app.py

import tensorflow as tf
import matplotlib.pyplot as plt

#Preprocesamiento de imagenes del conjunto de entrenamiento
training_set = tf.keras.utils.image_dataset_from_directory(
    'FruitTrainingDataset/train',
    labels="inferred",
    label_mode="categorical",
    class_names=None,
    color_mode="rgb",
    batch_size=32,
    image_size=(64, 64),
    shuffle=True,
    seed=None,
    validation_split=None,
    subset=None,
    interpolation="bilinear",
    follow_links=False,
    crop_to_aspect_ratio=False
)

#Preprocesamiento de imagenes del conjunto de validacion
validation_set = tf.keras.utils.image_dataset_from_directory(
    'FruitTrainingDataset/validation',
    labels="inferred",
    label_mode="categorical",
    class_names=None,
    color_mode="rgb",
    batch_size=32,
    image_size=(64, 64),
    shuffle=True,
    seed=None,
    validation_split=None,
    subset=None,
    interpolation="bilinear",
    follow_links=False,
    crop_to_aspect_ratio=False
)