如何防止Keras Forecast_generator对数据进行混排？

Question

我创建了一个深度学习模型，我想使用predict_generator检查模型的性能。我正在使用以下代码，该代码将图像的标签与预测的类进行比较，然后返回预测错误。

validation_generator = validation_datagen.flow_from_directory(
            validation_dir,
            target_size=(image_size, image_size),
            batch_size=val_batchsize,
            class_mode='categorical',
            shuffle=False)

    # Get the filenames from the generator
    fnames = validation_generator.filenames

    # Get the ground truth from generator
    ground_truth = validation_generator.classes

    # Get the label to class mapping from the generator
    label2index = validation_generator.class_indices

    # Getting the mapping from class index to class label
    idx2label = dict((v,k) for k,v in label2index.items())

    # Get the predictions from the model using the generator
    predictions = model.predict_generator(validation_generator, steps=validation_generator.samples/validation_generator.batch_size,verbose=1)
    predicted_classes = np.argmax(predictions,axis=1)

    errors = np.where(predicted_classes != ground_truth)[0]
    print("No of errors = {}/{}".format(len(errors),validation_generator.samples))

    # Show the errors
    for i in range(len(errors)):
        pred_class = np.argmax(predictions[errors[i]])
        pred_label = idx2label[pred_class]

        title = 'Original label:{}, Prediction :{}, confidence : {:.3f}'.format(
            fnames[errors[i]].split('/')[0],
            pred_label,
            predictions[errors[i]][pred_class])

        original = load_img('{}/{}'.format(validation_dir,fnames[errors[i]]))
        plt.figure(figsize=[7,7])
        plt.axis('off')
        plt.title(title)
        plt.imshow(original)
        plt.show()

validation_generator.classes被安排，但是predicted_classes未被安排。

我从这里https://www.learnopencv.com/keras-tutorial-fine-tuning-using-pre-trained-models/

获取代码

如何防止predict_generator改组数据？