<commit_before># <NAME>
# 9/6/15
# FacialDetection

import cv2

cascadePath = 'haarcascade_frontalface_default.xml'
faceCascade = cv2.CascadeClassifier(cascadePath)

video_capture = cv2.VideoCaptureq(0)

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

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    faces = faceCascade.detectMultiScale(
        gray,
        scaleFactor=1.1,
        minNeighbors=5,
        minSize=(30, 30)
    )

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

    # Display the resulting frame
    cv2.imshow('Facial Detection', frame)

    # When 'q' on the keyboard is hit the loop is exited
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
<commit_msg>fix typo<commit_after># <NAME>
# 9/6/15
# FacialDetection

import cv2

cascadePath = 'haarcascade_frontalface_default.xml'
faceCascade = cv2.CascadeClassifier(cascadePath)

video_capture = cv2.VideoCapture(0)

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

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    faces = faceCascade.detectMultiScale(
        gray,
        scaleFactor=1.1,
        minNeighbors=5,
        minSize=(30, 30)
    )

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

    # Display the resulting frame
    cv2.imshow('Facial Detection', frame)

    # When 'q' on the keyboard is hit the loop is exited
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

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