opencv
कैस्केड क्लासिफायर
खोज…
चेहरे का पता लगाने के लिए कैस्केड क्लासिफायर का उपयोग करना
अजगर
कोड
import numpy as np
import cv2
#loading haarcascade classifiers for face and eye
#You can find these cascade classifiers here
#https://github.com/opencv/opencv/tree/master/data/haarcascades
#or where you download opencv inside data/haarcascades
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
#loading the image
img = cv2.imread('civil_war.jpg')
#converting the image to gray scale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
#detecting face in the grayscale image
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
#iterate through each detected face
for (x,y,w,h) in faces:
cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2) #draw rectangle to each detected face
#take the roi of the face (region of interest)
roi_gray = gray[y:y+h, x:x+w]
roi_color = img[y:y+h, x:x+w]
#detect the eyes
eyes = eye_cascade.detectMultiScale(roi_gray)
for (ex,ey,ew,eh) in eyes:
#draw rectangle for each eye
cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
#show the image
cv2.imshow('img',img)
cv2.waitKey(0)
cv2.destroyAllWindows()
परिणाम
जावा के साथ चेहरे का पता लगाने के लिए कैस्केड क्लासिफायर
जावा
कोड
import org.opencv.core.Mat;
import org.opencv.core.MatOfRect;
import org.opencv.core.Point;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.highgui.Highgui;
import org.opencv.highgui.VideoCapture;
import org.opencv.objdetect.CascadeClassifier;
public class FaceDetector{
public static void main(String[] args) {
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
//Create object
CascadeClassifier faceDetector = new CascadeClassifier(FaceDetector.class.getResource("haarcascade_frontalface_default.xml").getPath());
//Read image
Mat image = Highgui.imread("sourceimage.jpg");
/*
//Or read from webcam
* Mat image=new Mat();
*VideoCapture videoCapture=new VideoCapture(0);
*videoCapture.read(image);
*/
MatOfRect faceDetections = new MatOfRect();
//Result list
faceDetector.detectMultiScale(image, faceDetections);
for (Rect rect : faceDetections.toArray()) {
//Draw rectangle on result
Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height),
new Scalar(0, 255, 0));
}
//write result
Highgui.imwrite("result.png", image);
System.out.println("Succesfull");
}
}
परिणाम
हार कास्केड क्लासिफायर का उपयोग करके चेहरा पहचानना
सी ++
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
using namespace std;
using namespace cv;
// Function Headers
void detectAndDisplay(Mat frame);
// Global variables
string face_cascade_name = "./data/haarcascade_frontalface_alt2.xml";
CascadeClassifier face_cascade;
// Function main
int main(void)
{
// Load the cascade
if (!face_cascade.load(face_cascade_name)){
printf("--(!)Error on cascade loading\n");
return (-1);
}
// Read the image file
Mat frame = imread("d:/obama_01.jpg");
// Apply the classifier to the frame
if (!frame.empty())
detectAndDisplay(frame);
waitKey(0);
return 0;
}
// Function detectAndDisplay
void detectAndDisplay(Mat frame)
{
std::vector<Rect> faces;
Mat frame_gray;
cvtColor(frame, frame_gray, COLOR_BGR2GRAY);
equalizeHist(frame_gray, frame_gray);
// Detect faces
face_cascade.detectMultiScale(frame_gray, faces, 1.1, 2, 0 | CASCADE_SCALE_IMAGE, Size(30, 30));
for (int ic = 0; ic < faces.size(); ic++) // Iterate through all current elements (detected faces)
{
Point pt1(faces[ic].x, faces[ic].y); // Display detected faces on main window - live stream from camera
Point pt2((faces[ic].x + faces[ic].height), (faces[ic].y + faces[ic].width));
rectangle(frame, pt1, pt2, Scalar(0, 255, 0), 2, 8, 0);
}
imshow("original", frame);
}
Modified text is an extract of the original Stack Overflow Documentation
के तहत लाइसेंस प्राप्त है CC BY-SA 3.0
से संबद्ध नहीं है Stack Overflow