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rasberry pi face detection

Michael Manders answered on June 30, 2023 Popularity 4/10 Helpfulness 1/10

answer rasberry pi face detection

rasberry pi face detection

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import cv2

# Load the pre-trained Haar cascade classifier for detecting faces
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')

# Start the video capture from the default camera (index 0)
video_capture = cv2.VideoCapture(0)

while True:
    # Read a frame from the video capture
    ret, frame = video_capture.read()

    # Convert the frame to grayscale
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # Detect faces in the grayscale frame
    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))

    # Iterate over the detected faces and draw rectangles around them
    for (x, y, w, h) in faces:
        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)

        # Calculate the coordinates of the person
        center_x = x + w / 2
        center_y = y + h / 2

        # Display the coordinates on the frame
        cv2.putText(frame, f"({center_x:.2f}, {center_y:.2f})", (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2)

    # Display the frame with the detected faces
    cv2.imshow('Video', frame)

    # Break the loop if 'q' is pressed
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# Release the video capture and close the OpenCV windows
video_capture.release()
cv2.destroyAllWindows()

Popularity 4/10 Helpfulness 1/10 Language python

Source: chat.openai.com

Tags: face-detection pi python

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Contributed on Jun 30 2023

Michael Manders

0 Answers Avg Quality 2/10

rasberry pi face detection

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