import numpy as np
from collections import OrderedDict


class TrackState(object):
    New = 0
    Tracked = 1
    Lost = 2
    Removed = 3


class BaseTrack(object):
    def __init__(self, tracker_max_id):
        self.tracker_max_id = tracker_max_id
    _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)

    @property
    def end_frame(self):
        return self.frame_id

    def next_id(self):
        if BaseTrack._count == self.tracker_max_id:
            BaseTrack._count = 0
        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