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4040[ TableRecognitionMetric 评测工具] ( https://github.com/SWHL/TableRecognitionMetric ) [ huggingface数据集] ( https://huggingface.co/datasets/SWHL/table_rec_test_dataset ) [ modelscope 数据集] ( https://www.modelscope.cn/datasets/jockerK/TEDS_TEST/files ) [ Rapid OCR] ( https://github.com/RapidAI/RapidOCR )
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42- 注: StructEqTable 输出为 latex,只取成功转换为html并去除样式标签后进行测评
42+ 测试环境: ubuntu 20.04 python 3.10.10 opencv-python 4.10.0.84
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44+ 注: StructEqTable 输出为 latex,只取成功转换为html并去除样式标签后进行测评
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4446| 方法 | TEDS | TEDS-only-structure |
4547| :---------------------------------------------------------------------------------------------------------------------------| :-----------:| :-------------------:|
@@ -155,6 +157,7 @@ flowchart TD
155157[ Qanything-RAG] ( https://github.com/netease-youdao/QAnything )
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157159非常感谢 llaipython(微信,提供全套有偿高精度表格提取) 提供高精度有线表格模型。
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158161非常感谢 [ MajexH] ( https://github.com/MajexH ) 完成deepdoctection(rag-flow)的表格识别测试
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160163### 贡献指南
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