Dimensional Data

How cool would it be for your Windows or mobile app to allow travelers to take random pictures at interesting places and retrieve instant useful information about the location they are visiting and the landmarks they can see? In this article we will see how to easily do just that using RAD Studio and Delphi with only few lines of code! Google API – harnessing super computing power the Delphi way Google may be a great search engine but behind all of the search hits and map directions there is a massive stack of super-computing power driving it all. A search on a location in Google Maps quite often shows not only a detailed map and even a street-level view of the area but also, frequently, a series of additional information about the locale such as points of interest, local landmarks and other items about the selected place. Google allows us to tap into that rich enhanced intelligence and apply it not just to maps but to objects and places in images we have taken or have in our data. This is done via the Google Cloud Vision API. Google’s Cloud Vision API – using machine learning to ‘understand’ our images Google Cloud’s Vision API offers powerful pre-trained machine learning models that you can easily use on your desktop and mobile applications through REST or RPC API methods calls. Lets say you want your application to detect objects, locations, activities, animal species, products, or maybe you want not only to detect faces but also their emotions, or you may have the need to read printed or handwritten text, this and much more is possible to be done for free (up to first 1000 units/month per feature) or at very affordable prices and scalable to the use you make with no upfront commitments. Detecting landmarks The option to “Detect Landmarks” is part of the Vision API that we can use to detect and extract information about entities in an image n order to identify a landmark and retrieve its GPS coordinates. We can use RAD Studio and Delphi to easily setup its REST client library to take advantage of Google Cloud’s Vision API to empower our desktop and mobile applications and if the request is successful, the server returns a 200 OK HTTP status code and the response in JSON format. Our RAD Studio and Delphi applications will be able to either call the API and perform the detection on a local image file by sending the contents of the image file as a base64 encoded string in the body of the request or rather use an image file located in Google Cloud Storage or on the Web without the need to send the contents of the image file in the body of your request. How do I set up the Google Cloud Vision Landmark Detection API? Make sure you refer to Google Cloud Vision API documentation in the “Detect Landmark” section – https://cloud.google.com/vision/docs/detecting-landmarks – generally, this is what you need to do on Google’s side: Visit https://cloud.google.com/vision and login with your Gmail account Create or select a Google Cloud Platform (GCP) project Enable the Vision API for that project Enable the Billing for that project Create a API Key credential AI vision, in your apps! Lets say one good friend […]

Manuel Lopez has working with Delphi since 1995. His software (Fotomorsaicos) was one of the showcase entries for the Delphi 26th Showcase Challenge and we had a conversation with him about his experience with Delphi through the years. Download the software through the FotoMorsaicos sourceforge page. When did you start using RAD Studio/Delphi and have long have you been using it? I started using Delphi from version 1, which came out in 1995 and was announced at the Borland Conference that year. From there I used versions 1, 23, 3, 4, 5, 6 and 7, the latter being the most stable and the best. Later new versions came out but I no longer worked with them. However, for an academic project, I acquired the Delphi RAD Seattle academic license a couple of years ago. What was it like building software before you had RAD Studio/Delphi? Before you had to do a lot of work manually. The idea of components (visual and non-visual), was undoubtedly an advance in the way of programming. I think the programming paradigm changed with the arrival of Delphi, making Windows applications really easy to create. Turbo Pascal already had some possibilities thanks to the enormous amount of source code available (even from Borland), but the idea of components simplified many of the previous difficulties in programming. How did RAD Studio/Delphi help you create your showcase application? The manipulation of graphics, images and the methods of the corresponding components made writing a program like the photomosaics really much easier. In fact, the idea of the “canvas”, with its corresponding methods, makes the problems to solve much easier. I think that a photomosaic system without the help of these components would be much more difficult to program. What made RAD Studio/Delphi stand out from other options? I never really thought of another option, as I had previously used Turbo Pascal and Delphi is finally Pascal on Windows. Also, the speed of the compiler is unmatched comparing with other development tools. What made you happiest about working with RAD Studio/Delphi? Easy to program, great debugger, stable code, powerful language and rich in expressiveness. All of this shows up clearly in the Delphi compilers over time. It seems to me that programming with all these facilities is of great help. What have you been able to achieve through using RAD Studio/Delphi to create your showcase application? The creation of the photomosaic program had some results that made me happy. For example, the fact that creating a photomosaic could be done in a couple of minutes. Considering the amount of calculations that must be done (about 500 thousand square roots), the speed of the code is very, very acceptable. What are some future plans for your showcase application? Some ideas for the photomosaic app is to create images with photographs that are not necessarily rectangular. Also improve the possibility of avoiding repetitions and combining different image libraries to have more attractive mosaics. Showcase

How do I start using Natural Language Processing in Windows? Natural language processing (NLP) is a subfield of Linguistics, Computer Science, and Artificial Intelligence which concerned with the interactions between computers and human language, in particular, how to program computers to process and analyze large amounts of natural language data, or teaching machines how to understand human languages and extract meaning from text. The common tasks in NLP include Text Mining, Text Classification, Text Analysis, Sentiment Analysis, Word Sequencing, Speech Recognition & Generation, Machine Translation, and Dialog Systems, to name a few. Since NLP relies on advanced computational skills and tools, developers need the best available tools to help them to make the most of NLP approaches and algorithms for creating services that can handle natural languages. We can build Windows apps with Natural Language Processing capabilities using Embarcadero’s Python4Delphi (P4D). P4D empowers 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 Natural Language Processing 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 Natural Language Processing applications in Windows. In this tutorial, we will discuss the following: How to use these 5 Python libraries with different Natural Language Processing capabilities to perform Natural Language Processing in Windows Apps: NLTK, FlashText, Gensim, TextBlob, and spaCy. All of them would be integrated with Python4Delphi to create Windows Apps with Natural Language Processing 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 the 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 NLTK for NLP inside Python4Delphi in Windows? NLTK is a leading platform for building Python programs to work with human language data. Natural Language Processing or NLP for short — in a wide sense, to cover any kind of computer manipulation of natural language. NLP is a field in Machine Learning with the ability of a computer to understand, analyze, manipulate, and potentially generate human language. NLTK provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum. Do you want to perform Natural Language Processing tasks like predicting text, analyzing & visualizing sentence structure, Sentiment Analysis, gender classification, etc. in the Windows GUI app? You can easily solve these tasks by […]

The webinar was a huge hit. Planning future follow-up webinars on the topic. Blog post: OpenAI’s Introduction to the API with sign-up for the waiting list Academic Paper: Language Models are Few-Shot Learners Documentation: OpenAI API Personally curated YouTube playlist providing a  Slides for today’s webinar (subject to change)

Dmitry Sidorkin started programming with Delphi in 1995. His application (CST CAD Navigator) was one of the submissions for the Delphi 26th Showcase Challenge and we interviewed him for some insights toward his accumulated Delphi knowledge throughout the years. More information about the application at the CST CAD Navigator website. When did you start using RAD Studio/Delphi and have long have you been using it? I started development in Delphi back in 1995, so I have been using it for more than 25 years. We started the development of ABViewer, our first CAD viewer, in Delphi 7 which was the latest version at that time. And now CST CAD Navigator is created with RAD Studio 10. What was it like building software before you had RAD Studio/Delphi? Before Delphi, I developed in Turbo Pascal, using Turbo Vision and Borland Pascal with the OWL library for Windows. My main programming language was Pascal and I sometimes used C/C++, that’s why when Delphi appeared, my choice was obvious. At least for me, there was no viable alternative. How did RAD Studio/Delphi help you create your showcase application? The support for cross-platform applications allowed us to create CST CAD Navigator, a CAD viewer that works on Windows, Linux and Mac. We started working on it from scratch. Without Delphi, we wouldn’t have been able to develop it so quickly. What made RAD Studio/Delphi stand out from other options? It is a single IDE, a single tool for different platforms that makes Delphi especially convenient. In this respect, there are no other options that can be alternatives to Pascal. Without any additional efforts, we created CST CAD Navigator for Windows, Linux and Mac. What made you happiest about working with RAD Studio/Delphi? Delphi is loved by lots of developers. I know that for sure because we often communicate with other Delphi developers who contact us about CAD VCL, our CAD library for Delphi supporting DXF, DWG and a wide range of other formats. But for me personally, the best thing about RAD Studio is being able to create software compatible with different platforms. Our team also appreciates the technical support provided by Embarcadero. What have you been able to achieve through using RAD Studio/Delphi to create your showcase application? With Delphi, CST CAD Navigator can work on several operation systems, which became possible thanks to Delphi. It is also easy to transfer code between projects, thus using our own developments several times. What are some future plans for your showcase application? We are working hard on a version of CST CAD Navigator for mobile platforms – Android and iOS. After that, we plan to add support for new formats. At the moment CST CAD Navigator supports more than 50 different formats including DXF, DWG, STP, IGS, STL and lots of other ones. Our customers expect our viewer to be able to open any drawings, so we do our best to meet their expectations. We plan to add support for Autodesk Revit® formats, Catia files and improve our own parametric 3D core in Pascal. By the way, CADSoftTools is quite unique in using Pascal for such mathematical problems and having tens of thousands of customers all over the world proves the high quality our solutions. Thank you, Dmitry! You may view his showcase entry through the link below. Showcase

Coins, wallets and the tale of very big numbers It’s hard to miss the tidal wave of stories about cryptocurrency. The inexorable rise of BitCoin, Ethereum and a whole stable of others and the volatility where fortunes are made – and lost – has ensured it is the hot technical topic of the day. You can even apparently soon pay for a Tesla with cryptocurrency. In this article we’re going to visualize that volatility and plot the ups and downs of various virtual cryptocurrencies against good old hard cash. It’s surprisingly easy to do! Charts, graphs and bars In this article we are going to use Steema TeeChart for the charting functions. The RAD Studio Delphi VCL framework comes with built-in TeeChart Std. It doesn’t have some of the additional bells and whistles of the TeeChart Pro version but it’s enough to produce some really functional examples. For other platforms such as Firemonkey TeeChart Lite is provided but it has a few features that aren’t included which we would for our purposes. To overcome this you can install Teechart Pro trial version from https://www.steema.com. The trial versions are fully functional with the only limitation that a small nag screen appears when you first run them. Where are we going to get the cryptocurrency data from? We’re going to use the TFDMemTable ExchangeMemTable components to provide the data to the charts. This table contains three fields: USD_BTC (USD for one Bitcoin) USD_ETH (USD for one Ethereum) At runtime, we can retrieve actual data from the Web, or load it from some predefined files. At design time, the table comes with 12 records – last year per month. More details about the table filling see below. Creating our cryptocurrency chart Create a blank VCL form and drop TDBChart on it: Click with your right mouse and select “Edit Chart”: On “Series”, select “Add” Now select “Bar” and press “OK” We have a sample chart! A sample TeeChart bar appears. Now, expand “Series”, select “Series1”, choose “Data Source” and select “Dataset” Select ExchangeMemTable, Date for X, USD_BTC for Bar. Press the “Apply” button. Our 12-month data appears. Tidying some loose ends For this task, probably, we do not need Legend. Uncheck Visible for it: Probably, we do not need also marks, left axis is enough. Uncheck “Visible” for them: Trying out other charts We can easily select another chart style for the same data. Press “Change” for Series1: Now, select “Line” Adding additional cryptocurrencies to our VCL chart example Now, let us add another cryptocurrency. In “Series”, press Add: Choose “Line”. For Series2, select “Dataset” – ExchangeMemTable, Date for X, USD_ETH for Y and then press “Apply” to make the chart sprint into life. Adjusting for cryptocurrency variations on the example VCL chart Ethereum (ETH) values are significantly smaller than BitCoin (BTC). To improve the scaling and provide a better comparison let’s expand “ETH” to a full chart size. Let us give ETH a separate axis on the right side: How to fetch live cryptocurrency data into our VCL chart example To fill the ExchangeMemTable with actual rates from the currency exchange, you should get a free key from https://coinlayer.com/. Enter this key in the editor field. Select an appropriate time period (last year, last month, last week) and step (month, week, number […]

For good food fans in the gorgeous island of Cyprus Delphi is the power behind Wagamama Cyprus’ mouth-watering mobile ordering app. The Wagamama mobile ordering app from developer Dafera Ltd makes it a delight for the eyes and the tastebuds by powering Cypriots to have the opportunity to enjoy their favorite delicious Wagamama delivered fresh and ready at the office, at home or anywhere they wish. Firemonkey Power – Android and iOS with almost no code changes Dafera, based in sunny Nicosia, really make the app shine through their clever use of the best RAD Studio Delphi’s Firemonkey FMX cross-platform features so that the same app can be delivered on Android and iOS with virtually no changes to the code. Firemonkey and RAD Studio do the heavy-lifting. Coupled with simply stunning photography and skillful direct integration into Wagamama’s order management workflow users are treated to a seamless, trouble-free ordering and delivery experience. Great work by the Dafera team! Website wagamama Google Play wagamama Apple App Store wagamama Screenshot Gallery If you’re looking to create a professional, top quality mobile or desktop app like Wagamama Cyprus- RAD Studio has the answers and the power to make it happen – just bring your imagination! What do you want to create?