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demo_framediff_video.py
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demo_framediff_video.py
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# Background Subtraction using pybgs library
# This script demonstrates the usage of the pybgs library for background subtraction in a video.
# It processes a video file, extracts the moving objects by applying the FrameDifference algorithm,
# and displays the original video, the foreground mask, and the background model in real-time.
# Import necessary libraries
import numpy as np
import cv2
import pybgs as bgs
# Initialize the background subtraction algorithm
algorithm = bgs.FrameDifference()
video_file = "dataset/video.avi"
# Create a video capture object to read the video file
capture = cv2.VideoCapture(video_file)
# Wait for the video file to be opened
while not capture.isOpened():
capture = cv2.VideoCapture(video_file)
cv2.waitKey(1000)
print("Waiting for the video to be loaded...")
# Main loop to process the video frames
while True:
# Read a new frame
flag, frame = capture.read()
# If a frame was successfully read
if flag:
# Display the original video frame
cv2.imshow('Original Video', frame)
# Apply the background subtraction algorithm
img_output = algorithm.apply(frame)
# Retrieve the current background model
img_bgmodel = algorithm.getBackgroundModel()
# Display the foreground mask and the background model
cv2.imshow('Foreground Mask', img_output)
cv2.imshow('Background Model', img_bgmodel)
else:
# Wait for a bit and exit the loop if no frame is captured
cv2.waitKey(1000)
print("No more frames to read or error in reading the frame.")
break
# Break the loop if the user presses 'Esc'
if cv2.waitKey(10) & 0xFF == 27:
print("Exiting...")
break
# Clean up: close all OpenCV windows and release the video capture object
cv2.destroyAllWindows()
capture.release()