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https://github.com/PaddlePaddle/PaddleOCR.git
synced 2025-06-03 21:53:39 +08:00
* 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>
44 lines
1.0 KiB
Python
44 lines
1.0 KiB
Python
import pytest
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from paddleocr import DocUnderstanding
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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() -> DocUnderstanding:
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return DocUnderstanding()
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@pytest.mark.resource_intensive
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@pytest.mark.parametrize(
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"input",
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[
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{
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"image": str(TEST_DATA_DIR / "medal_table.png"),
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"query": "识别这份表格的内容",
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},
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{
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"image": str(TEST_DATA_DIR / "table.jpg"),
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"query": "识别这份表格的内容",
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},
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],
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)
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def test_predict(ocr_engine: DocUnderstanding, input: dict) -> None:
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"""
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Test PaddleOCR's doc understanding functionality.
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Args:
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ocr_engine: An instance of `DocUnderstanding`.
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input: Input dict to be processed.
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"""
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result = ocr_engine.predict(input)
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check_simple_inference_result(result)
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res = result[0]
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assert res["result"] is not None
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assert isinstance(res["result"], str)
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