根据 Keras 中的图像和子文件夹名称设置 X 和 y 用于训练 CNN

Question

The following snippet of code gives me 150 images belonging to three classes (there are three subfolders with 50 images in each - the folders are named after the classes of Iris that I'm trying to write a CNN to classify).

The question I have is how do I set np arrays of the images as my X and the subfolder names as my y for training my CNN?

import keras
from keras.preprocessing.image import ImageDataGenerator

train_gen = ImageDataGenerator(rescale = 1./255,
shear_range = 0.2, zoom_range = 0.2, horizontal_flip = True)
test_gen = ImageDataGenerator(rescale = 1./255)
training_set = train_gen.flow_from_directory(r"Iris_Imgs",
target_size = (5, 5), shuffle=True, batch_size = 15, class_mode = 'binary')
train_imgs, train_labels = next(training_set)
test_set = test_gen.flow_from_directory(r"Iris_Imgs",
target_size = (5, 5), shuffle=True, class_mode = 'binary')
test_imgs, test_labels = next(test_set)

Answer 1

You are using flow_from_directory incorrectly. Unless your data is already grouped in subfolders, flow_from_directory will not work properly.

Use flow_from_dataframe. Store path to images in one column and class_labels in another column. Then use flow_from_dataframe. This is what you should be using since your data is not classified in subfolders.