Spaces:
Runtime error
Runtime error
| # 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. | |
| """Tests for ops.""" | |
| import numpy as np | |
| import tensorflow as tf, tf_keras | |
| from official.vision.utils.object_detection import ops | |
| class OpsTest(tf.test.TestCase): | |
| def test_merge_boxes_with_multiple_labels(self): | |
| boxes = tf.constant( | |
| [ | |
| [0.25, 0.25, 0.75, 0.75], | |
| [0.0, 0.0, 0.5, 0.75], | |
| [0.25, 0.25, 0.75, 0.75], | |
| ], | |
| dtype=tf.float32, | |
| ) | |
| class_indices = tf.constant([0, 4, 2], dtype=tf.int32) | |
| class_confidences = tf.constant([0.8, 0.2, 0.1], dtype=tf.float32) | |
| num_classes = 5 | |
| merged_boxes, merged_classes, merged_confidences, merged_box_indices = ( | |
| ops.merge_boxes_with_multiple_labels( | |
| boxes, class_indices, class_confidences, num_classes | |
| ) | |
| ) | |
| expected_merged_boxes = np.array( | |
| [[0.25, 0.25, 0.75, 0.75], [0.0, 0.0, 0.5, 0.75]], dtype=np.float32 | |
| ) | |
| expected_merged_classes = np.array( | |
| [[1, 0, 1, 0, 0], [0, 0, 0, 0, 1]], dtype=np.int32 | |
| ) | |
| expected_merged_confidences = np.array( | |
| [[0.8, 0, 0.1, 0, 0], [0, 0, 0, 0, 0.2]], dtype=np.float32 | |
| ) | |
| expected_merged_box_indices = np.array([0, 1], dtype=np.int32) | |
| self.assertAllClose(merged_boxes.numpy(), expected_merged_boxes) | |
| self.assertAllClose(merged_classes.numpy(), expected_merged_classes) | |
| self.assertAllClose(merged_confidences.numpy(), expected_merged_confidences) | |
| self.assertAllClose(merged_box_indices.numpy(), expected_merged_box_indices) | |
| def test_merge_boxes_with_multiple_labels_corner_case(self): | |
| boxes = tf.constant( | |
| [ | |
| [0, 0, 1, 1], | |
| [0, 1, 1, 1], | |
| [1, 0, 1, 1], | |
| [1, 1, 1, 1], | |
| [1, 1, 1, 1], | |
| [1, 0, 1, 1], | |
| [0, 1, 1, 1], | |
| [0, 0, 1, 1], | |
| ], | |
| dtype=tf.float32, | |
| ) | |
| class_indices = tf.constant([0, 1, 2, 3, 2, 1, 0, 3], dtype=tf.int32) | |
| class_confidences = tf.constant( | |
| [0.1, 0.9, 0.2, 0.8, 0.3, 0.7, 0.4, 0.6], dtype=tf.float32 | |
| ) | |
| num_classes = 4 | |
| merged_boxes, merged_classes, merged_confidences, merged_box_indices = ( | |
| ops.merge_boxes_with_multiple_labels( | |
| boxes, class_indices, class_confidences, num_classes | |
| ) | |
| ) | |
| expected_merged_boxes = np.array( | |
| [[0, 0, 1, 1], [0, 1, 1, 1], [1, 0, 1, 1], [1, 1, 1, 1]], | |
| dtype=np.float32, | |
| ) | |
| expected_merged_classes = np.array( | |
| [[1, 0, 0, 1], [1, 1, 0, 0], [0, 1, 1, 0], [0, 0, 1, 1]], dtype=np.int32 | |
| ) | |
| expected_merged_confidences = np.array( | |
| [ | |
| [0.1, 0, 0, 0.6], | |
| [0.4, 0.9, 0, 0], | |
| [0, 0.7, 0.2, 0], | |
| [0, 0, 0.3, 0.8], | |
| ], | |
| dtype=np.float32, | |
| ) | |
| expected_merged_box_indices = np.array([0, 1, 2, 3], dtype=np.int32) | |
| self.assertAllClose(merged_boxes.numpy(), expected_merged_boxes) | |
| self.assertAllClose(merged_classes.numpy(), expected_merged_classes) | |
| self.assertAllClose(merged_confidences.numpy(), expected_merged_confidences) | |
| self.assertAllClose(merged_box_indices.numpy(), expected_merged_box_indices) | |
| def test_merge_boxes_with_empty_inputs(self): | |
| boxes = tf.zeros([0, 4], dtype=tf.float32) | |
| class_indices = tf.constant([], dtype=tf.int32) | |
| class_confidences = tf.constant([], dtype=tf.float32) | |
| num_classes = 5 | |
| merged_boxes, merged_classes, merged_confidences, merged_box_indices = ( | |
| ops.merge_boxes_with_multiple_labels( | |
| boxes, class_indices, class_confidences, num_classes | |
| ) | |
| ) | |
| self.assertAllEqual(merged_boxes.shape, [0, 4]) | |
| self.assertAllEqual(merged_classes.shape, [0, 5]) | |
| self.assertAllEqual(merged_confidences.shape, [0, 5]) | |
| self.assertAllEqual(merged_box_indices.shape, [0]) | |
| if __name__ == '__main__': | |
| tf.test.main() | |