[Python] tf.keras.utils.image_dataset_from_directory Found 0 files belonging to 0 classes

I am currently attempting to develop an image classification model and have organized my data using the following

DATASET/

ejercicio1/
train/
frames/
ejercicio1_train_0001.jpg
ejercicio1_train_0002.jpg
...
test/
frames/
ejercicio1_test_0001.jpg
ejercicio1_test_0002.jpg
...
val/
frames/
ejercicio1_val_0001.jpg
ejercicio1_val_0002.jpg
...
ejercicio2/`'.


Upon executing my code, the path is correctly identified; however, I receive the message Found 0 files belonging to 0 classes. How could I resolve this issue?

Here is part of the code (this code uses TensorFlow):

def create_image_dataset(directory, img_size, batch_size, subset=None, validation_split=None, seed=None):
directory = os.path.abspath(directory)
directory = os.path.normpath(directory) # Normalizar la ruta
print(f"Intentando crear dataset desde: {directory}") # Depuración detallada
try:
dataset = tf.keras.utils.image_dataset_from_directory(
directory,
labels='inferred',
label_mode='categorical',
image_size=img_size,
batch_size=batch_size,
shuffle=True if subset == 'training' or validation_split is None else False,
validation_split=validation_split,
subset=subset,
seed=seed
)
print(f"Dataset creado con éxito desde: {directory}")
return dataset
except ValueError as e:
print(f"Error al crear dataset desde: {directory}. Error: {e}")
return None # Importante: devolver None en caso de error

train_datasets = []
test_datasets = []
val_datasets = []
# Obtiene la lista de nombres de las carpetas de ejercicio
exercise_names = [d for d in os.listdir(DATASET_DIR) if os.path.isdir(os.path.join(DATASET_DIR, d))]

# Crea un dataset para cada conjunto (train, test, val) de cada ejercicio
for exercise in exercise_names:
train_dir = os.path.join(DATASET_DIR, exercise, TRAIN_DIR_NAME, FRAME_DIR_NAME)
train_dir = os.path.normpath(train_dir) # Normalizar la ruta
test_dir = os.path.join(DATASET_DIR, exercise, TEST_DIR_NAME, FRAME_DIR_NAME)
test_dir = os.path.normpath(test_dir) # Normalizar la ruta
val_dir = os.path.join(DATASET_DIR, exercise, VAL_DIR_NAME, FRAME_DIR_NAME)
val_dir = os.path.normpath(val_dir) # Normalizar la ruta

print(f"Ruta de entrenamiento: {train_dir}")
print(f"Ruta de prueba: {test_dir}")
print(f"Ruta de validación: {val_dir}")

if os.path.exists(train_dir):
train_dataset = create_image_dataset(train_dir, IMG_SIZE, BATCH_SIZE, seed=SEED)
if train_dataset:
train_datasets.append(train_dataset)
if os.path.exists(test_dir):
test_dataset = create_image_dataset(test_dir, IMG_SIZE, BATCH_SIZE, seed=SEED)
if test_dataset:
test_datasets.append(test_dataset)
if os.path.exists(val_dir):
val_dataset = create_image_dataset(val_dir, IMG_SIZE, BATCH_SIZE, seed=SEED)
if val_dataset:
val_datasets.append(val_dataset)

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