dense-checkpoint2.py

import cv2 as cv
import numpy as np

# The video feed is read in as a VideoCapture object
# cap = cv.VideoCapture("shibuya.mp4")
# ret = a boolean return value from getting the frame, first_frame = the first frame in the entire video sequence
# ret, first_frame = cap.read()
# Converts frame to grayscale because we only need the luminance channel for detecting edges - less computationally expensive
prev_gray = cv.cvtColor(first_frame, cv.COLOR_BGR2GRAY)

# while(cap.isOpened()):
    # ret = a boolean return value from getting the frame, frame = the current frame being projected in the video
    # ret, frame = cap.read()
    # Opens a new window and displays the input frame
    # cv.imshow("input", frame)
    # Converts each frame to grayscale - we previously only converted the first frame to grayscale
    gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
    # Visualizes checkpoint 2
    cv.imshow("grayscale", gray)
    # Updates previous frame
    prev_gray = gray
    # Frames are read by intervals of 1 millisecond. The programs breaks out of the while loop when the user presses the 'q' key
    # if cv.waitKey(1) & 0xFF == ord('q'):
        # break
# The following frees up resources and closes all windows
# cap.release()
# cv.destroyAllWindows()