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The ability to automatically identify and extract tables from PDF documents is a highly sought-after feature. | ||
Automatically identifying and extracting tables from PDF documents is a highly desirable feature that many people are looking for. It's an exciting and active area of research, and our goal is to provide the community with access to the most effective tools available. | ||
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This is an active area of research and we aim to expose the best available tools to the community. This is a blend of newer deep learning approaches and traditional bounding box-based methods. We aim to be parsing algorithm agnostic and allow users to choose the method that best suits their needs. | ||
**By default this is turned off.** Parsing tables adds significant computational overhead, so we've made it optional. | ||
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We're expose both cutting-edge deep learning techniques with traditional bounding box-based methods. Our approach is designed to be flexible, allowing users to select the parsing algorithm that works best for their specific requirements. | ||
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At the moment, we offer three options for extracting tables from PDFs: `unitable`, `pymupdf`, and `table-transformer`. Each of these methods has its own unique advantages and limitations, so you can choose the one that aligns with your needs. | ||
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```python hl_lines="2" | ||
parser = openparse.DocumentParser( | ||
table_args={...} | ||
) | ||
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# ingesting the document | ||
parsed_10k = parser.parse(meta10k_path) | ||
``` | ||
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Currently, we support three methods for extracting tables from PDFs. | ||
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## Become a Contributor? | ||
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- If you have experience with quantizing models or optimizing them for inference, we would love to hear from you! Unitable achieves **state-of-the-art performance** on table extraction, but it is computationally expensive. We are looking to optimize the model for inference and reduce the size of the model. | ||
!!! note "Become a Contributor" | ||
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- If you have experience with quantizing models or optimizing them for inference, we would love to hear from you! Unitable achieves **state-of-the-art performance** on table extraction, but it is computationally expensive. We are looking to optimize the model for inference and reduce the size of the model. |
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