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# import cv2
# import mediapipe as mp
# mp_face_detection = mp.solutions.face_detection
# mp_drawing = mp.solutions.drawing_utils
# # Initialize the MTCNN detector
# # Create a VideoCapture object
# cap = cv2.VideoCapture(0)
# with mp_face_detection.FaceDetection(model_selection = 0 , min_detection_confidence = 0.5) as face_detection:
# while cap.isOpened():
# ret,image = cap.read()
# image.flags.writeable = False
# image = cv2.cvtColor(image,cv2.COLOR_BGR2RGB)
# results = face_detection.process(image)
# image.flags.writeable = True
# image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
# if results.detections:
# for face_no,face in enumerate(results.detections):
# mp_drawing.draw_detection(image = image,detection = face)
# cv2.imshow('Face Detection', cv2.flip(image,1))
# if cv2.waitKey(1) & 0xFF == ord('q'):
# break
# # Release the capture and close all OpenCV windows
# cap.release()
# cv2.destroyAllWindows()
import cv2
import mediapipe as mp
# Initialize MediaPipe Face Detection
mp_face_detection = mp.solutions.face_detection
mp_drawing = mp.solutions.drawing_utils
face_detection = mp_face_detection.FaceDetection(min_detection_confidence=0.5)
# Initialize webcam
cap = cv2.VideoCapture(0)
while cap.isOpened():
success, image = cap.read()
if not success:
print("Ignoring empty camera frame.")
continue
# Convert the BGR image to RGB
rgb_image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
# Perform face detection
results = face_detection.process(rgb_image)
# Draw the face detections
if results.detections:
for detection in results.detections:
mp_drawing.draw_detection(image, detection)
# Display the output
cv2.imshow('Face Detection', image)
# Press 'q' to exit
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# Release the webcam and close all windows
cap.release()
cv2.destroyAllWindows()