optic-flow.py

import cv2
import numpy as np
import matplotlib.pyplot as plt

a = []

cap = cv2.VideoCapture('clip.mp4')

ok, frame = cap.read()
parameters_shitomasi = dict(maxCorners=100, qualityLevel=0.3, minDistance=7)
frame_gray_init = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

# Use Shi-Tomasi to detect object corners / edges from initial frame
edges = cv2.goodFeaturesToTrack(frame_gray_init, mask = None, **parameters_shitomasi)
# create a black canvas the size of the initial frame
canvas = np.zeros_like(frame)
# create random colours for visualization for all 100 max corners for RGB channels
colours = np.random.randint(0, 255, (100, 3))

parameter_lucas_kanade = dict(winSize=(15, 15), maxLevel=2, criteria=(cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03))




def select_point(event, x, y, flags, params):
    global point, selected_point, old_points
    # record coordinates of mouse click
    if event == cv2.EVENT_LBUTTONDOWN:
        point = (x, y)
        selected_point = True
        old_points = np.array([[x, y]], dtype=np.float32)


# associate select function with window Selector
cv2.namedWindow('Optical Flow')
cv2.setMouseCallback('Optical Flow', select_point)

# initialize variables updated by function
selected_point = False
point = ()
old_points = ([[]])

while True:
    # get next frame
    ok, frame = cap.read()
    if ok:
        # covert to grayscale
        frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    
        if selected_point is True:
            cv2.circle(frame, point, 5, (0, 0, 255), 2)
            # update object corners by comparing with found edges in initial frame
            new_points, status, errors = cv2.calcOpticalFlowPyrLK(frame_gray_init, frame_gray, old_points, None,
                                                             **parameter_lucas_kanade)
    
            # overwrite initial frame with current before restarting the loop
            frame_gray_init = frame_gray.copy()
            # update to new edges before restarting the loop
            old_points = new_points
    
            x, y = new_points.ravel()
            j, k = old_points.ravel()
    
            # draw line between old and new corner point with random colour
            canvas = cv2.line(canvas, (int(x), int(y)), (int(j), int(k)), (0, 255, 0), 3)
            # draw circle around new position
            frame = cv2.circle(frame, (int(x), int(y)), 5, (0, 255, 0), -1)
            a.append(y)
    
        result = cv2.add(frame, canvas)
        cv2.imshow('Optical Flow', result)
        
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    else:
        break

cap.release()
cv2.destroyAllWindows()
plt.plot(a)
plt.title("point location")
plt.xlabel("frame")
plt.ylabel("y-location")
plt.show()