Internal change

PiperOrigin-RevId: 411191131

official/vision/beta/evaluation/wod_detection_evaluator_test.py

-# Copyright 2021 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 wod_detection_evaluator."""
-
-import tensorflow as tf
-
-from official.vision.beta.evaluation import wod_detection_evaluator
-
-
-class WodDetectionEvaluatorTest(tf.test.TestCase):
-
-  def _create_test_data(self):
-    y_pred = {
-        'source_id':
-            tf.convert_to_tensor([1], dtype=tf.int64),
-        'image_info':
-            tf.convert_to_tensor([[[100, 100], [50, 50], [0.5, 0.5], [0, 0]]],
-                                 dtype=tf.float32),
-        'num_detections':
-            tf.convert_to_tensor([4], dtype=tf.int64),
-        'detection_boxes':
-            tf.convert_to_tensor(
-                [[[0.1, 0.15, 0.2, 0.25], [0.35, 0.18, 0.43, 0.4],
-                  [0.2, 0.1, 0.3, 0.2], [0.65, 0.55, 0.75, 0.85]]],
-                dtype=tf.float32),
-        'detection_classes':
-            tf.convert_to_tensor([[1, 1, 2, 2]], dtype=tf.int64),
-        'detection_scores':
-            tf.convert_to_tensor([[0.95, 0.5, 0.1, 0.7]], dtype=tf.float32)
-    }
-
-    y_true = {
-        'source_id':
-            tf.convert_to_tensor([1], dtype=tf.int64),
-        'num_detections':
-            tf.convert_to_tensor([4], dtype=tf.int64),
-        'boxes':
-            tf.convert_to_tensor([[[0.1, 0.15, 0.2, 0.25], [0.3, 0.2, 0.4, 0.3],
-                                   [0.4, 0.3, 0.5, 0.6], [0.6, 0.5, 0.7, 0.8]]],
-                                 dtype=tf.float32),
-        'classes':
-            tf.convert_to_tensor([[1, 1, 1, 2]], dtype=tf.int64),
-        'difficulties':
-            tf.zeros([1, 4], dtype=tf.int64)
-    }
-    return y_pred, y_true
-
-  def test_wod_detection_evaluator(self):
-    wod_detection_metric = wod_detection_evaluator.WOD2dDetectionEvaluator()
-    y_pred, y_true = self._create_test_data()
-    wod_detection_metric.update_state(groundtruths=y_true, predictions=y_pred)
-    metrics = wod_detection_metric.evaluate()
-    for _, metric_value in metrics.items():
-      self.assertAlmostEqual(metric_value.numpy(), 0.0, places=3)
-
-
-if __name__ == '__main__':
-  tf.test.main()