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README.md
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- math-formula-recognition
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- mfr
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- pix2text
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- image-to-text
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license: mit
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library_name: transformers
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@@ -16,11 +17,11 @@ Mathematical Formula Recognition (MFR) model from [Pix2Text (P2T)](https://githu
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## Model Details / 模型细节
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This MFR model utilizes the [TrOCR](https://huggingface.co/docs/transformers/model_doc/trocr) architecture developed by Microsoft, starting with its initial values and retrained using a dataset of mathematical formula images.
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The resulting MFR model can be used to convert images of mathematical formulas into LaTeX text representation.
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此 MFR 模型使用了微软的 [TrOCR](https://huggingface.co/docs/transformers/model_doc/trocr) 架构,以其为初始值并利用数学公式图片数据集进行了重新训练。
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获得的 MFR 模型可用于把数学公式图片转换为 LaTeX 文本表示。
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## Documents / 文档
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- Pix2Text (P2T) Github: [breezedeus/pix2text](https://github.com/breezedeus/Pix2Text) ;
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- Pix2Text Online Free Service: [p2t.breezedeus.com](https://p2t.breezedeus.com/) ;
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- Pix2Text More: [breezedeus.com/pix2text](https://breezedeus.com/pix2text) ;
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这种方法无需安装 pix2text,但只能识别纯公式图片。
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```python
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#! pip install
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from PIL import Image
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from transformers import TrOCRProcessor
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from optimum.onnxruntime import ORTModelForVision2Seq
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这种方法需要安装 pix2text,借助 Pix2Text 中的数学公式检测模型(MFD),它不仅可以识别纯公式图片,还可以识别包含文本的混合图片。
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```bash
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$ pip install pix2text
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```
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```python
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#! pip install pix2text
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from pix2text import Pix2Text, merge_line_texts
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- math-formula-recognition
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- mfr
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- pix2text
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- p2t
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- image-to-text
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license: mit
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library_name: transformers
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## Model Details / 模型细节
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This MFR model utilizes the [TrOCR](https://huggingface.co/docs/transformers/model_doc/trocr) architecture developed by Microsoft, starting with its initial values and retrained using a dataset of mathematical formula images.
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The resulting MFR model can be used to convert images of mathematical formulas into LaTeX text representation. More detailed can be found: [Pix2Text V1.0 New Release: The Best Open-Source Formula Recognition Model | Breezedeus.com](https://www.breezedeus.com/article/p2t-v1.0).
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此 MFR 模型使用了微软的 [TrOCR](https://huggingface.co/docs/transformers/model_doc/trocr) 架构,以其为初始值并利用数学公式图片数据集进行了重新训练。
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获得的 MFR 模型可用于把数学公式图片转换为 LaTeX 文本表示。更多细节请见:[Pix2Text V1.0 新版发布:最好的开源公式识别模型 | Breezedeus.com](https://www.breezedeus.com/article/p2t-v1.0)。
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## Documents / 文档
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- [Pix2Text V1.0 New Release: The Best Open-Source Formula Recognition Model | Breezedeus.com](https://www.breezedeus.com/article/p2t-v1.0) ;
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- Pix2Text (P2T) Github: [breezedeus/pix2text](https://github.com/breezedeus/Pix2Text) ;
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- Pix2Text Online Free Service: [p2t.breezedeus.com](https://p2t.breezedeus.com/) ;
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- Pix2Text More: [breezedeus.com/pix2text](https://breezedeus.com/pix2text) ;
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这种方法无需安装 pix2text,但只能识别纯公式图片。
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```python
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#! pip install transformers>=4.37.0 pillow optimum
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from PIL import Image
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from transformers import TrOCRProcessor
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from optimum.onnxruntime import ORTModelForVision2Seq
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这种方法需要安装 pix2text,借助 Pix2Text 中的数学公式检测模型(MFD),它不仅可以识别纯公式图片,还可以识别包含文本的混合图片。
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```bash
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$ pip install pix2text>=1.0
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```
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```python
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#! pip install pix2text>=1.0
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from pix2text import Pix2Text, merge_line_texts
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