Try different augmentation techniques about riadd.aucmedi

[muellerdo]

0.augmenting_mean     0.774548
0.augmenting_softmax  0.712707
0.simple              0.749488
1.augmenting_mean     0.741797
1.augmenting_softmax  0.712770
1.simple              0.733496
2.augmenting_mean     0.639958
2.augmenting_softmax  0.638353
2.simple              0.620327
3.augmenting_mean     0.687538
3.augmenting_softmax  0.669613
3.simple              0.659798
4.augmenting_mean     0.685304
4.augmenting_softmax  0.645983
4.simple              0.662414

[muellerdo]

# Initialize Image Augmentation
    if i == 0:
        aug = Image_Augmentation(flip=True, rotate=True, brightness=True, contrast=True,
                                 saturation=True, hue=True, scale=False, crop=False,
                                 grid_distortion=False, compression=False,
                                 gaussian_noise=False, gaussian_blur=False,
                                 downscaling=False, gamma=False,
                                 elastic_transform=False)
    elif i == 1:
        aug = Image_Augmentation(flip=True, rotate=True, brightness=False, contrast=False,
                                 saturation=False, hue=False, scale=False, crop=False,
                                 grid_distortion=False, compression=False,
                                 gaussian_noise=False, gaussian_blur=False,
                                 downscaling=False, gamma=False,
                                 elastic_transform=False)
    elif i == 2:
        aug = Image_Augmentation(flip=True, rotate=True, brightness=True, contrast=True,
                                 saturation=False, hue=False, scale=False, crop=False,
                                 grid_distortion=True, compression=False,
                                 gaussian_noise=False, gaussian_blur=False,
                                 downscaling=False, gamma=False,
                                 elastic_transform=False)
    elif i == 3:
        aug = Image_Augmentation(flip=True, rotate=True, brightness=True, contrast=True,
                                 saturation=False, hue=False, scale=False, crop=False,
                                 grid_distortion=True, compression=False,
                                 gaussian_noise=True, gaussian_blur=True,
                                 downscaling=False, gamma=False,
                                 elastic_transform=False)
    elif i == 4:
        aug = Image_Augmentation(flip=True, rotate=True, brightness=True, contrast=True,
                                  saturation=False, hue=False, scale=False, crop=False,
                                  grid_distortion=True, compression=False,
                                  gaussian_noise=False, gaussian_blur=False,
                                  downscaling=False, gamma=False,
                                  elastic_transform=False)

    if i != 4:
        val_gen = DataGenerator(X_test, path_images, labels=y_test, batch_size=32,
                                img_aug=aug, subfunctions=sf_list, standardize_mode=sf_standardize,
                                shuffle=False, resize=input_shape, grayscale=False, prepare_images=False,
                                sample_weights=None, seed=None, image_format=image_format, workers=8)
    else:
        val_gen = DataGenerator(X_test, path_images, labels=y_test, batch_size=32,
                                img_aug=aug, subfunctions=sf_list, standardize_mode=sf_standardize,
                                shuffle=False, resize=input_shape, grayscale=False, prepare_images=False,
                                sample_weights=sample_weights, seed=None, image_format=image_format, workers=8)

[muellerdo]

Winner: -> Include sample weights for validation

aug = Image_Augmentation(flip=True, rotate=True, brightness=True, contrast=True,
                                 saturation=True, hue=True, scale=False, crop=False,
                                 grid_distortion=False, compression=False,
                                 gaussian_noise=False, gaussian_blur=False,
                                 downscaling=False, gamma=False,
                                 elastic_transform=False)