Keras flow_from_directory class index

Question

I used to make it manually, but i am using now flow_from_directory to train my network with my own data. I just have one question. When i make model.predict(), how can i know that my index 0 on predictions is for label category dog and index 1 is for category cats?

The code i am using is the following.

train_datagen = ImageDataGenerator(
    rescale=1./255,
    shear_range=0.2,
    zoom_range=0.2,
    horizontal_flip=True)

test_datagen = ImageDataGenerator(rescale=1./255)

train_generator = train_datagen.flow_from_directory(
        train_images_path,  
        target_size=(64, 64),  
        batch_size=batch_size)  


validation_generator = test_datagen.flow_from_directory(
        validate_images_path,
        target_size=(64, 64),
        batch_size=batch_size)
early_stopping = keras.callbacks.EarlyStopping(monitor='val_acc', min_delta=0, patience=3, verbose=1, mode='auto')
history = model.fit_generator(
        train_generator,
        steps_per_epoch=1700,
        epochs=epochs,
        verbose=1,
        callbacks=[early_stopping],
        validation_data=validation_generator,
        validation_steps=196
)

What i wanted to know is the pair images vs ground truth label.

Thank you

Answer 1

You can have the the index of each class generated by the generator with class_indices property.

print(validation_generator.class_indices)

Simple...

Answer 2

When you gather data, you define that. There is no rule. But a simple way to check is:

• see what your first training image is, look at it yourself: is it a cat or a dog?
• then see the training Y (result/class/desired output), is it [0,1] or [1,0]?

This will answer your question.

For getting one sample from a generator, you can see this question: How to get one value from a generator in Python?

As defined in Keras documentation, the generator output is a tuple of (inputs, targets)