karolmajek/maxdeeplab

1# coding=utf-82# Copyright 2021 The Deeplab2 Authors.3#4# Licensed under the Apache License, Version 2.0 (the "License");5# you may not use this file except in compliance with the License.6# You may obtain a copy of the License at7#8#     http://www.apache.org/licenses/LICENSE-2.09#10# Unless required by applicable law or agreed to in writing, software11# distributed under the License is distributed on an "AS IS" BASIS,12# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.13# See the License for the specific language governing permissions and14# limitations under the License.15 16"""Test for vip_deeplab.py."""17import numpy as np18import tensorflow as tf19 20from deeplab2.model.post_processor import vip_deeplab21 22 23class PostProcessingTest(tf.test.TestCase):24 25  def test_stitch_video_panoptic_prediction(self):26    concat_semantic = np.array(27        [[[0, 0, 0, 0],28          [0, 1, 1, 0],29          [0, 2, 2, 0],30          [2, 2, 3, 3]]], dtype=np.int32)31    concat_instance = np.array(32        [[[1, 1, 2, 2],33          [1, 0, 0, 2],34          [1, 1, 1, 2],35          [2, 2, 1, 1]]], dtype=np.int32)36    next_semantic = np.array(37        [[[0, 1, 1, 0],38          [0, 1, 1, 0],39          [0, 2, 2, 0],40          [2, 2, 3, 3]]], dtype=np.int32)41    next_instance = np.array(42        [[[2, 0, 0, 1],43          [2, 0, 0, 1],44          [2, 4, 4, 1],45          [5, 5, 3, 3]]], dtype=np.int32)46    label_divisor = 100047    concat_panoptic = concat_semantic * label_divisor + concat_instance48    next_panoptic = next_semantic * label_divisor + next_instance49    new_panoptic = vip_deeplab.stitch_video_panoptic_prediction(50        concat_panoptic,51        next_panoptic,52        label_divisor)53    # The expected instance is manually computed. It should receive the IDs54    # propagated from concat_instance by IoU matching between concat_panoptic55    # and next_panoptic.56    expected_semantic = next_semantic57    expected_instance = np.array(58        [[[1, 0, 0, 2],59          [1, 0, 0, 2],60          [1, 1, 1, 2],61          [2, 2, 1, 1]]], dtype=np.int32)62    expected_panoptic = expected_semantic * label_divisor + expected_instance63    np.testing.assert_array_equal(expected_panoptic, new_panoptic)64 65 66if __name__ == '__main__':67  tf.test.main()68