singleface.py 文件源码

def format_image(image):
    """
    Function to format frame
    """
    if len(image.shape) > 2 and image.shape[2] == 3:
        # determine whether the image is color
        image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    else:
        # Image read from buffer
        image = cv2.imdecode(image, cv2.CV_LOAD_IMAGE_GRAYSCALE)

    faces = cascade_classifier.detectMultiScale(image,scaleFactor = 1.3 ,minNeighbors = 5)

    if not len(faces) > 0:
        return None

    # initialize the first face as having maximum area, then find the one with max_area
    max_area_face = faces[0]
    for face in faces:
        if face[2] * face[3] > max_area_face[2] * max_area_face[3]:
            max_area_face = face
    face = max_area_face

    # extract ROI of face
    image = image[face[1]:(face[1] + face[2]), face[0]:(face[0] + face[3])]

    try:
        # resize the image so that it can be passed to the neural network
        image = cv2.resize(image, (48,48), interpolation = cv2.INTER_CUBIC) / 255.
    except Exception:
        print("----->Problem during resize")
        return None

    return image

# Initialize object of EMR class