main.py 文件源码

def compute_ap(class_score_matrix, labels):
    num_classes=class_score_matrix.shape[1]
    one_hot_labels=dense_to_one_hot(labels, num_classes)
    predictions=np.array(class_score_matrix>0, dtype="int32")
    average_precision=[]
    for i in range(num_classes):
        ps=average_precision_score(one_hot_labels[:, i], class_score_matrix[:, i])
       # if not np.isnan(ps):
        average_precision.append(ps)
    return np.array(average_precision)