Beispiel für einen technischen Test von Computer Vision – Python / C++

So installieren Sie opencv in Python

pip install opencv-python

So installieren Sie opencv in C++

git clone https://github.com/opencv/opencv.git
mkdir -p build && cd build
cmake ../opencv
make -j4
sudo make install

CmakeLists.txt

cmake_minimum_required(VERSION 3.0)
project(opencv_c__)

find_package(OpenCV REQUIRED)
include_directories(${OpenCV_INCLUDE_DIRS})
set(CMAKE_CXX_STANDARD 17)

add_executable(opencv_c__ main.cpp)
target_link_libraries(opencv_c__ ${OpenCV_LIBS})

---

I – Bewegungserkennung

def ex1():
    cap = cv2.VideoCapture(0)

    object_detector = cv2.createBackgroundSubtractorMOG2()

    while True:
        ret, frame = cap.read()
        mask = object_detector.apply(frame)
        cv2.imshow('Video', mask)
        if cv2.waitKey(30) & 0xFF == 27:
            break

    cap.release()
    cv2.destroyAllWindows()

#include <iostream>

#include <opencv2/opencv.hpp>
#include <opencv2/videoio.hpp>
#include <opencv2/video.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>

int main() {
    cv::VideoCapture cap(0);
    cv::Ptr<cv::BackgroundSubtractor> object_detector = cv::createBackgroundSubtractorMOG2();

    while (true) {
        cv::Mat frame;
        cap >> frame;
        cv::Mat mask;
        object_detector->apply(frame, mask);
        cv::imshow("Video", mask);
        if (cv::waitKey(30) == 27) {
            break;
        }
    }

    cap.release();
    cv::destroyAllWindows();
    return 0;
}

II – Gesichter verwischen

def ex2():
    cap = cv2.VideoCapture(0)

    while True:
        ret, frame = cap.read()
        face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        faces = face_cascade.detectMultiScale(gray, 1.1, 4)
        for (x, y, w, h) in faces:
            roi = frame[y:y + h, x:x + w]
            roi = cv2.GaussianBlur(roi, (23, 23), 30)
            frame[y:y + h, x:x + w] = roi

        cv2.imshow("gray", gray)
        if cv2.waitKey(30) & 0xFF == 27:
            break

    cap.release()
    cv2.destroyAllWindows()

#include <iostream>

#include <opencv2/opencv.hpp>
#include <opencv2/videoio.hpp>
#include <opencv2/video.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>


int main() {
    cv::VideoCapture cap(0);

    while(true) {
        cv::Mat frame;
        cap >> frame;

        cv::CascadeClassifier face_cascade;
        face_cascade.load("haarcascade_frontalface_default.xml");

        std::vector<cv::Rect> faces;
        face_cascade.detectMultiScale(frame, faces, 1.1, 3, 0, cv::Size(30, 30));

        for(int i = 0; i < faces.size(); i++) {
            cv::Rect face = faces[i];
            cv::Mat faceROI = frame(face);
            cv::blur(faceROI, faceROI, cv::Size(30, 30));
        }

        cv::imshow("frame", frame);

        if(cv::waitKey(1) == 27) {
            break;
        }
    }

}

III – Einer Bewegung nachspüren

def ex3():
    cap = cv2.VideoCapture(0)
    object_detector = cv2.createBackgroundSubtractorMOG2()

    last_coordinates = []

    while True:
        ret, frame = cap.read()
        mask = object_detector.apply(frame)
        contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
        for contour in contours:
            if cv2.contourArea(contour) < 5000:
                continue
            (x, y, w, h) = cv2.boundingRect(contour)
            last_coordinates.append((x, y, w, h))
        for i in range(1, len(last_coordinates)):
            cv2.line(frame, (last_coordinates[i - 1][0], last_coordinates[i - 1][1]),
                     (last_coordinates[i][0], last_coordinates[i][1]), (0, 0, 255), 5)
        cv2.imshow('Video', frame)
        if cv2.waitKey(30) & 0xFF == 27:
            break

    cap.release()
    cv2.destroyAllWindows()

#include <iostream>

#include <opencv2/opencv.hpp>
#include <opencv2/videoio.hpp>
#include <opencv2/video.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>


int main() {
    cv::VideoCapture cap(0);
    cv::Ptr<cv::BackgroundSubtractor> object_detector = cv::createBackgroundSubtractorMOG2();

    std::vector<cv::Rect> last_coordinates;

    while (true) {
        cv::Mat frame;
        cap >> frame;
        cv::Mat mask;
        object_detector->apply(frame, mask);
        std::vector<std::vector<cv::Point>> contours;
        std::vector<cv::Vec4i> hierarchy;
        cv::findContours(mask, contours, hierarchy, cv::RETR_TREE, cv::CHAIN_APPROX_SIMPLE);
        for (auto &contour : contours) {
            if (cv::contourArea(contour) < 5000) {
                continue;
            }
            cv::Rect rect = cv::boundingRect(contour);
            last_coordinates.push_back(rect);
        }
        for (int i = 1; i < last_coordinates.size(); i++) {
            cv::line(frame, cv::Point(last_coordinates[i - 1].x, last_coordinates[i - 1].y),
                     cv::Point(last_coordinates[i].x, last_coordinates[i].y), cv::Scalar(0, 0, 255), 5);
        }
        cv::imshow("Video", frame);
        if (cv::waitKey(30) & 0xFF == 27) {
            break;
        }
    }

    cap.release();
    cv::destroyAllWindows();
    return 0;
}

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