def test_pnp():
# Test that facepose can be estimated properly using landmarks + pnp algorithm
detector = Detector(face_model="RetinaFace",
landmark_model="MobileFaceNet",
facepose_model="PnP")
bboxes = detector.detect_faces(frame=img01)
lms = detector.detect_landmarks(frame=img01, detected_faces=bboxes)
poses = detector.detect_facepose(frame=img01, landmarks=lms)
pose_to_test = poses[0][0] # first image and first face
pitch, roll, yaw = pose_to_test.reshape(-1)
assert -10 < pitch < 10
assert -5 < roll < 5
assert -10 < yaw < 10
def test_img2pose():
# Test that both face detection and facepose estimation work
detector = Detector(face_model="img2pose", facepose_model="img2pose")
# Face detection
faces = detector.detect_faces(img01)[0]
bbox_x = faces[0][0]
assert bbox_x is not None
assert len(faces[0]) == 5
assert 180 < bbox_x < 200
# Pose estimation
poses = detector.detect_facepose(img01)[0]
pose_to_test = poses[0][0] # first image and first face
pitch, roll, yaw = pose_to_test.reshape(-1)
assert -10 < pitch < 10
assert -5 < roll < 5
assert -10 < yaw < 10