# Copyright 2021 The MediaPipe 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 mediapipe.python.solutions.selfie_segmentation."""

import os

from absl.testing import absltest
from absl.testing import parameterized
import cv2
import numpy as np

# resources dependency
# undeclared dependency
from mediapipe.python.solutions import selfie_segmentation as mp_selfie_segmentation

TEST_IMAGE_PATH = 'mediapipe/python/solutions/testdata'


class SelfieSegmentationTest(parameterized.TestCase):

  def _draw(self, frame: np.ndarray, mask: np.ndarray):
    frame = np.minimum(frame, np.stack((mask,) * 3, axis=-1))
    path = os.path.join(tempfile.gettempdir(), self.id().split('.')[-1] + '.png')
    cv2.imwrite(path, frame)

  def test_invalid_image_shape(self):
    with mp_selfie_segmentation.SelfieSegmentation() as selfie_segmentation:
      with self.assertRaisesRegex(
          ValueError, 'Input image must contain three channel rgb data.'):
        selfie_segmentation.process(
            np.arange(36, dtype=np.uint8).reshape(3, 3, 4))

  def test_blank_image(self):
    with mp_selfie_segmentation.SelfieSegmentation() as selfie_segmentation:
      image = np.zeros([100, 100, 3], dtype=np.uint8)
      image.fill(255)
      results = selfie_segmentation.process(image)
      normalized_segmentation_mask = (results.segmentation_mask *
                                      255).astype(int)
      self.assertLess(np.amax(normalized_segmentation_mask), 1)

  @parameterized.named_parameters(('general', 0), ('landscape', 1))
  def test_segmentation(self, model_selection):
    image_path = os.path.join(os.path.dirname(__file__),
                              'testdata/portrait.jpg')
    image = cv2.imread(image_path)
    with mp_selfie_segmentation.SelfieSegmentation(
        model_selection=model_selection) as selfie_segmentation:
      results = selfie_segmentation.process(
          cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
      normalized_segmentation_mask = (results.segmentation_mask *
                                      255).astype(int)
      self._draw(image.copy(), normalized_segmentation_mask)


if __name__ == '__main__':
  absltest.main()