main.py

#https://pysource.com/2021/10/29/kalman-filter-predict-the-trajectory-of-an-object/
from kalmanfilter import KalmanFilter
import cv2

# Kalman Filter
kf = KalmanFilter()

img = cv2.imread("blue_background.webp")

ball2_positions = [(4, 300), (61, 256), (116, 214), (170, 180), (225, 148), (279, 120), (332, 97),
         (383, 80), (434, 66), (484, 55), (535, 49), (586, 49), (634, 50),
         (683, 58), (731, 69), (778, 82), (824, 101), (870, 124), (917, 148),
         (962, 169), (1006, 212), (1051, 249), (1093, 290)]

for pt in ball2_positions:
    cv2.circle(img, pt, 15, (0, 20, 220), -1)
    predicted = kf.predict(pt[0], pt[1])

    cv2.circle(img, predicted, 15, (20, 220, 0), 4)

for i in range(10):
    predicted = kf.predict(predicted[0], predicted[1])
    cv2.circle(img, predicted, 15, (20, 220, 0), 4)

    print(predicted)


cv2.imshow("Img", img)

while True:
    if cv2.waitKey(0) & 0xFF == ord('q'):
        break 

cv2.destroyAllWindows()