Parkinson_disease_detection

data_augmentaion.py

train_data_generator = ImageDataGenerator(rotation_range=360, 
                                    width_shift_range=0.0, 
                                    height_shift_range=0.0, 
#                                     brightness_range=[0.5, 1.5],
                                    horizontal_flip=True, 
                                    vertical_flip=True)

x = list(x_train)
y = list(y_train)

x_aug_train = []
y_aug_train = []

for (i, v) in enumerate(y):
    x_img = x[i]
    x_img = np.array(x_img)
    x_img = np.expand_dims(x_img, axis=0)
    aug_iter = train_data_generator.flow(x_img, batch_size=1, shuffle=True)
    for j in range(70):
        aug_image = next(aug_iter)[0].astype('uint8')
        x_aug_train.append(aug_image)
        y_aug_train.append(v)
print(len(x_aug_train))
print(len(y_aug_train))

x_train = x + x_aug_train
y_train = y + y_aug_train
print(len(x_train))
print(len(y_train))

test_data_generator = ImageDataGenerator(rotation_range=360, 
                                    width_shift_range=0.0, 
                                    height_shift_range=0.0, 
#                                     brightness_range=[0.5, 1.5],
                                    horizontal_flip=True, 
                                    vertical_flip=True)

x = list(x_test)
y = list(y_test)

x_aug_test = []
y_aug_test = []

for (i, v) in enumerate(y):
    x_img = x[i]
    x_img = np.array(x_img)
    x_img = np.expand_dims(x_img, axis=0)
    aug_iter = test_data_generator.flow(x_img, batch_size=1, shuffle=True)
    for j in range(20):
        aug_image = next(aug_iter)[0].astype('uint8')
        x_aug_test.append(aug_image)
        y_aug_test.append(v)
print(len(x_aug_test))
print(len(y_aug_test))

x_test = x + x_aug_test
y_test = y + y_aug_test
print(len(x_test))
print(len(y_test))