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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) | |
# Calculates dense optical flow by Farneback method | |
# https://docs.opencv.org/3.0-beta/modules/video/doc/motion_analysis_and_object_tracking.html#calcopticalflowfarneback | |
flow = cv.calcOpticalFlowFarneback(prev_gray, gray, None, 0.5, 3, 15, 3, 5, 1.2, 0) | |
# 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() |
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