mirror of
https://github.com/PaddlePaddle/PaddleOCR.git
synced 2025-07-29 11:50:15 +00:00
3d03ca5500
* Init new paddleocr * Remove unused dependency * Fix typos * Fix * Add doc understanding modules * Fix package finding * Normalize name * Fix setting bugs * Fix setting bug * Support single model inference * Add PP-ChatOCRv4-doc * Add pp_chatocrv4_doc tests * Enable MKL-DNN when available * add seal_text_detection modules * add layout_detection and table_cells_detection modules * add testing scripts * Fix desc * add text_image_unwarping and table_structure_recognition modules * add formula_recognition and doc_vlm modules * update formula_recognition default_model_name * add MKLDNN_BLOCKLIST * update MKLDNN log * add seal rec pipeline * fix sth * fix sth * add doc preprocessor pipeline * fix sth * add doc understanding * add table_rec_v2, ppstructurev3, formula_rec pipelines * move test files * forward kwargs to pipeline.predict * clean test files * Add missing kwargs * Fix typo * Fix typo * rerun CI * update mkldnn BLOCKLIST * update * update warning message * fix cli args * update PIPELINE_MKLDNN_BLOCKLIST * update of workflow * skip resource_intensive tests * update config * skip ppdocbee test_predict_params --------- Co-authored-by: zhangyue66 <zhangyue66@baidu.com> Co-authored-by: zhangzelun <zhangzelun@baidu.com>
71 lines
1.8 KiB
Python
71 lines
1.8 KiB
Python
import pytest
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from paddleocr import SealRecognition
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from ..testing_utils import (
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TEST_DATA_DIR,
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check_simple_inference_result,
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check_wrapper_simple_inference_param_forwarding,
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)
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@pytest.fixture(scope="module")
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def ocr_engine() -> SealRecognition:
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return SealRecognition()
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@pytest.mark.parametrize(
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"image_path",
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[
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TEST_DATA_DIR / "seal.png",
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],
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)
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def test_predict(ocr_engine: SealRecognition, image_path: str) -> None:
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"""
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Test PaddleOCR's seal recognition functionality.
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Args:
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ocr_engine: An instance of `SealRecognition`.
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image_path: Path to the image to be processed.
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"""
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result = ocr_engine.predict(str(image_path))
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check_simple_inference_result(result)
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res = result[0]["seal_res_list"][0]
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assert len(res["dt_polys"]) > 0
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assert isinstance(res["rec_texts"], list)
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assert len(res["rec_texts"]) > 0
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for text in res["rec_texts"]:
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assert isinstance(text, str)
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@pytest.mark.parametrize(
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"params",
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[
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{"use_doc_orientation_classify": False, "use_doc_unwarping": False},
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{"use_layout_detection": False},
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{"layout_det_res": None},
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{"layout_threshold": 0.5},
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{"layout_nms": False},
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{"layout_unclip_ratio": 1.0},
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{"layout_merge_bboxes_mode": "large"},
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{"seal_det_limit_side_len": 736},
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{"seal_det_limit_type": "min"},
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{"seal_det_thresh": 0.5},
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{"seal_det_box_thresh": 0.6},
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{"seal_det_unclip_ratio": 0.5},
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{"seal_rec_score_thresh": 0.05},
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],
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)
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def test_predict_params(
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monkeypatch,
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ocr_engine: SealRecognition,
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params: dict,
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) -> None:
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check_wrapper_simple_inference_param_forwarding(
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monkeypatch,
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ocr_engine,
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"paddlex_pipeline",
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"dummy_path",
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params,
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)
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