使用 Keras 的 CSV 文件数据集增强

Question

I am working on an already implemented project in Kaggle which has to do with Image Classification . I have 6 classes to predict on in total, which are Angry, Happy, Sad etc. I have implemented a CNN model and I am currently using only 4 classes(the ones with highest number of images), but my model is overfitting, my validation accuracy is going 53% at maximum, therefore I have tried several things but not seemingly improving my accuracy. Now I saw people mentioning something called Data Augmentation and thought to give it a go as it seems a potential to increase the accuracy. However I am stuck with an error which I cannot figure out.

Distribution of dataset:

from tensorflow.keras.preprocessing.image import ImageDataGenerator
from matplotlib.pyplot import imread, imshow, subplots, show


def plot(data_generator):
    """
    Plots 4 images generated by an object of the ImageDataGenerator class.
    """
    data_generator.fit(df_training)
    image_iterator = data_generator.flow(df_training)

    # Plot the images given by the iterator
    fig, rows = subplots(nrows=1, ncols=4, figsize=(18,18))
    for row in rows:
        row.imshow(image_iterator.next()[0].astype('int'))
        row.axis('off')
    show()

x_train = df_training.drop("emotion",axis=1)
image = x_train[1:2].values.reshape(48, 48)
x_train = x_train.values.reshape(x_train.shape[0], 48, 48,1)
x_train = x_train.astype("float32")
image = image.astype("float32")
image = x_train[1:2].reshape(48, 48)

# Creating a dataset which contains just one image.
images = image.reshape((1, image.shape[0], image.shape[1]))

imshow(images[0])
show()
print(x_train.shape)
data_generator = ImageDataGenerator(rotation_range=90)
plot(data_generator)

Error:

ValueError: Input to .fit() should have rank 4. Got array with shape: (28709, 2305)

I have already reshaped my data into a 4d array but for some reason in the error it appears as my data is 2d. This is the shape of print(x_train.shape) => (28709, 48, 48, 1)

x_train is where the dataset is, x_train[1:2] accessing one image.

Ps Is there any other approach that you would recommend to improve my accuracy according to this dataset. For further questions about my dataset please let me know if you don't understand something in this partial code.

Answer 1

You use your data_generator on df_training and not on x_train.

As for more ideas about how to avoid overfitting: Tensorflow has an official tutorial on that with some good suggestions:https://www.tensorflow.org/tutorials/keras/overfit_and_underfit