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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()
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