Haar- Cascade face detection OpenCv

Question

I used the following code to detect a face using Haar cascade classifiers provided by OpenCv Python. But the faces are not detected and the square around the face is not drawn. How to solve this?

import cv2

index=raw_input("Enter the index No. : ")

cascPath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascPath)

cap = cv2.VideoCapture(0)

cont=0

while(True):
   # Capture frame-by-frame
   ret, frame = cap.read()

   # Our operations on the frame come here
   gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

   faces = faceCascade.detectMultiScale(
  gray,
  scaleFactor=1.1,
  minNeighbors=10,
  minSize=(30, 30),
  flags = cv2.cv.CV_HAAR_SCALE_IMAGE
  )

for (x, y, w, h) in faces:
    #cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
    cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)


   # Display the resulting frame
  cv2.imshow('frame',frame)
  inpt=cv2.waitKey(1)

  if inpt & 0xFF == ord('q'):
    break

  elif inpt & 0xFF == ord('s') :

    #name='G:\XCODRA\Integrated_v_01\EigenFaceRecognizer\img2'+index+"."+(str(cont))+".png"
    name='IC_image\\'+index+"."+(str(cont))+".png"
    resized = cv2.resize(gray,None,fx=200, fy=200, interpolation = cv2.INTER_AREA)
    img=cv2.equalizeHist(resized)

    cv2.imwrite(name,img)
    print cont
    cont+=1

Answer 1

you can use the code and try if it works for you.

from __future__ import print_function
import cv2 as cv
import argparse
import numpy as np
import pywt


def detectAndDisplay(frame):
    frame_gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
    frame_gray = cv.equalizeHist(frame_gray)
    # -- Detect faces
    faces = face_cascade.detectMultiScale(frame_gray)
    for (x, y, w, h) in faces:
        center = (x + w//2, y + h//2)
        frame = cv.ellipse(frame, center, (w//2, h//2),
                           0, 0, 360, (255, 0, 0), 4)
        faceROI = frame_gray[y:y+h, x:x+w]
        # -- In each face, detect eyes
        eyes = eyes_cascade.detectMultiScale(faceROI)
        for (x2, y2, w2, h2) in eyes:
            eye_center = (x + x2 + w2//2, y + y2 + h2//2)
            radius = int(round((w2 + h2)*0.25))
            frame = cv.circle(frame, eye_center, radius, (0, 255, 0), 10)
    cv.imshow('Capture - Face detection', frame)


parser = argparse.ArgumentParser(
    description='Code for Cascade Classifier tutorial.')
parser.add_argument('--face_cascade', help='Path to face cascade.',
                    default='./opencv/haarcascade/haarcascade_frontalface_default.xml')
parser.add_argument('--eyes_cascade', help='Path to eyes cascade.',
                    default='./opencv/haarcascade/haarcascade_eye.xml')
parser.add_argument(
    '--camera', help='Camera divide number.', type=int, default=0)
args = parser.parse_args()
face_cascade_name = args.face_cascade
eyes_cascade_name = args.eyes_cascade
face_cascade = cv.CascadeClassifier()
eyes_cascade = cv.CascadeClassifier()
# -- 1. Load the cascades
if not face_cascade.load(cv.samples.findFile(face_cascade_name)):
    print('--(!)Error loading face cascade')
    exit(0)
if not eyes_cascade.load(cv.samples.findFile(eyes_cascade_name)):
    print('--(!)Error loading eyes cascade')
    exit(0)
camera_device = args.camera
# -- 2. Read the video stream
cap = cv.VideoCapture(camera_device)
if not cap.isOpened:
    print('--(!)Error opening video capture')
    exit(0)
while True:
    ret, frame = cap.read()
    if frame is None:
        print('--(!) No captured frame -- Break!')
        break
    detectAndDisplay(frame)
    if cv.waitKey(10) == 27:
        break

Answer 2

Use the full path for the classifier.