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# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Utility functions for dataloader."""
import tensorflow as tf, tf_keras
from official.legacy.detection.utils import input_utils
def process_source_id(source_id):
"""Processes source_id to the right format."""
if source_id.dtype == tf.string:
source_id = tf.cast(tf.strings.to_number(source_id), tf.int64)
with tf.control_dependencies([source_id]):
source_id = tf.cond(
pred=tf.equal(tf.size(input=source_id), 0),
true_fn=lambda: tf.cast(tf.constant(-1), tf.int64),
false_fn=lambda: tf.identity(source_id))
return source_id
def pad_groundtruths_to_fixed_size(gt, n):
"""Pads the first dimension of groundtruths labels to the fixed size."""
gt['boxes'] = input_utils.pad_to_fixed_size(gt['boxes'], n, -1)
gt['is_crowds'] = input_utils.pad_to_fixed_size(gt['is_crowds'], n, 0)
gt['areas'] = input_utils.pad_to_fixed_size(gt['areas'], n, -1)
gt['classes'] = input_utils.pad_to_fixed_size(gt['classes'], n, -1)
return gt
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