mirror of
https://github.com/PaddlePaddle/PaddleOCR.git
synced 2025-06-03 21:53:39 +08:00
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>
65 lines
1.7 KiB
Python
65 lines
1.7 KiB
Python
import pytest
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from paddleocr import TableRecognitionPipelineV2
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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 table_recognition_v2_pipeline():
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return TableRecognitionPipelineV2()
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@pytest.mark.parametrize(
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"image_path",
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[
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TEST_DATA_DIR / "table.jpg",
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],
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)
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def test_visual_predict(table_recognition_v2_pipeline, image_path):
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result = table_recognition_v2_pipeline.predict(
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str(image_path), use_doc_orientation_classify=False, use_doc_unwarping=False
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)
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check_simple_inference_result(result)
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res = result[0]
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assert len(res["table_res_list"]) > 0
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assert isinstance(res["table_res_list"][0], dict)
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assert len(res["table_res_list"][0]["cell_box_list"]) > 0
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assert isinstance(res["table_res_list"][0]["pred_html"], str)
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assert isinstance(res["table_res_list"][0]["table_ocr_pred"], dict)
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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},
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{"use_doc_unwarping": False},
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{"use_layout_detection": False},
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{"use_ocr_model": False},
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{"text_det_limit_side_len": 640, "text_det_limit_type": "min"},
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{"text_det_thresh": 0.5},
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{"text_det_box_thresh": 0.3},
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{"text_det_unclip_ratio": 3.0},
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{"text_rec_score_thresh": 0.5},
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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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table_recognition_v2_pipeline,
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params,
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):
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check_wrapper_simple_inference_param_forwarding(
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monkeypatch,
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table_recognition_v2_pipeline,
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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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# TODO: Test constructor and other methods
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