def correct(self, measure):
"""Correct the model based on real measures."""
measures_array = np.array([measure.x, measure.y, measure.w, measure.h],
dtype=np.float32)
estimated = self.kalman_filter.correct(measures_array)
estimated = KalmanTracker.__decapsulate_measure(estimated)
self.act_prediction = Region.from_matrix(estimated)
return self.act_prediction
def predict(self):
"""Predict next position and size of tracked object."""
prediction_raw = self.kalman_filter.predict()
self.kalman_filter.statePost = np.copy(self.kalman_filter.statePre)
self.kalman_filter.errorCovPost = np.copy(
self.kalman_filter.errorCovPre)
prediction_decapsulated = KalmanTracker.__decapsulate_measure(
prediction_raw)
prediction_wrap = Region.from_matrix(prediction_decapsulated)
self.act_prediction = prediction_wrap
# Collect last history:
if self.prediction_history.full():
self.prediction_history.get()
self.prediction_history.put(self.act_prediction)
return self.act_prediction
