main.py 文件源码

def get_top1(label_sum,out_sum):
    label_sum=label_sum.numpy()
    out_sum=out_sum.numpy().argmax(1)
    assert len(label_sum)==len(out_sum)
    cf=confusion_matrix(label_sum,out_sum).astype(float)
    cls_cnt=cf.sum(axis=1)
    cls_hit=np.diag(cf)
    #accuracy=sum([1 for i in range(len(label_sum)) if label_sum[i]==out_sum[i]])/float(len(label_sum))
    #return accuracy
    return np.mean(cls_hit/cls_cnt)