如何计算keras中每个时期后的查准率和召回率？

from keras.callbacks import Callback
from sklearn.metrics import precision_score, recall_score

class PrecisionRecallCallback(Callback):
    def on_epoch_end(self, epoch, logs=None):
        # 获取当前模型在验证集上的预测结果
        y_pred = self.model.predict(self.validation_data[0])
        y_pred = (y_pred > 0.5).astype(int)  # 将概率转换为类别
        
        # 计算查准率和召回率
        precision = precision_score(self.validation_data[1], y_pred)
        recall = recall_score(self.validation_data[1], y_pred)
        
        # 打印结果
        print("Epoch {}: Precision = {:.4f}, Recall = {:.4f}".format(epoch+1, precision, recall))

# 创建模型并编译
model = ...
model.compile(...)

# 创建回调函数实例
callback = PrecisionRecallCallback()

# 训练模型时指定回调函数
model.fit(x_train, y_train, validation_data=(x_val, y_val), callbacks=[callback], ...)