比较tf.keras.callbacks.Callback回调实例中单个类的精度

class ClassAccuracyCallback(tf.keras.callbacks.Callback):
    def __init__(self, class_index):
        super(ClassAccuracyCallback, self).__init__()
        self.class_index = class_index
        self.class_samples = 0
        self.class_correct = 0

    def on_train_begin(self, logs=None):
        self.class_samples = 0
        self.class_correct = 0

    def on_epoch_end(self, epoch, logs=None):
        predictions = self.model.predict(self.validation_data[0])
        y_pred = np.argmax(predictions, axis=1)
        y_true = np.argmax(self.validation_data[1], axis=1)

        class_samples = np.sum(y_true == self.class_index)
        class_correct = np.sum((y_pred == y_true) & (y_true == self.class_index))

        self.class_samples += class_samples
        self.class_correct += class_correct

        class_accuracy = class_correct / class_samples if class_samples > 0 else 0
        print(f'Class {self.class_index} accuracy: {class_accuracy}')

        return

    def on_train_end(self, logs=None):
        overall_accuracy = self.class_correct / self.class_samples if self.class_samples > 0 else 0
        print(f'Overall accuracy: {overall_accuracy}')

        return

class_index = 0  # 需要计算精度的类别索引
callback = ClassAccuracyCallback(class_index)

model.fit(x_train, y_train, callbacks=[callback])