def extract_features(face_id, image_id, face_top, face_left, face_height, face_width, image_height, image_width, landmarks):
features = feature_comp.compute(landmarks)
if not features: return
cursor.execute('INSERT INTO `features`(face_id, d_eyes_1, d_eyes_2, width_eye_left, width_eye_right, angle_chin_1, angle_chin_2, angle_chin_3, len_nose) VALUES (%d, %f, %f, %f, %f, %f, %f, %f, %f)'%(face_id, features['d_eyes_1'], features['d_eyes_2'], features['width_eye_left'], features['width_eye_right'], features['angle_chin_1'], features['angle_chin_2'],features['angle_chin_3'], features['len_nose']))
faces_obj = []
for i, face in enumerate(faces):
face_top = face.top()
face_left = face.left()
face_width = face.width()
face_height = face.height()
landmarks = deserialize(serialize(predictor(img, face)))
scaleX = 150 / face_width
scaleY = 150 / face_height
landmarks = scale(landmarks, scaleX, scaleY)
features = feature_comp.compute(landmarks)
face = {
'face_top': face_top,
'face_left': face_left,
'face_width': face_width,
'face_height': face_height,
'features': features
}
faces_obj.append(face)
res = {
'faces': faces_obj,
'image_height': img_height,
'image_width': img_width
}
