test_seal_recognition.py 1.6 KB

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  1. # Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
  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. from paddlex import create_pipeline
  15. pipeline = create_pipeline(pipeline="seal_recognition")
  16. output = pipeline.predict(
  17. "./test_samples/seal_text_det.png",
  18. use_doc_orientation_classify=False,
  19. use_doc_unwarping=False,
  20. )
  21. # output = pipeline.predict(
  22. # "./test_samples/seal_text_det.png",
  23. # use_doc_orientation_classify=False,
  24. # use_doc_unwarping=False,
  25. # text_rec_score_thresh = 0.9
  26. # )
  27. # output = pipeline.predict(
  28. # "./test_samples/seal_text_det.png",
  29. # use_doc_orientation_classify=True,
  30. # use_doc_unwarping=True
  31. # )
  32. # output = pipeline.predict(
  33. # "./test_samples/seal_text_det.png",
  34. # use_doc_orientation_classify=False,
  35. # use_doc_unwarping=False,
  36. # use_layout_detection=False
  37. # )
  38. # output = pipeline.predict(
  39. # "./test_samples/seal_text_det.png"
  40. # )
  41. # output = pipeline.predict("./test_samples/财报1.pdf")
  42. for res in output:
  43. print(res)
  44. res.print()
  45. res.save_to_img("./output")
  46. res.save_to_json("./output")