import?cv2
import?numpy?as?np

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

#?初始化測(cè)量坐標(biāo)和鼠標(biāo)運(yùn)動(dòng)預(yù)測(cè)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(biāo)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(dāng)前預(yù)測(cè)存儲(chǔ)為上一次預(yù)測(cè)
????last_measurement?=?current_measurement?#?把當(dāng)前測(cè)量存儲(chǔ)為上一次測(cè)量
????current_measurement?=?np.array（[[np.float32（x）]?[np.float32（y）]]）?#?當(dāng)前測(cè)量
????kalman.correct（current_measurement）?#?用當(dāng)前測(cè)量來校正卡爾曼濾波器
????current_prediction?=?kalman.predict（）?#?計(jì)算卡爾曼預(yù)測(cè)值，作為當(dāng)前預(yù)測(cè)

????lmx?lmy?=?last_measurement[0]?last_measurement[1]?#?上一次測(cè)量坐標(biāo)
????cmx?cmy?=?current_measurement[0]?current_measurement[1]?#?當(dāng)前測(cè)量坐標(biāo)
????lpx?lpy?=?last_prediction[0]?last_prediction[1]?#?上一次預(yù)測(cè)坐標(biāo)
????cpx?cpy?=?cu