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A year ago, we launched the Delphi University project here in Brazil. And yesterday, 13/04/2021, it was a day to celebrate the success of the project. The idea of ​​live and the call The day started and at around 10 am I remembered that I was completing exactly one year since the launch of Delphi University . I talked with the team in the group of content producers and sent “let’s do a live class?” I wanted the live to be light, a chat without responsibility, without a technical part … So when making the call to live I thought to myself: “I want something that makes people laugh…” and the rest is what you saw in the editing I did, if you have not seen the video of the call is here below: Video call for Delphi University’s 1-year Live Guests In addition to the content producers, we opened space to interact with some special guests… who for example went to live was Prof. Tiago Souza , training coordinator at the Paula Souza Center. You can find the full post on my website (in Portuguese): And this year we intend to deliver even more content at Delphi University. Discover: universidadedelphi.com.br. See you at the next opportunity.

George Kirkwood has been working with the programming language ever since Delphi 1. His application (SiteZilla) showcase entry was an excellent addition to the Delphi 26th Showcase Challenge and we exclusively asked him about how he works with Delphi. Take a look at his SiteZilla website for further knowledge about his application. When did you start using RAD Studio/Delphi and have long have you been using it? I’ve been using Delphi since version 1. We previously created applications in Visual Basic, but as soon as Delphi came along we jumped ship and abandoned all VB code. What was it like building software before you had RAD Studio/Delphi? We had MS-DOS based character interfaces. Then VB came along and we could design more visual applications for Microsoft Windows. Connecting to databases with VB wasn’t exactly straightforward, and the choice of databases was limited. Delphi changed all of this. How did RAD Studio/Delphi help you create your showcase application? The app needed to work on multiple platforms, so as an existing Delphi developer it was a simple decision to make to go with Delphi and FireMonkey. Although there was still a lot to learn, we could re-use a lot of the existing code so this gave us an advantage in getting started. Our development time for this app from concept to delivery was achieved extremely quickly. What made RAD Studio/Delphi stand out from other options? The cross platform write once, run anywhere ability was a big plus for us. It also helped our customers in being able to provide the same app, with the same layouts and interfaces, on all devices. What made you happiest about working with RAD Studio/Delphi? Being able to utilise nearly 30 years of experience to create solutions quickly. The familiarity of the IDE, code etc., when developing for other platforms made life a lot easier. I didn’t have to learn Android Studio, Objective C or the myriad of ways in which you had to do certain tasks on each platform. What have you been able to achieve through using RAD Studio/Delphi to create your showcase application? We’ve utilised push messaging, GPS location and offline data storage. Some of this would have been difficult with the platform specific IDEs. The app was delivered from concept to production ready in less than 6 weeks. What are some future plans for your showcase application? We plan to add more features, utilize new technologies and device capabilities and ensure compatibility with every device our customers use. Thank you, George! Click the link below to view his showcase entry. Showcase

We love featuring our showcase applications – it’s great to see the versatility and skill Delphi developers put into them. There’s such a wide variety of offerings too from intelligent order-taking, machine-learning vision apps, powerful museum mobile experiences which enhance visits to exhibits with helpful information and three dimensional images. Wherever your imagination takes you RAD Studio Delphi can help make it a reality on Windows, macOS, Linux, iOS and Android. All work and no play? Not with Firemonkey! Games are also well represented by our community of wonderfully talented Delphi developers. This beautifully-designed game from French developer GBESort is a great example of what can be done. FMXPong is a version of the famous game “Pong”. The original Pong, from Atari, was very likely the first computer game ever released. FMXPong is a tribute to the original, but bringing things right up to date in 3D. FMXPong also contains some additional features enabled by the modern world of mobile devices. For example you can move the paddle by touching on the screen or by tilting the smartphone or tablet which the code then detects using the gyroscope of your device. What’s better than a great mobile game written with Delphi? How about a great game with full open source? All the code for FMXPong is fully open source and available at: https://github.com/gbegreg/FMXPong Website FMXPong Google Play FMXPong Screenshot Gallery Are you ready to write a mobile game?

Microsoft’s Azure has a broad collection of services you can access with an easy-to-use API. Azure is Microsoft’s cloud hosting and computing platform with a catalog of more than 200 different products. It also includes products which allow you to implement Machine Learning services. Those services all have an API which can you can access using client access libraries or a REST client. Delphi takes this ease of use one step further by providing a TAzureConnectionInfo to implement some of those services quickly and with a minimal amount of code. Also, we can access the services using Delphi’s built-in REST client. Is Azure Read Client Free? No, the Azure Read Client is not free, but the good news is when you first register you will get some free 12 months services and an free-tier allowance for services so you can try things out as you develop, test and launch your app. Some Azure services have very generous ‘always free’ levels. The service we going to use in our OCR application is  “Cognitive Search” which is one of those which is always free. It has a permanent limit of 10,000 documents, but that’s more than enough for our testing purposes. How do we get API credentials for the “Computer Vision” service resources? For our OCR application, we going to use the “Cognitive Services->Computer Vision” resource. First you must have an “Azure subscription”. Go to the link below and create an “Azure subscription” if you don’t have one. It’s free to start! https://azure.microsoft.com/en-us/free/cognitive-services/ Once you have the subscription, you can create the required service links. Go to this link to create a “Computer Vision” resource. https://portal.azure.com/#create/Microsoft.CognitiveServicesComputerVision Make sure you select the correct region because you can’t go back and change it later. Now go to the resource you created and choose “Keys and Endpoint” from the left-hand menu. Now, copy one of the keys and and the location. We need those in our application. How to connect to the Cognitive Services REST API? We need TRESTClient, TRESTRequest and a TRESTResponse components to connect to the cognitive services REST Api. Lets drag and drop TRESTClient in to the forum and do some basic property changes. Make sure the “Accept” property has “application/json” type. Set the content type to “application/json“. Then drop a TRESTRequest component into the forum and set client property to the client we created earlier. Set the method to “rmPOST“. Place a TRESTResponse component and set the response property in the request component to this response object. Add some edit boxes, buttons and a memo box to complete our interface. How do we use the API to post the image for processing? We cannot post the image to cognitive services and get the result in one call. The image processing takes time, although usually this is less than five seconds. So, first we need to submit our image to the cognitive service and get the “Operation-Location” and check the status until it’s “succeeded”. If the server is still processing the image, status will be “running” instead. For each and every call to cognitive service API, we need to provide our subscription key through the HTTP Header. It’s the key we copied earlier from the resource we created. To do that, add a new parameter to TRESTRequest component, set the ‘kind’ to […]

Michał Bąkowski first worked with Delphi many years ago. He participated in the Delphi 26th Showcase Challenge with his cutting optimization (TonCut) showcase entry. Learn more about his software over at the TonCut website. When did you start using RAD Studio/Delphi and have long have you been using it? I’ve started with Delphi 1 ages ago. Before I was working with Borland Pascal for Windows and when Delphi came out, it was like a revolution. What was it like building software before you had RAD Studio/Delphi? It was much more time consuming, difficult and harder to control. With Delphi, creating UI is very fast and simple. How did RAD Studio/Delphi help you create your showcase application? Most of all it allows creating own components and easily using it. Besides that, when I started working on TonCut, there was no other option actually.  All other tools were far behind Delphi. What made RAD Studio/Delphi stand out from other options? It allows fast creation and modification of UI. This is the main advantage of Delphi. What made you happiest about working with RAD Studio/Delphi? Hard to tell. I think, again option to create own components. What have you been able to achieve through using RAD Studio/Delphi to create your showcase application? Well, I created the app that my customers like. This is all I need. What are some future plans for your showcase application? We will be working on adding more AI to the app. Also we plan to add new optimization algorithms (1D with slants, 2D nesting of any shapes and maybe even 3D). Some functional changes are also on their way.   Thank you so much Michał! Head on over to the TonCut showcase to read more about Michał’s work

How do I start using Machine Learning in Windows? Machine learning isn’t only for the cloud, or run locally in a web browser or command prompt, Microsoft is bringing it to PCs in the latest Windows 10 release. For example, Microsoft provides Python’s WinRT to create Windows Machine Learning applications, and ONNX (Open Neural Network Exchange) format, an open standard for sharing trained deep learning models between platforms and services. The latest release of Windows 10 provides plenty of new APIs for your applications. This includes the support for running trained Machine Learning models as part of Windows applications, taking advantage of local GPUs to accelerate Machine Learning applications. On the other hand, Embarcadero created Python4Delphi (P4D) to empower Python users with Delphi’s award-winning VCL functionalities for Windows which enables us to build native Windows apps 5x faster. This integration enables us to create a modern GUI with Windows 10 looks and responsive controls for our Python Machine Learning applications. Python4Delphi makes it very easy to use Python as a scripting language for Delphi applications. It also comes with an extensive range of demos and tutorials. With Python4Delphi, you can integrate any Python features, functionalities, and libraries with Delphi to create a nice GUI for your Machine Learning applications in Windows. In this tutorial, we will discuss the following: How to use these 5 Python libraries with different Machine Learning capabilities to perform Machine Learning in Windows Apps: Matplotlib, NLTK, Pillow, OpenCV, and Keras. All of them would be integrated with Python4Delphi to create Windows Apps with Machine Learning capabilities. Prerequisites: Before we begin to work, download and install the latest Python for your platform. Follow the Python4Delphi installation instructions mentioned here. Alternatively, you can check out the easy instructions found in Getting Started With Python4Delphi video by Jim McKeeth. Time to get started! First, open and run our Python GUI using project Demo1 from Python4Delphi with RAD Studio. Then insert the script into the lower Memo, click the Execute button, and get the result in the upper Memo. You can find the Demo1 source on GitHub. The behind the scene details of how Delphi manages to run your Python code in this amazing Python GUI can be found at this link. Open Demo01.dproj. 1. How do I enable Matplotlib inside Python4Delphi in Windows? Matplotlib is one of the most popular and oldest plotting libraries in Python which is used in Machine Learning. In Machine Learning, Matplotlib helps to gain insights from a huge amount of data through different data visualization techniques. With the high demand for Data Science and Analytics skill sets, drawing graphics programmatically is a very popular task these days. You can easily solve these tasks by combining the Matplotlib library with Python4Delphi (P4D). Matplotlib can be used in Python scripts, the Python and IPython shell, web application servers, and various graphical user interface toolkits (in this post, Python GUI by Delphi’s VCL using P4D)! After installing Python4Delphi properly, you can get Matplotlib using pip or easy install to your command prompt: and don’t forget to put the path where your Matplotlib installed, to the System Environment Variables, here are the example: C:/Users/YOUR_USERNAME/AppData/Local/Programs/Python/Python38/Lib/site-packages C:/Users/YOUR_USERNAME/AppData/Local/Programs/Python/Python38/Scripts C:/Users/YOUR_USERNAME/AppData/Local/Programs/Python/Python38 C:/Users/YOUR_USERNAME/AppData/Local/Programs/Python/Python38/Lib/site–packages C:/Users/YOUR_USERNAME/AppData/Local/Programs/Python/Python38/Scripts C:/Users/YOUR_USERNAME/AppData/Local/Programs/Python/Python38 The following is a code example of Matplotlib to create Stacked Horizontal Bar Chart to Visualize Discrete Distribution (run […]