import?cv2
import?numpy?as?np

#?創(chuàng)建一個空幀，定義（700?700?3）畫圖區(qū)域
frame?=?np.zeros（（700?700?3）?np.uint8）?

#?初始化測量坐標和鼠標運動預(yù)測的數(shù)組
last_measurement?=?current_measurement?=?np.array（（2?1）?np.float32）
last_prediction?=?current_prediction?=?np.zeros（（2?1）?np.float32）

#?定義鼠標回調(diào)函數(shù)，用來繪制跟蹤結(jié)果
def?mousemove（event?x?y?s?p）:
????global?frame?current_measurement?measurements?last_measurement?current_prediction?last_prediction
????last_prediction?=?current_prediction?#?把當前預(yù)測存儲為上一次預(yù)測
????last_measurement?=?current_measurement?#?把當前測量存儲為上一次測量
????current_measurement?=?np.array（[[np.float32（x）]?[np.float32（y）]]）?#?當前測量
????kalman.correct（current_measurement）?#?用當前測量來校正卡爾曼濾波器
????current_prediction?=?kalman.predict（）?#?計算卡爾曼預(yù)測值，作為當前預(yù)測

????lmx?lmy?=?last_measurement[0]?last_measurement[1]?#?上一次測量坐標
????cmx?cmy?=?current_measurement[0]?current_measurement[1]?#?當前測量坐標
????lpx?lpy?=?last_prediction[0]?last_prediction[1]?#?上一次預(yù)測坐標
????cpx?cpy?=?cu