CODEWITHSUNDEEP
imagetensorflowkerasimage-augmentation
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Neg

Reputation: 41

Number of augmented images on the fly in Keras

I have a code to augment images like the following,

# Augmentation
train_datagen = ImageDataGenerator(rotation_range=5,  # rotation
                                   width_shift_range=0.2,  # horizontal shift
                                   zoom_range=0.2,  # zoom
                                   horizontal_flip=True,  # horizontal flip
                                   brightness_range=[0.2,0.8])  # brightness

# Epochs
epochs = 25
# Batch size
batch_size = 32

history = model.fit(train_datagen.flow(x_train,y_train,
                                       batch_size=batch_size, 
                                       seed=27,
                                       shuffle=False),
                    epochs=epochs,
                    steps_per_epoch=x_train.shape[0] // batch_size,
                    validation_data=(x_test,y_test),
                    verbose=1)

I am trying to understand exactly how many extra images will be created in the training process as a result of augmentation. The second question is how can I create extra 50K images on the fly for the training?

Upvotes: 1

Views: 217

Answers (1)

Fady Guirguis
Fady Guirguis

Reputation: 11

The datagenerator doesn't create new images it rather just transforms it for each epoch. if you have x_train ) = [x1,x2,x3] images in your entire training set, upon training in each epoch the model should see the same x_train BUT your x_train is so small (just 3 images) so the thing is for each epoch the datagen will feed the model the whole x_train slightly transformed (according to the parameters you put in ImageDataGenerator) e.g.:

  • for epoch 1 x_train: [x1,x2,x3]
  • for epoch 2 x_train: [x1_t1,x2_t1,x3_t1]
  • for epoch 3 x_train: [x1_t2,x2_t2,x3_t2] etc...

Upvotes: 1

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