feat: switch to face mesh for now

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Laureηt 2022-11-25 11:49:26 +01:00
parent 0ed01b9172
commit 95f8fdfbae
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@ -8,13 +8,17 @@ def main() -> None:
"""Main function.""" """Main function."""
mp_drawing = mp.solutions.drawing_utils # type: ignore mp_drawing = mp.solutions.drawing_utils # type: ignore
mp_drawing_styles = mp.solutions.drawing_styles # type: ignore mp_drawing_styles = mp.solutions.drawing_styles # type: ignore
mp_holistic = mp.solutions.holistic # type: ignore mp_face_mesh = mp.solutions.face_mesh # type: ignore
# open webcam # open webcam
cap = cv2.VideoCapture(0) cap = cv2.VideoCapture(0)
with mp_holistic.Holistic(min_detection_confidence=0.5, min_tracking_confidence=0.5) as holistic: with mp_face_mesh.FaceMesh(
max_num_faces=2, refine_landmarks=True, min_detection_confidence=0.5, min_tracking_confidence=0.5
) as face_mesh:
while cap.isOpened(): while cap.isOpened():
# read webcam # read webcam
success, image = cap.read() success, image = cap.read()
if not success: if not success:
@ -22,34 +26,40 @@ def main() -> None:
# If loading a video, use 'break' instead of 'continue' # If loading a video, use 'break' instead of 'continue'
continue continue
# to improve performance, optionally mark the image as not writeable to pass by reference # to improve performance, optionally mark the image as not writeable to pass by reference.
image.flags.writeable = False image.flags.writeable = False
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
results = holistic.process(image) results = face_mesh.process(image)
# log landmarks # draw the face mesh annotations on the image.
logging.debug(results.face_landmarks)
logging.debug(results.pose_landmarks)
# draw landmark annotation on the image
image.flags.writeable = True image.flags.writeable = True
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR) image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
mp_drawing.draw_landmarks( if results.multi_face_landmarks:
image, for face_landmarks in results.multi_face_landmarks:
results.face_landmarks, mp_drawing.draw_landmarks(
mp_holistic.FACEMESH_CONTOURS, image=image,
landmark_drawing_spec=None, landmark_list=face_landmarks,
connection_drawing_spec=mp_drawing_styles.get_default_face_mesh_contours_style(), connections=mp_face_mesh.FACEMESH_TESSELATION,
) landmark_drawing_spec=None,
mp_drawing.draw_landmarks( connection_drawing_spec=mp_drawing_styles.get_default_face_mesh_tesselation_style(),
image, )
results.pose_landmarks, mp_drawing.draw_landmarks(
mp_holistic.POSE_CONNECTIONS, image=image,
landmark_drawing_spec=mp_drawing_styles.get_default_pose_landmarks_style(), landmark_list=face_landmarks,
) connections=mp_face_mesh.FACEMESH_CONTOURS,
landmark_drawing_spec=None,
connection_drawing_spec=mp_drawing_styles.get_default_face_mesh_contours_style(),
)
mp_drawing.draw_landmarks(
image=image,
landmark_list=face_landmarks,
connections=mp_face_mesh.FACEMESH_IRISES,
landmark_drawing_spec=None,
connection_drawing_spec=mp_drawing_styles.get_default_face_mesh_iris_connections_style(),
)
# flip the image horizontally for a selfie-view display. # flip the image horizontally for a selfie-view display.
cv2.imshow("MediaPipe Holistic", cv2.flip(image, 1)) cv2.imshow("MediaPipe Face Mesh", cv2.flip(image, 1))
if cv2.waitKey(5) & 0xFF == 27: if cv2.waitKey(5) & 0xFF == 27:
break break
@ -60,7 +70,7 @@ def main() -> None:
if __name__ == "__main__": if __name__ == "__main__":
# setup logging format # setup logging format
logging.basicConfig( logging.basicConfig(
level=logging.DEBUG, level=logging.INFO,
format="%(asctime)s %(name)s %(levelname)-8s %(message)s", format="%(asctime)s %(name)s %(levelname)-8s %(message)s",
datefmt="(%F %T)", datefmt="(%F %T)",
) )