nlc.py 文件源码

def consensus_vote(votes, transM, frameEnd, iters):
    """
    Perform iterative consensus voting
    """
    sTime = time.time()
    for t in range(iters):
        votes = np.dot(transM, votes)
        # normalize per frame
        for i in range(frameEnd.shape[0]):
            currStartF = 1 + frameEnd[i - 1] if i > 0 else 0
            currEndF = frameEnd[i]
            frameVotes = np.max(votes[currStartF:1 + currEndF])
            votes[currStartF:1 + currEndF] /= frameVotes + (frameVotes <= 0)
    eTime = time.time()
    print('Consensus voting finished: %.2f s' % (eTime - sTime))
    return votes