在Linux Mint上的Qt Creator 3.5.1上使用OpenCV 3.3.1（最新内核）

Question

I'm trying too make a project in C++ using OpenCV via Qt Creator. I have not written any code yet as such, I'm just trying to get my project to access my openCV file. I've tried a couple of methods I found on google, namely editing the $PKG_CONFIG_PATH variable:

 echo $PKG_CONFIG_PATH
:/home/jess/Documents/SRI/TER/opencv-3.3.1`

(/home/jess... is where the openCV files are - as obtained and extracted from the website) my .pro file looks like this:

QT       += core gui
# add open CV
CONFIG += link_pkgconfig
PKGCONFIG += opencv-3.3.1

greaterThan(QT_MAJOR_VERSION, 4): QT += widgets

TARGET = test
TEMPLATE = app

SOURCES += main.cpp\
        mainwindow.cpp

HEADERS  += mainwindow.h

FORMS    += mainwindow.ui

And when I build the project it tells me that openCV cannot be found (I have also tested using the name "openCV-3.3.1", same result) if anyone can give me any pointers as to where I'm going wrong, I would be most grateful!

Answer 1

You need to have OpenCV dev version installed on your system. Fortunately OpenCV can be found in official Ubuntu/Mint repositories. To start developing OpenCV apps you need to install its -dev version.

sudo apt install libopencv-dev

Ok. Now head to your project's .pro file and link your project to OpenCV.

LIBS += -lopencv_core -lopencv_highgui

Make sure you've added all the OpenCV modules you need. OpenCV have the following modules:

• core - a compact module defining basic data structures, including the dense multi-dimensional array Mat and basic functions used by all other modules.

• imgproc - an image processing module that includes linear and non-linear image filtering, geometrical image transformations (resize, affine and perspective warping, generic table-based remapping), color space conversion, histograms, and so on.

• video - a video analysis module that includes motion estimation, background subtraction, and object tracking algorithms.

• calib3d - basic multiple-view geometry algorithms, single and stereo camera calibration, object pose estimation, stereo correspondence algorithms, and elements of 3D reconstruction.

• features2d - salient feature detectors, descriptors, and descriptor matchers.

• objdetect - detection of objects and instances of the predefined classes (for example, faces, eyes, mugs, people, cars, and so on).

• highgui - an easy-to-use interface to simple UI capabilities.

• videoio - an easy-to-use interface to video capturing and video codecs.

• gpu - GPU-accelerated algorithms from different OpenCV modules.

• ... some other helper modules, such as FLANN and Google test wrappers, Python bindings, and others.

To link your project to another module just add a -lopencv_<module> to LIBS . That's it!