Demystifying pointers in Delphi

Having a general understanding of how memory and addressing works, helps you understand pointers in Delphi (and C/C++). Learning assembler also gives you that knowledge, but there are simpler ways to think about it.

A pointer is a memory location that contains the address to the actual data you want.

Think of a street with houses. Make a list of the houses and their addresses.
This is a list of pointers. Each pointer in the list leads to the actual house it refers to.

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Generic Command Line Parser for Delphi 10.3.x

You know the feeling. You need a specific input from your command line, but you can’t find something lightweight that does the job. Hence, the FDC.CommandLine was born.

You can use – / or + as a switch, and use : or = as a flag for parameters.
/option:parameter

You can use single and double quotes to be able to parse parameters that contain spaces and quotes.
/quoteoftheday:”This is a ‘quoted’ parameter”

It also supports lists of parameters.
/inputfiles:(file1.txt , “file with space.txt”)

Take a look at the TestFDCCommandLine.dpr for more examples of how it works.

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Demo shows an Android application using an Android Service to download an image from the Internet.

Originally shared by Delphi

Demo shows an Android application using an Android Service to download an image from the Internet. The Android Service works as a background task, even if the main application is not running. When the image file is downloaded to the device, a notification is presented. Handling the notification loads the image previously downloaded. The service stops itself after performing the download process.

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http://embt.co/2qXZwAH

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Access OpenCV headers and samples for #Delphi which contain 2D and 3D feature toolkits, Egomotion estimation, Facial…

Originally shared by Embarcadero Technologies

Access OpenCV headers and samples for which contain 2D and 3D feature toolkits, Egomotion estimation, Facial recognition system, Gesture recognition, Human–computer interaction (HCI), Mobile robotics, Motion understanding, Object identification, Segmentation and recognition, Stereopsis stereo vision: depth perception from 2 cameras, Structure from motion (SFM), Motion tracking, and Augmented reality. OpenCV also includes a statistical machine learning library with things like Boosting (meta-algorithm), Decision tree learning, Gradient boosting trees, Expectation-maximization algorithm, k-nearest neighbor algorithm, Naive Bayes classifier, Artificial neural networks, Random forest, Support vector machine (SVM).

.>>> http://embt.co/2edXa7G