# Copyright 2017 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 object_detection.np_box_ops."""

import numpy as np
import tensorflow as tf

from object_detection.utils import np_box_ops


class BoxOpsTests(tf.test.TestCase):

  def setUp(self):
    boxes1 = np.array([[4.0, 3.0, 7.0, 5.0], [5.0, 6.0, 10.0, 7.0]],
                      dtype=float)
    boxes2 = np.array([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
                       [0.0, 0.0, 20.0, 20.0]],
                      dtype=float)
    self.boxes1 = boxes1
    self.boxes2 = boxes2

  def testArea(self):
    areas = np_box_ops.area(self.boxes1)
    expected_areas = np.array([6.0, 5.0], dtype=float)
    self.assertAllClose(expected_areas, areas)

  def testIntersection(self):
    intersection = np_box_ops.intersection(self.boxes1, self.boxes2)
    expected_intersection = np.array([[2.0, 0.0, 6.0], [1.0, 0.0, 5.0]],
                                     dtype=float)
    self.assertAllClose(intersection, expected_intersection)

  def testIOU(self):
    iou = np_box_ops.iou(self.boxes1, self.boxes2)
    expected_iou = np.array([[2.0 / 16.0, 0.0, 6.0 / 400.0],
                             [1.0 / 16.0, 0.0, 5.0 / 400.0]],
                            dtype=float)
    self.assertAllClose(iou, expected_iou)

  def testIOA(self):
    boxes1 = np.array([[0.25, 0.25, 0.75, 0.75],
                       [0.0, 0.0, 0.5, 0.75]],
                      dtype=np.float32)
    boxes2 = np.array([[0.5, 0.25, 1.0, 1.0],
                       [0.0, 0.0, 1.0, 1.0]],
                      dtype=np.float32)
    ioa21 = np_box_ops.ioa(boxes2, boxes1)
    expected_ioa21 = np.array([[0.5, 0.0],
                               [1.0, 1.0]],
                              dtype=np.float32)
    self.assertAllClose(ioa21, expected_ioa21)


if __name__ == '__main__':
  tf.test.main()