test_image_unwarping.py 1.8 KB

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  1. # copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve.
  2. #
  3. # Licensed under the Apache License, Version 2.0 (the "License");
  4. # you may not use this file except in compliance with the License.
  5. # You may obtain a copy of the License at
  6. #
  7. # http://www.apache.org/licenses/LICENSE-2.0
  8. #
  9. # Unless required by applicable law or agreed to in writing, software
  10. # distributed under the License is distributed on an "AS IS" BASIS,
  11. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  12. # See the License for the specific language governing permissions and
  13. # limitations under the License.
  14. import numpy as np
  15. from paddlex.inference.results import DocTrResult
  16. from tests.models.base import BaseTestPredictor
  17. from paddlex_hpi.models import WarpPredictor
  18. MODEL_URL = "https://paddle-model-ecology.bj.bcebos.com/paddlex/PaddleX3.0/deploy/paddlex_hpi/tests/models/warp_model.zip"
  19. INPUT_DATA_URL = "https://paddle-model-ecology.bj.bcebos.com/paddlex/PaddleX3.0/deploy/paddlex_hpi/tests/models/warp_input.jpg"
  20. EXPECTED_RESULT_URL = "https://paddle-model-ecology.bj.bcebos.com/paddlex/PaddleX3.0/deploy/paddlex_hpi/tests/models/warp_result.json"
  21. class TestWarpPredictor(BaseTestPredictor):
  22. @property
  23. def model_url(self):
  24. return MODEL_URL
  25. @property
  26. def input_data_url(self):
  27. return INPUT_DATA_URL
  28. @property
  29. def expected_result_url(self):
  30. return EXPECTED_RESULT_URL
  31. @property
  32. def predictor_cls(self):
  33. return WarpPredictor
  34. def _check_result(self, result, expected_result):
  35. assert isinstance(result, DocTrResult)
  36. assert set(result) == set(expected_result)
  37. assert np.allclose(
  38. result["doctr_img"],
  39. np.array(expected_result["doctr_img"]),
  40. rtol=1e-2,
  41. atol=2,
  42. )