kaushil24

# parent_serializer.py
class MetaObj():
  pass

class ParentSerializer(serializers.ModelSerializer):
    def __init__(self, *args, **kwargs):
        meta_obj = MetaObj()
        meta_obj.model = ParentModel
        meta_obj.fields = ["field_1", "field_2"]
        meta_obj.read_only_fields = ["field 3", "field_4"]

kaushil24

def drawEyeliner(img, interp_pts):
    L_eye_interp, R_eye_interp = interp_pts

    L_interp_x, L_interp_top_y, L_interp_bottom_y = L_eye_interp
    R_interp_x, R_interp_top_y, R_interp_bottom_y = R_eye_interp

    overlay = img.copy()
    # overlay = np.empty(img.shape)
    # overlay = np.zeros_like(img)

kaushil24

def getEyelinerPoints(eye_landmark_points):
    '''
    Takes an array of eye coordinates and interpolates them:
    '''
    L_eye_top, L_eye_bottom, R_eye_top, R_eye_bottom = eye_landmark_points

    L_interp_x = np.arange(L_eye_top[0][0], L_eye_top[-1][0], 1)
    R_interp_x = np.arange(R_eye_top[0][0], R_eye_top[-1][0], 1)

    L_interp_top_y = interpolateCoordinates(L_eye_top, L_interp_x)

kaushil24

from scipy.interpolate import interp1d

def interpolateCoordinates(xy_coords, x_intrp):
    x = xy_coords[:, 0]
    y = xy_coords[:, 1]
    intrp = interp1d(x, y, kind='quadratic')
    y_intrp = intrp(x_intrp)
    y_intrp = np.floor(y_intrp).astype(int)
    return y_intrp

kaushil24

def getEyeLandmarkPts(face_landmark_points):
    '''
    Input: Coordinates of Bounding Box single face
    Returns: eye's landmark points
    '''
    face_landmark_points[36][0]-=5
    face_landmark_points[39][0]+=5
    face_landmark_points[42][0]-=5
    face_landmark_points[45][0]+=5
    

kaushil24

face_detector = dlib.get_frontal_face_detector()
lndMrkDetector = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")

def Eyeliner(frame):
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    bounding_boxes = face_detector(gray, 0)# The 2nd argument means that we upscale the image by 'x' number of times to detect more faces.
    if bounding_boxes:    
        for i, bb in enumerate(bounding_boxes):
            face_landmark_points = lndMrkDetector(gray, bb)
            face_landmark_points = face_utils.shape_to_np(face_landmark_points)