Face detection using Haar Cascades – OpenCV 3.4 with python 3 Tutorial 37
You will learn in this video how to detect Faces using the Haar Cascades object detection method.
Source code:
import cv2 import numpy as np def nothing(x): pass cap = cv2.VideoCapture(0) face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml") cv2.namedWindow("Frame") cv2.createTrackbar("Neighbours", "Frame", 5, 20, nothing) while True: _, frame = cap.read() gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) neighbours = cv2.getTrackbarPos("Neighbours", "Frame") faces = face_cascade.detectMultiScale(gray, 1.3, neighbours) for rect in faces: (x, y, w, h) = rect frame = cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2) cv2.imshow("Frame", frame) key = cv2.waitKey(1) if key == 27: break cap.release() cv2.destroyAllWindows()