OpenCV & Python : Face Detection using haarcascades is detecting many boxes as eyes.

I am using Haarcascades for detecting faces and eyes. My problem is, its bounding many boxes as eyes. My syntax is

face_cascade = cv2.CascadeClassifier('haarcascades\haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascades\haarcascade_eye.xml')
img = cv2.imread('SAM7.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray,1.2,6)

I am currently using 1.2 and 6. What should be the value of the parameters in faces(5 line) like scaleFactor, minNeighbors ??

You really need to play with the parameters and find the ones works fine for you. Always there is a better way to do it but remember you'll never achieve 100% accuracy. You can learn about the parameters here.

An example of face and eyes detection in python that works for me:

    import cv2

    face_cascade = cv2.CascadeClassifier("../haarcascades/haarcascade_frontalface_default.xml")
    eye_cascade = cv2.CascadeClassifier("../haarcascades/haarcascade_eye.xml") 

    cap = cv2.VideoCapture(0)

        while cap.isOpened():
            ret, frame = cap.read()
            if ret:
                gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
                faces = face_cascade.detectMultiScale(
                        gray,
                        scaleFactor=1.3,
                        minNeighbors=5,
                        minSize=(50, 50)
                       )

                for (x, y, w, h) in faces:
                    cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0),2)
                    roi_gray = gray[y:y + h, x:x + w]
                    roi_color = frame[y:y + h, x:x + w]
                    eyes = eye_cascade.detectMultiScale(
                           roi_gray,
                           scaleFactor=1.2,
                           minNeighbors=5,
                           minSize=(10, 10)
                           )

                    for (ex, ey, ew, eh) in eyes:
                        cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (255, 0, 0), 2)

            cv2.imshow("Faces found", frame)

            k = cv2.waitKey(10) & 0xff
            if k == 27:
                break

    cv2.destroyAllWindows()
    cap.release()   

I hope this helps you. If you need help with the code let me know.