ssegota

from PIL import Image
import os

def augment_and_save(patch, base_name, count, output_dir_aug):
    transformations = {
        'orig': patch,
        'rot90': patch.rotate(90),
        'rot180': patch.rotate(180),
        'rot270': patch.rotate(270),
        'flipH': patch.transpose(Image.FLIP_LEFT_RIGHT),

ssegota

import os
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score, roc_auc_score, precision_score, recall_score, f1_score, confusion_matrix
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.applications import VGG16
from tensorflow.keras.models import Model
from tensorflow.keras.layers import Dense, GlobalAveragePooling2D
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.utils import to_categorical