def _dataset():
"""Returns the `MS-ASL` dataset example for the word `dance`.
The dataset example corresponding to the label with index 84 and the signer with index 347 shall be returned.
Returns:
The dataset example for the word `dance`.
"""
dataset = tf_record_dataset(DatasetName.MSASL, DatasetType.TRAIN)
dataset = dataset.batch(1)
dataset = dataset.map(transform_for_prediction)
dataset = dataset.unbatch()
dataset = dataset.filter(lambda frames, label, signer: tf.math.equal(label, 84) and tf.math.equal(signer, 347))
dataset = dataset.batch(1)
return dataset.take(1)
def inspect_dataset(dataset_name: DatasetName, dataset_type: DatasetType,
inspect_fn, batch_size=1, skip_count=0, take_count=1):
"""Inspects a given number of dataset examples according to a passed inspection function.
Arguments:
dataset_name: The name of the dataset to inspect (one of `DatasetName`).
dataset_type: The type of the dataset to inspect (one of `DatasetType`).
inspect_fn: The function to apply to a sequence of frames.
batch_size: The number of consecutive dataset examples to combine into a batch.
skip_count: The number of dataset examples to skip.
take_count: The maximum number of dataset examples to fetch.
"""
dataset = tf_record_dataset(dataset_name, dataset_type)
dataset = dataset.batch(batch_size)
dataset = dataset.map(transform_for_inspection)
if skip_count:
dataset = dataset.skip(skip_count)
for frames_batch, labels, signers in dataset.take(take_count):
frames_batch = frames_batch.numpy()
for frames in frames_batch:
inspect_fn(frames)
def _train_dataset():
train_dataset = tf_record_dataset(DatasetName.MSASL, DatasetType.TRAIN)
train_dataset = train_dataset.shuffle(2048)
train_dataset = train_dataset.batch(32)
train_dataset = train_dataset.map(transform_for_msasl_model)
return train_dataset.prefetch(2)
def _validation_dataset():
validation_dataset = tf_record_dataset(DatasetName.SIGNUM,
DatasetType.VALIDATION)
validation_dataset = validation_dataset.batch(32)
validation_dataset = validation_dataset.map(transform_for_signum_model)
return validation_dataset.prefetch(2)
def _train_dataset():
train_dataset = tf_record_dataset(DatasetName.SIGNUM, DatasetType.TRAIN)
train_dataset = train_dataset.shuffle(2048)
train_dataset = train_dataset.batch(32)
train_dataset = train_dataset.map(transform_for_signum_model)
return train_dataset.prefetch(2)
def _test_dataset():
test_dataset = tf_record_dataset(DatasetName.SIGNUM, DatasetType.TEST)
test_dataset = test_dataset.batch(32)
test_dataset = test_dataset.map(transform_for_signum_model)
return test_dataset.prefetch(2)