56 lines
1.8 KiB
Python
56 lines
1.8 KiB
Python
import cv2
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import numpy as np
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from 视觉代码python.config import KF_PROCESS_NOISE, KF_MEASUREMENT_NOISE
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class KalmanFilter:
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"""卡尔曼滤波器：平滑并预测装甲板位置"""
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def __init__(self):
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self.kf = cv2.KalmanFilter(4, 2) # 4状态(x,y,dx,dy)，2测量(x,y)
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self._init_params()
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self.initialized = False
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self.last_measurement = None
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self.last_prediction = None
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def _init_params(self):
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"""初始化卡尔曼参数"""
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self.kf.transitionMatrix = np.array([
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[1, 0, 1, 0],
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[0, 1, 0, 1],
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[0, 0, 1, 0],
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[0, 0, 0, 1]
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], np.float32)
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self.kf.measurementMatrix = np.array([
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[1, 0, 0, 0],
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[0, 1, 0, 0]
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], np.float32)
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self.kf.processNoiseCov = np.eye(4, dtype=np.float32) * KF_PROCESS_NOISE
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self.kf.measurementNoiseCov = np.eye(2, dtype=np.float32) * KF_MEASUREMENT_NOISE
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self.kf.errorCovPost = np.eye(4, dtype=np.float32)
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def update(self, measurement):
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"""用测量值更新滤波器"""
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measurement = np.array([[np.float32(measurement[0])], [np.float32(measurement[1])]])
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if not self.initialized:
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self.kf.statePost = np.array([
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[measurement[0, 0]],
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[measurement[1, 0]],
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[0.0],
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[0.0]
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], np.float32)
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self.initialized = True
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else:
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self.kf.correct(measurement)
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self.last_measurement = (measurement[0, 0], measurement[1, 0])
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def predict(self):
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"""预测下一帧位置"""
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if not self.initialized:
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return None
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prediction = self.kf.predict()
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self.last_prediction = (prediction[0, 0], prediction[1, 0])
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return self.last_prediction |