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| # coding=utf-8 | |
| # Copyright 2021 The Deeplab2 Authors. | |
| # | |
| # 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 post_processor_builder.py.""" | |
| import tensorflow as tf | |
| from google.protobuf import text_format | |
| from deeplab2 import common | |
| from deeplab2 import config_pb2 | |
| from deeplab2.data import dataset | |
| from deeplab2.model.post_processor import post_processor_builder | |
| class EvaluatorTest(tf.test.TestCase): | |
| def test_evaluates_panoptic_deeplab_model(self): | |
| experiment_options_textproto = """ | |
| experiment_name: "evaluation_test" | |
| eval_dataset_options { | |
| dataset: "cityscapes_panoptic" | |
| file_pattern: "EMPTY" | |
| batch_size: 1 | |
| crop_size: 1025 | |
| crop_size: 2049 | |
| # Skip resizing. | |
| min_resize_value: 0 | |
| max_resize_value: 0 | |
| } | |
| evaluator_options { | |
| continuous_eval_timeout: 43200 | |
| stuff_area_limit: 2048 | |
| center_score_threshold: 0.1 | |
| nms_kernel: 13 | |
| save_predictions: true | |
| save_raw_predictions: false | |
| } | |
| """ | |
| config = text_format.Parse(experiment_options_textproto, | |
| config_pb2.ExperimentOptions()) | |
| config.model_options.panoptic_deeplab.instance.enable = True | |
| post_processor = post_processor_builder.get_post_processor( | |
| config, dataset.CITYSCAPES_PANOPTIC_INFORMATION) | |
| result_dict = { | |
| common.PRED_SEMANTIC_PROBS_KEY: | |
| tf.zeros([1, 1025, 2049, 19], dtype=tf.float32), | |
| common.PRED_CENTER_HEATMAP_KEY: | |
| tf.zeros([1, 1025, 2049, 1], dtype=tf.float32), | |
| common.PRED_OFFSET_MAP_KEY: | |
| tf.zeros([1, 1025, 2049, 2], dtype=tf.float32) | |
| } | |
| processed_dict = post_processor(result_dict) | |
| expected_keys = { | |
| common.PRED_PANOPTIC_KEY, | |
| common.PRED_SEMANTIC_KEY, | |
| common.PRED_INSTANCE_KEY, | |
| common.PRED_INSTANCE_CENTER_KEY, | |
| common.PRED_INSTANCE_SCORES_KEY | |
| } | |
| self.assertCountEqual(processed_dict.keys(), expected_keys) | |
| if __name__ == '__main__': | |
| tf.test.main() | |