Face detection using Cascade Classifier in opencv python

Question

I am using the inbuilt cascade classifier for the face detection. This is how the code is (OpenCV Python Tutorials):

import numpy as np
import cv2

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

img = cv2.imread('ammma.jpg')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

faces = face_cascade.detectMultiScale(gray, 1.3, 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)
cv2.waitKey(0)
cv2.destroyAllWindows()

But when I run the code I am getting the following error:

C:\Python27\python.exe C:/Users/DELL/Downloads/Amma/code/fd.py

OpenCV Error: Assertion failed (!empty()) in cv::CascadeClassifier::detectMultiScale, file C:\builds\master_PackSlaveAddon-win32-vc12-static\opencv\modules\objdetect\src\cascadedetect.cpp, line 1634 Traceback (most recent call last): File "C:/Users/DELL/Downloads/Amma/code/fd.py", line 10, in faces = face_cascade.detectMultiScale(img, 1.3, 5) cv2.error: C:\builds\master_PackSlaveAddon-win32-vc12-static\opencv\modules\objdetect\src\cascadedetect.cpp:1634: error: (-215) !empty() in function cv::CascadeClassifier::detectMultiScale

Answer 1

Refer to this line of code, it failed on checking that cascade is non empty. Please check path to XML files with trained cascades. You may need to specify full path to XML's like this:

face_cascade = cv2.CascadeClassifier('D:\opencv\data\haarcascades\haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('D:\opencv\data\haarcascades\haarcascade_eye.xml')

Or just put this files to directory containig your script.

Answer 2

You do NOT need to download or copy the .xml files. According to the OpenCV-Python PyPi page, you can simply use the packaged path to the installed cascades - cv2.data.haarcascades:

import cv2

# Globals
FACE_CLASSIFIER = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
EYE_CLASSIFIER = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_eye.xml')
SCALE_FACTOR = 1.3
BLUE_COLOR = (255, 0, 0)
MIN_NEIGHBORS = 5

# Then use it however you'd like
try:
    faces = FACE_CLASSIFIER.detectMultiScale(gray, SCALE_FACTOR, MIN_NEIGHBORS)
    for (x, y, w, h) in faces:
        cv2.rectangle(self.roi_frame, (x, y), (x+w, y+h), BLUE_COLOR, HAAR_LINE_THICKNESS)
        roi_gray = gray[y:y+h, x:x+w]
        roi_color = self.roi_frame[y:y+h, x:x+w]
        eyes = EYE_CLASSIFIER.detectMultiScale(roi_gray)
        for (ex, ey, ew, eh) in eyes:
            cv2.rectangle(roi_color, (ex, ey), (ex+ew, ey+eh), GREEN_COLOR, HAAR_LINE_THICKNESS)
except Exception as e:
    warnings.warn('{}.show_haar_features: got exception {}'.format(__name__, e))