170 lines
5.0 KiB
Python
170 lines
5.0 KiB
Python
# vim: expandtab:ts=4:sw=4
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class TrackState:
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"""
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Enumeration type for the single target track state. Newly created tracks are
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classified as `tentative` until enough evidence has been collected. Then,
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the track state is changed to `confirmed`. Tracks that are no longer alive
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are classified as `deleted` to mark them for removal from the set of active
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tracks.
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"""
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Tentative = 1
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Confirmed = 2
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Deleted = 3
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class Track:
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"""
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A single target track with state space `(x, y, a, h)` and associated
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velocities, where `(x, y)` is the center of the bounding box, `a` is the
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aspect ratio and `h` is the height.
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Parameters
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----------
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mean : ndarray
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Mean vector of the initial state distribution.
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covariance : ndarray
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Covariance matrix of the initial state distribution.
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track_id : int
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A unique track identifier.
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n_init : int
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Number of consecutive detections before the track is confirmed. The
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track state is set to `Deleted` if a miss occurs within the first
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`n_init` frames.
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max_age : int
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The maximum number of consecutive misses before the track state is
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set to `Deleted`.
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feature : Optional[ndarray]
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Feature vector of the detection this track originates from. If not None,
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this feature is added to the `features` cache.
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Attributes
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----------
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mean : ndarray
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Mean vector of the initial state distribution.
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covariance : ndarray
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Covariance matrix of the initial state distribution.
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track_id : int
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A unique track identifier.
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hits : int
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Total number of measurement updates.
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age : int
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Total number of frames since first occurance.
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time_since_update : int
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Total number of frames since last measurement update.
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state : TrackState
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The current track state.
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features : List[ndarray]
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A cache of features. On each measurement update, the associated feature
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vector is added to this list.
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"""
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def __init__(self, mean, covariance, track_id, n_init, max_age,
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feature=None, cls=None, mask=None):
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self.mean = mean
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self.covariance = covariance
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self.track_id = track_id
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self.hits = 1
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self.age = 1
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self.time_since_update = 0
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self.state = TrackState.Tentative
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self.cls = cls
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self.mask = mask
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self.features = []
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if feature is not None:
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self.features.append(feature)
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self._n_init = n_init
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self._max_age = max_age
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def to_tlwh(self):
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"""Get current position in bounding box format `(top left x, top left y,
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width, height)`.
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Returns
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-------
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ndarray
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The bounding box.
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"""
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ret = self.mean[:4].copy()
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ret[2] *= ret[3]
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ret[:2] -= ret[2:] / 2
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return ret
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def to_tlbr(self):
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"""Get current position in bounding box format `(min x, miny, max x,
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max y)`.
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Returns
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-------
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ndarray
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The bounding box.
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"""
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ret = self.to_tlwh()
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ret[2:] = ret[:2] + ret[2:]
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return ret
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def predict(self, kf):
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"""Propagate the state distribution to the current time step using a
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Kalman filter prediction step.
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Parameters
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----------
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kf : kalman_filter.KalmanFilter
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The Kalman filter.
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"""
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self.mean, self.covariance = kf.predict(self.mean, self.covariance)
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self.age += 1
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self.time_since_update += 1
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def update(self, kf, detection):
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"""Perform Kalman filter measurement update step and update the feature
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cache.
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Parameters
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----------
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kf : kalman_filter.KalmanFilter
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The Kalman filter.
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detection : Detection
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The associated detection.
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"""
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self.mask = detection.mask
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self.mean, self.covariance = kf.update(
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self.mean, self.covariance, detection.to_xyah())
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self.features.append(detection.feature)
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self.hits += 1
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self.time_since_update = 0
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if self.state == TrackState.Tentative and self.hits >= self._n_init:
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self.state = TrackState.Confirmed
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def mark_missed(self):
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"""Mark this track as missed (no association at the current time step).
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"""
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if self.state == TrackState.Tentative:
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self.state = TrackState.Deleted
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elif self.time_since_update > self._max_age:
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self.state = TrackState.Deleted
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def is_tentative(self):
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"""Returns True if this track is tentative (unconfirmed).
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"""
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return self.state == TrackState.Tentative
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def is_confirmed(self):
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"""Returns True if this track is confirmed."""
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return self.state == TrackState.Confirmed
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def is_deleted(self):
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"""Returns True if this track is dead and should be deleted."""
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return self.state == TrackState.Deleted
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