CutMixImageDataGenerator (Keras)

Paper: CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features

Install

$ pip install cutmix-keras

How To Use

class CutMixImageDataGenerator():
    def __init__(self, generator1, generator2, img_size, batch_size):
        self.batch_index = 0
        self.samples = generator1.samples
        self.class_indices = generator1.class_indices
        self.generator1 = generator1
        self.generator2 = generator2
        . . .

• generator1, generator2 need same generator applied flow method

• generator1, generator2 need shuffle=True
  If shuffle=False, This generator cutmix with same images.
  So there would no augmentation

• Why are there two same generators? (generator1, generator2)
  --> To Solve Reference Problem

Using Example

# (some codes) ...
from cutmix_keras import CutMixImageDataGenerator  # Import CutMix


train_datagen = ImageDataGenerator(
    rescale=1./255,
)

train_generator1 = train_datagen.flow_from_dataframe(
    dataframe=X_train,
    directory=IMG_DIR,
    target_size=(IMG_SIZE, IMG_SIZE),
    x_col='X_Column',
    y_col='Y_Column',
    color_mode='rgb',
    class_mode='categorical',
    batch_size=BATCH_SIZE,
    shuffle=True,  # Required
)

train_generator2 = train_datagen.flow_from_dataframe(
    dataframe=X_train,
    directory=IMG_DIR,
    target_size=(IMG_SIZE, IMG_SIZE),
    x_col='X_Column',
    y_col='Y_Column',
    color_mode='rgb',
    class_mode='categorical',
    batch_size=BATCH_SIZE,
    shuffle=True,  # Required
)

# CutMixImageDataGenerator
train_generator = CutMixImageDataGenerator(
    generator1=train_generator1,
    generator2=train_generator2,
    img_size=IMG_SIZE,
    batch_size=BATCH_SIZE,
)