How to use keras flow method?
Assuming you already have resized and other preprocessing your image data into a multi-dimensional numpy array and split the data into training and test. 

To use the flow() method. You first want to create a generator using ImageDataGenerator(). The example below DOES NOT DO image augmentation. It will feed only the images in your training set. I added the rescale parameter in case one had not normalized the pixel data.

You then pass your training data to the fit() method of the generator (datagen.fit()).

datagen = ImageDataGenerator(rescale=1./255) 
datagen.fit(x_train)


Now you can train your model using the fit_generator() method for your model.

model.fit_generator(datagen.flow(x_train, y_train, batch_size=batchSize),
                    steps_per_epoch=len(x_train) / batchSize, epochs=epochs)


You can do it the manual way:

for epoch in range(epochs):
    for x_batch, y_batch in datagen.flow(x_train, y_train, batch_size=batchSize):
        model.fit(x_batch, y_batch)


Here's the link to the corresponding Keras documentation: https://keras.io/preprocessing/image/