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import numpy as np | |
from collections import OrderedDict | |
class TrackState(object): | |
New = 0 | |
Tracked = 1 | |
Lost = 2 | |
Removed = 3 | |
class BaseTrack(object): | |
_count = 0 | |
track_id = 0 | |
is_activated = False | |
state = TrackState.New | |
history = OrderedDict() | |
features = [] | |
curr_feature = None | |
score = 0 | |
start_frame = 0 | |
frame_id = 0 | |
time_since_update = 0 | |
# multi-camera | |
location = (np.inf, np.inf) | |
def end_frame(self): | |
return self.frame_id | |
def next_id(): | |
BaseTrack._count += 1 | |
return BaseTrack._count | |
def activate(self, *args): | |
raise NotImplementedError | |
def predict(self): | |
raise NotImplementedError | |
def update(self, *args, **kwargs): | |
raise NotImplementedError | |
def mark_lost(self): | |
self.state = TrackState.Lost | |
def mark_removed(self): | |
self.state = TrackState.Removed | |