Delphi/FPC sources and examples:

• added Pascal classes for vectors and Ptrs (TOcvVector, TOcvPtr) Note: the classes use generics and require FPC 3.3.1 or superior
• added an example showing how to use Pascal classes: featureTestWithClasses
• detailed docs on vectors and Ptrs

C++ sources:

• ocvWrp_nativeNotGen.h, ocvWrp_nativeNotGen_signatures.h : added parameter "mask" to PCvMatCopy function; added parameter "channel" to PCvMatGetx/pCvMatSetx functions
• ocvWrp_c_generated_const.h: added constants for all types of Mat

Binaries:

• recompiled all DLL

Delphi/FPC sources and examples:

• unOcvWrapper_const.pas: added constants for all types of Mat
• OpencvWrapper.pas: added parameter "mask" to PCvMatCopy function; added parameter "channel" to PCvMatGetx/pCvMatSetx functions
• Pascal-classes\unOCVImage.pas: new class TOCVParamMat; many new methods for TOCVImage
• Pascal-classes\ocvWrapComp.pas: added reference to new unit unOCVImage
• Pascal-classes\unOpenCVDelphi46.pas: moved TOCVImage class to new unit unOCVImage; fixed some minor bugs
• Pascal-classes\unOCVContours.pas: new class for OpenCV contours
• frameRecon: new project Delphi/Lazarus that find the transformation matrix (homography) between a camera image and corresponding horizontal image (floor)

Also added a new directory pasdoc with documentation on Pascal classes.

• Added scripts to compile library under Apple MacOS. Kindly contributed by user "havezet". This require also a modify in OpencvWrapper.pas conditionals for FPC/Lazarus: changed symbol LINUX with more general UNIX; added lines to link library in MacOS

• Added an example using Midas DNN, that estimates depth (distances)
  in a photo. Red points are points closer to observer,
  blu points are farther.

• Added four Delphi VCL/Lazarus components: two as image source, TOcvVideoSource and TOcvImageDirectory; two as image processors, TOCVProcObjectDetector and TOcvProcFaceDetector (also face recognizer)
• Added a program, createFacesDB, that creates and save on disk a lightweight database of faces "signatures". This is needed from the face recognizer class
• Added unOpencvDelphi46 unit with a class to wrap the Opencv image/Mat class, and other classes that wrap and simplify some Opencv DNN algorithms
• Added DELPHIDELAYED define to activate in Delphi the delayed DLL load mechanism (so removed the separate files in Delayed directory)

• Added scripts and instruction to build on Linux
• For Linux, changed CopyMemory to Move in OpencvWrapper.pas
• Added fromarray/toarray for vectors with simple types (int, char, float, double, uchar)
• Changed default value from 0 to nil for pointer args in Delphi/Freep. functions signatures
• For Delphi extern declarations, added version with "delayed" option
• Added predefinited PCvStringEmpty variable, it can be used when want to pass an empty string as parameter

This project contains a dynamic library (DLL in Windows) that is a wrapper around the C++ API of Opencv v 4.6 . The library expose a pure C API interface to all C++ classes and functions of Opencv. More than 4.000 C wrapper functions, cover vast majority of Opencv C++ classes (more than 300) and global functions, and some standard C++ classes (as vectors). The library is intended especially for accessing Opencv C++ API from Delphi and Freepascal units. So in this repository there are Delphi/Freepascal units with signatures to all the wrapper C API.

This version contains a Deep Neural Network (DNN) module, capable of load and use all main DNN formats: Tensorflow, Torch, Caffe, Darknet, ONNX. The neural net can be used to produce prediction on a assigned input. Varying on net type, input can be: an image (classification, object detection boxes, pose estimation, colorization etc.); a text (classification); and more.

The use of GPU, if any, is totally transparent. The programmer has only to use the class UMat instead of Mat, and Opencv will use optimized code for the GPU.

The official Opencv release contains OpenCL backend to address GPU calculations. So any GPU can be exploited: NVidia, AMD, Intel, and more.

There is a class to read and decode QR Codes. And many more new functions, plus all the standard image processing and general functions found also in older versions.

The wrapper code is based on the Python Opencv interface. So, all Opencv classes or functions exposed to Python are also exposed in wrapper. The code is in general divided in two parts:

• "generated" code, so called because it's automatically and totally generated from scripts using some annotations included in Opencv C++ headers (see https://docs.opencv.org/3.0.0/da/d49/tutorial_py_bindings_basics.html). This code must not be modified by hand .
• "native" code, so called because contains base Opencv classes and also native C++ classes that are not generated from script, but are hand written.

General documentation

Notes on Matrices

Notes on vectors

Notes on Ptr

Inside the pasdoc directory, in HTML format.

Prerequisites to use provided DLL binaries:

• Opencv version 4.6
• Visual C++ 2017 runtime

Download Opencv version 4.6 from https://sourceforge.net/projects/opencvlibrary/files/4.6.0/opencv-4.6.0-vc14_vc15.exe/download NOTE: the official Opencv version has only 64 bit binaries. In this repository, directory Opencv4.6-x86 contains the 32 bit binaries

Install Opencv, and add in Windows path the directory with Opencv DLL (for example: C:\opencv4.6\build\x64\vc14\bin):

set path=C:\opencv4.6\build\x64\vc14\bin;%path%

Download this repository and add in Windows path the directory with ocvWrapper46x64.dll . For example, if you have copied repository in C:\ocvWrapper, then:

set path=C:\ocvWrapper46\bin\Release\x64

Now Opencv and ocvWrapper can be used from every program.

If you haven't Visual C++ runtime, download and install from here:

https://learn.microsoft.com/it-it/cpp/windows/latest-supported-vc-redist?view=msvc-170

WARNING! 64 bit applications could raise error "0xc000007b" if in the path the FIRST ocvWrapper or Opencv directory is the one for 32 bit. Same error if a 32 bit application find in path a 64 bit DLL.

The library can be rebuilt using the Visual C++ 2017 project in ocvCPPWrapper46 directory. Only dependence are the headers, from Opencv source directory, and .lib files of Opencv, found in \build directory of Opencv.

Many thanks to Fred "Jurassic Pork", that prepared and tested the build scripts.

Tested with:

• Ubuntu 20
• Xubuntu 22

1. Install minimal prerequisites (Ubuntu 20.04 as reference)
   sudo apt update && sudo apt install -y cmake g++ wget unzip
2. Download and unpack Opencv 4.6 sources in your home directory:
   wget -O opencv.zip https://github.com/opencv/opencv/archive/4.6.0.zip
   unzip opencv.zip
3. Download ocvWrapper46 repository from github in your home
4. in install.sh set your home folder, Opencv source folder and ocvWrapper folder
5. change install.sh permission to executable:
   chmod a+x install.sh
6. run install.sh:
   ./install.sh

At end you will have Opencv libraries and libocvWrapper46.so installed in /usr/lib

• testKNN: a pure C program that use the K Nearest Neighbors class from Machine Learning module (ML)

• testPCA: a Delphi/Lazarus program for testing the PCA class from ML module

• testSVM: a Delphi/Lazarus program for testing CvSVM class from ML module

• featureTest: a Delphi/Lazarus demo program for ORB feature detector class and matching between images

• cascadeTest: a Delphi/Lazarus demo program for face recognition on webcam, by cascade classifier class

• skeletonize: a Delphi/Lazarus demo program that reduces an image to its more basic contours ("skeleton")

• camshiftdemo: a Delphi/Lazarus demo program, adapted from a classical Opencv example; the program tracks movements of a selected area in real time on webcam, for example the face of person in front of webcam

• qrcodeTest: a Delphi/Lazarus demo that identify and decode QR-CODEs on webcam

• testGPU: a Delphi/Lazarus demo that measures the performances improvement using GPU capable Opencv UMat

• dnnObjectDetection: a Delphi/Lazarus demo program for the DNN module with Yolo object detection neural net

• dnnOpenPose: a Delphi/Lazarus demo program for the DNN module with Coco human pose detection neural net

• dnnRecolorize: a Delphi/Lazarus demo program for the DNN module with a neural net that colorize gray images