused experts from the industry..

Who are Azure Masters?

Microsoft Azure Masters are experts in the space of cloud computing. They are invariably passionate about sharing their knowledge with their peers, and using the same to architect, design, build and manage the next generation of systems and solutions.

On the bleeding edge of technology

Azure Masters are on the “bleeding edge” of technology know-how, and have an unstoppable urge to get their hands on future-oriented technologies. They have deep knowledge of Microsoft Azure, while inheriting the ability to bring together diverse platforms, products and solutions to solve real world problems.

Passion, sharing & caring

Azure Masters are driven by their passion, sharing spirit and their quest for knowledge. Above all, they are always ready to help others – the one that sets them apart.

How to become an Azure Master?

There are 3 very fundamental qualities you need to have to become an Azure Master:

  • A passion to learn new technologies pertaining to cloud computing;
  • A willingness to use your knowledge to enable and empower your peers; and
  • Envisioning, architecting, designing, building and managing future-ready cloud solutions.

The best of the lot loves what they do – something that stands them apart from all others. Whether you are an expert cloud implementer or manager, a great trainer, an influencer, a top technical community contributor, or have some totally different way of sharing your passion for cloud computing, we would love to hear from you!

From Announcement in Azure Master site:
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To Join the Azure Master Program – Sign Up @ https://www.azuremaster.in

C# 8.0 New Feature–Interface Default Implementation for Methods

December 1, 2018 .NET, .NET 4.8, .NET Core, .NET Core 3.0, ASP.NET, Microsoft, Visual Studio 2017, VisualStudio, VS2017 No comments

With upcoming C# 8.0, there is an interesting feature called default implementation body for methods within an interface definition. That means if you have few methods signatures defined and you want make implementation classes to implement these methods optionally (remember, previously all interface methods needs to be implemented in implementation classes) , with C# 8.0, you can define methods to follow default implementation body, if it not explicitly implemented by implementation classes of the same interface.

When will we get C# 8.0?

C# 8.0 will be released along .NET Core 3.0, in upcoming months. Currently preview 1 version is available to try out.

Get Started:

1.) First of all, download and install Preview 1 of .NET Core 3.0 and Preview 1 of Visual Studio 2019.

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2.) Launch Visual Studio 2019 Preview, Create a new project, and select “Console App (.NET Core)” as the project type.

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3.) Once the project is up and running, change its target framework to .NET Core 3.0 (right click the project in Solution Explorer, select Properties and use the drop down menu on the Application tab).

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Here is how it can be implemented:

using System;

namespace CSharp8Demo
{
    class Program
    {
        static void Main(string[] args)
        {
            Console.WriteLine("Hello World!");

            IVehicle bmw = new Bmw();
            bmw.DefaultMessage();

            IVehicle audi = new Audi();
            audi.DefaultMessage(); 
        }
    }


    interface IVehicle
    {
        //default implementation 
        void DisplayMessage();

        void DefaultMessage() { Console.WriteLine("I am  inside default method in the interface!");} 
      
    }

    public class Bmw : IVehicle
    {
        public void DisplayMessage()
        {
            Console.WriteLine("I am BMW!!!");
        }
    }

    public class Audi : IVehicle
    {
        public void DisplayMessage()
        {
            Console.WriteLine("I am AUDI!!!");
        }
        public void DefaultMessage() => Console.WriteLine("I am  inside audi class!");
    }
}

Azure DevOps Server 2019 rc1–Available/Download Now

November 21, 2018 Azure, Azure DevOps, Azure DevOps Server, Azure DevOps Services, Microsoft, TFS No comments

Microsoft has announced the availability of first release candidate (RC) of Azure DevOps Server 2019. The Azure DevOps Server(previously TFS/Team Foundation Server) delivers the Azure DevOps Services optimized for customers who prefer to self-host these devops services on-premises.

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Key Features included/improved :

  • Branding Changes
  • Azure DevOps Server includes support for Azure SQL in addition to existing SQL Server support.
  • New release management interface from Azure DevOps (Cloud Server) is also included.

Editions Available:

  • Azure DevOps Server Express – Free version for individuals and small teams.
  • Azure DevOps Server – enterprise grade version with more seats.

Upgrading from TFS :

  • TFS 2012 and above: A direct upgrade to Azure DevOps Server  is possible.
  • TFS 2010 or lower:  Perform interim steps before upgrading to Azure DevOps Server 2019.

Production/Go-Live Use:

  • Azure DevOps Server 2019 RC1 includes a go-live license making it suitable for production use right away.
  • Microsoft is looking for feedbacks though to incorporate in future RC’s

Download:

Source:

Visual Studio 2017–Version 15.9.0 released

November 13, 2018 .NET, .NET 4.8, .NET Core, .NET Core 2.0, .NET Core 2.1, .NET Core 2.2, .NET Core 3.0, .NET Framework, ASP.NET, ASP.NET Core 2.1, C#.NET, JavaScript, Microsoft, Razor, SignalR, TypeScript No comments

Microsoft has today released Visual Studio 2017 – Update 15.9.0 with lots of bug fixed and improvements to the IDE for stability and performance.

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Release Notes: Visual Studio 2017 version 15.9 Minor Release

Download the latest update from: visualstudio.com/downloads

Latest News: There is a new service update released on November 15, 2018 — Visual Studio 2017 version 15.9.1 Servicing Update

Useful Reads: