import pytest from paddleocr import FormulaRecognitionPipeline from ..testing_utils import ( TEST_DATA_DIR, check_simple_inference_result, check_wrapper_simple_inference_param_forwarding, ) @pytest.fixture(scope="module") def formula_recognition_engine() -> FormulaRecognitionPipeline: return FormulaRecognitionPipeline() # TODO: Should we separate unit tests and integration tests? @pytest.mark.parametrize( "image_path", [ TEST_DATA_DIR / "doc_with_formula.png", ], ) def test_predict( formula_recognition_engine: FormulaRecognitionPipeline, image_path: str ) -> None: """ Test FormulaRecognitionPipeline's formula_recognition functionality. Args: formula_recognition_engine: An instance of `FormulaRecognitionPipeline`. image_path: Path to the image to be processed. """ result = formula_recognition_engine.predict(str(image_path)) check_simple_inference_result(result) res = result[0] assert isinstance(res["formula_res_list"], list) assert len(res["formula_res_list"]) > 0 # TODO: Also check passing `None` @pytest.mark.parametrize( "params", [ {"use_doc_orientation_classify": False}, {"use_doc_unwarping": False}, {"use_layout_detection": False}, {"layout_threshold": 0.5}, {"layout_nms": True}, {"layout_unclip_ratio": 1.5}, {"layout_merge_bboxes_mode": "large"}, ], ) def test_predict_params( monkeypatch, formula_recognition_engine: FormulaRecognitionPipeline, params: dict, ) -> None: check_wrapper_simple_inference_param_forwarding( monkeypatch, formula_recognition_engine, "paddlex_pipeline", "dummy_path", params, ) # TODO: Test init params