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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Aug 3 21:01:48 2024
@author: ysnrfd
"""
import cv2
import numpy as np
def main():
# Initialize video capture
cap = cv2.VideoCapture(0)
# Create background subtractor with KNN
backSub = cv2.createBackgroundSubtractorKNN(history=500, dist2Threshold=.512, detectShadows=True)
if not cap.isOpened():
print("Error: Unable to open camera.")
return
try:
while True:
# Read frame from the camera
ret, frame = cap.read()
if not ret:
print("Error: Unable to read frame.")
break
# Apply background subtraction
fgMask = backSub.apply(frame)
# Apply morphological operations
kernel = np.ones((5, 5), np.uint8)
fgMask = cv2.morphologyEx(fgMask, cv2.MORPH_CLOSE, kernel)
fgMask = cv2.morphologyEx(fgMask, cv2.MORPH_OPEN, kernel)
# Apply Gaussian blur to reduce noise
blurred = cv2.GaussianBlur(fgMask, (5, 5), 0)
# Find contours
contours, _ = cv2.findContours(blurred, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# Draw bounding boxes around detected objects
for contour in contours:
if cv2.contourArea(contour) > 500: # Filter out small contours
x, y, w, h = cv2.boundingRect(contour)
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
# Display the results
cv2.imshow('Frame', frame)
cv2.imshow('Foreground Mask', fgMask)
# Exit loop if 'q' is pressed
if cv2.waitKey(1) & 0xFF == ord('q'):
break
finally:
# Release resources
cap.release()
cv2.destroyAllWindows()
if __name__ == "__main__":
main()
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