Environment

  • Python 2.7.15
  • Windows 10
  • opencv 3.4.3

Steps

  1. Start command prompt
  2. Install opencv. Reference the post face detection in python using webcam
  3. Create folder Image-Face-Detect
  4. Change to Image-Face-Detect folder 
    cd Image-Face-Detect
  5. Copy files haarcascade_frontalface_default.xml and haarcascade_eye.xml from C:\Users\user\Downloads\opencv\sources\data\haarcascades folder to D:\Temp\Image-Face-Detect
  6. Create file image_cv3.py
import numpy as np
import cv2
from matplotlib import pyplot as plt

face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')

img = cv2.imread('harry-meghan-15.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

faces = face_cascade.detectMultiScale(gray, 1.1, 5)


for (x,y,w,h) in faces:
    cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
    roi_gray = gray[y:y+h, x:x+w]
    roi_color = img[y:y+h, x:x+w]
    eyes = eye_cascade.detectMultiScale(roi_gray)
    for (ex,ey,ew,eh) in eyes:
        cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)

cv2.imshow('img',img)
# waitKey(0) will display the window infinitely until any keypress
cv2.waitKey(0)
if cv2.waitKey(1) & 0xFF == ord('q'):
        break
cv2.destroyAllWindows()
  1. Start face detection 
    c:\Python27\python.exe image_cv3.py

    python-face-detection-image-1.1

  2. If I decrease the scaleFactor parameter to 1.01, I will get more detect regions. python-face-detection-image-1.01

Parameters

  • scaleFactor: Parameter specifying how much the image size is reduced at each image scale.
  • minNeighbors: Parameter specifying how many neighbors each candidate rectangle should have to retain it.This parameter will affect the quality of the detected faces: higher value results in less detections but with higher quality.
  • minSize : Minimum possible object size. Objects smaller than that are ignored.

Reference