ENSEEIHT/projet-transversal
1
0
Fork 0
Code Issues Pull requests Packages Projects Releases Wiki Activity

chore: move code to main function

Browse source
This commit is contained in:
Laureηt 2022-11-25 11:20:04 +01:00
parent 434cea77c1
commit 0ed01b9172
No known key found for this signature in database
GPG key ID: D88C6B294FD40994
1 changed files with 59 additions and 39 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

98
src/main.py
View file

@ -1,48 +1,68 @@
import logging
import cv2 import cv2
import mediapipe as mp import mediapipe as mp
mp_drawing = mp.solutions.drawing_utils # type: ignore
mp_drawing_styles = mp.solutions.drawing_styles # type: ignore
mp_holistic = mp.solutions.holistic # type: ignore
# open webcam def main() -> None:
cap = cv2.VideoCapture(0) """Main function."""
mp_drawing = mp.solutions.drawing_utils # type: ignore
mp_drawing_styles = mp.solutions.drawing_styles # type: ignore
mp_holistic = mp.solutions.holistic # type: ignore
with mp_holistic.Holistic(min_detection_confidence=0.5, min_tracking_confidence=0.5) as holistic: # open webcam
while cap.isOpened(): cap = cv2.VideoCapture(0)
# read webcam
success, image = cap.read()
if not success:
print("Ignoring empty camera frame.")
# If loading a video, use 'break' instead of 'continue'
continue
# to improve performance, optionally mark the image as not writeable to pass by reference with mp_holistic.Holistic(min_detection_confidence=0.5, min_tracking_confidence=0.5) as holistic:
image.flags.writeable = False while cap.isOpened():
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) # read webcam
results = holistic.process(image) success, image = cap.read()
if not success:
print("Ignoring empty camera frame.")
# If loading a video, use 'break' instead of 'continue'
continue
# draw landmark annotation on the image # to improve performance, optionally mark the image as not writeable to pass by reference
image.flags.writeable = True image.flags.writeable = False
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR) image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
mp_drawing.draw_landmarks( results = holistic.process(image)
image,
results.face_landmarks,
mp_holistic.FACEMESH_CONTOURS,
landmark_drawing_spec=None,
connection_drawing_spec=mp_drawing_styles.get_default_face_mesh_contours_style(),
)
mp_drawing.draw_landmarks(
image,
results.pose_landmarks,
mp_holistic.POSE_CONNECTIONS,
landmark_drawing_spec=mp_drawing_styles.get_default_pose_landmarks_style(),
)
# flip the image horizontally for a selfie-view display. # log landmarks
cv2.imshow("MediaPipe Holistic", cv2.flip(image, 1)) logging.debug(results.face_landmarks)
if cv2.waitKey(5) & 0xFF == 27: logging.debug(results.pose_landmarks)
break
# close webcam # draw landmark annotation on the image
cap.release() image.flags.writeable = True
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
mp_drawing.draw_landmarks(
image,
results.face_landmarks,
mp_holistic.FACEMESH_CONTOURS,
landmark_drawing_spec=None,
connection_drawing_spec=mp_drawing_styles.get_default_face_mesh_contours_style(),
)
mp_drawing.draw_landmarks(
image,
results.pose_landmarks,
mp_holistic.POSE_CONNECTIONS,
landmark_drawing_spec=mp_drawing_styles.get_default_pose_landmarks_style(),
)
# flip the image horizontally for a selfie-view display.
cv2.imshow("MediaPipe Holistic", cv2.flip(image, 1))
if cv2.waitKey(5) & 0xFF == 27:
break
# close webcam
cap.release()
if __name__ == "__main__":
# setup logging format
logging.basicConfig(
level=logging.DEBUG,
format="%(asctime)s %(name)s %(levelname)-8s %(message)s",
datefmt="(%F %T)",
)
main()