latest/en/version3.x/pipeline_usage/PP-StructureV3

[giscus[bot]]

latest/en/version3.x/pipeline_usage/PP-StructureV3

Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)

https://www.paddleocr.ai/latest/en/version3.x/pipeline_usage/PP-StructureV3.html

[Lafitte1573]

here is my script:

from paddleocr import PPStructureV3

input_file = "3ul2Rq4Sk5Cn-l69D695U.png"
pipeline = PPStructureV3(
    # models
    text_recognition_model_name="PP-OCRv5_mobile_rec",
    text_detection_model_name="PP-OCRv5_mobile_det",
    # table_classification_model_name="PP-LCNet_x1_0_table_cls",
    # wired_table_cells_detection_model_name="SLANeXt_wired",
    formula_recognition_model_name="PP-OCRv5_mobile_rec",  # "PP-OCRv5_mobile_rec",
    layout_detection_model_name="PP-DocBlockLayout",  # "PP-DocBlockLayout",
    region_detection_model_name="PP-DocBlockLayout",
    # model dirs
    text_recognition_model_dir='/mnt/public/public_file/models/PP-OCRv5_mobile_rec',
    text_detection_model_dir='/mnt/public/public_file/models/PP-OCRv5_mobile_det',
    # table_classification_model_dir='/mnt/public/public_file/models/PP-LCNet_x1_0_table_cls',
    # wired_table_cells_detection_model_dir="/mnt/public/public_file/models/SLANeXt_wired",
    formula_recognition_model_dir='/mnt/public/public_file/models/PP-OCRv5_mobile_rec',
    layout_detection_model_dir='/mnt/public/public_file/models/PP-DocBlockLayout',
    region_detection_model_dir='/mnt/public/public_file/models/PP-DocBlockLayout',
    # Use options
    use_doc_orientation_classify=False,
    # # Use use_doc_orientation_classify to enable/disable document orientation classification model
    use_doc_unwarping=False,  # Use use_doc_unwarping to enable/disable document unwarping module
    use_textline_orientation=False,
    # # Use use_textline_orientation to enable/disable textline orientation classification model
    use_seal_recognition=False,
    use_table_recognition=False,
    use_chart_recognition=False,
    device="gpu",  # Use device to specify GPU for model inference
)
output = pipeline.predict(input=input_file)

for res in output:
    res.print() # Print the structured prediction output
    res.save_to_json(save_path="output") ## Save the current image's structured result in JSON format
    res.save_to_markdown(save_path="output")

Why is my output Markdown file blank?

[liuhongen1234567]

Hello, you can try setting the layout_detection_model_dir to PP-DocLayout_plus-L. PP-DocBlockLayout is a block detection model that only detects the block category, not a layout model.

[Lafitte1573]

Thanks a lot. I changed the layout_detection_model to PP-DocLayout_plus-L, and this problem was successfully fixed. 😄😄😄

[w2918000]

请问下面dict的中类别ID是在哪里定义的？

layout_threshold 版面模型得分阈值。
float：0-1 之间的任意浮点数；
dict： {0:0.1} key为类别ID，value为该类别的阈值；
None：如果设置为None，将使用产线初始化的该参数值，默认初始化为 0.5。

[w2918000]

或者说每一项id具体对应的目标是什么

[liuhongen1234567]

您好，可以下载具体的版面模型然后查看inference.yaml 的 label_list 文件，从0开始依次编号。 如果是 PP-Structurev3的默认版面模型可以直接参考 PP-Structurev3 产线配置文件

https://github.com/PaddlePaddle/PaddleX/blob/1f63f83829c8242a1655127b760206ae5faa30e8/paddlex/configs/pipelines/PP-StructureV3.yaml#L19

[naked34501]

你好 ，我想问下 版面识别是否可以在识别的时候自动忽略印章？检验合同文档OCR的时候如何解决文字被印章覆盖的问题，导致OCR出来包含部分印章文字？同时印章的文字识别也被原本的合同文字遮挡导致失败？是否能进行两边的分离检查？万分感谢！

[w2918000]

你好，有个问题咨询下，我想知道在使用PP-StructureV时如何调整表格识别下单元格识别的threshold参数

[kyle-hy]

公式乱码：
$$P_{\mathrm{SRD}}=\frac{3.6nK_{\mathrm{DL}}K_{\mathrm{DY}}}{tK}\times10^3\quad\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots P P_{P_{{{\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots P_{{\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots P_\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots P_\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots P_\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots P_\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots P_{\cdots\cdots\cdots\cdots\cdots P_{\cdots\cdots\cdots\cdots\cdots\cdots P_\cdots\cdots\cdots\cdots\cdots P_{\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots\cdots P_\cdots\cdots\cdots\cdots\cdots\cdots\cdots P_\cdots\cdots\cdots\cdots P_{\cdots\cdots\cdots\cdots\cdots\cdots P_\cdots\cdots\cdots\cdots\cdots\cdots P_\cdots\cdots\cdots\cdots P_{\cdots\cdots\cdots\cdots\cdots P_\cdots\cdots\cdots\cdots P_\cdots\cdots\cdots\cdots\cdots P_\cdots\cdots\cdots P_\cdots{\cdots\cdots P_\cdots\cdots\cdots P_\cdots\cdots\cdots\cdots P_\cdots\cdots\cdots\cdots P_\cdots\cdots\cdots P_{\cdots\cdots\cdots\cdots P_\cdots\cdots\cdots P_\cdots\cdots\cdots\cdots P_\cdots\cdots P_\cdots P_{\cdots\cdots\cdots\cdots\cdots P_\cdots\cdots\cdots\cdots P_\cdots P_\cdots\cdots\cdots\cdots\cdots P_\cdots\cdots P_\cdots\cdots P_{\cdots\cdots\cdots P_\cdots\cdots P_\cdots\cdots\cdots P_\cdots\cdots\cdots P_\cdots\cdots P_\cdots\cdots P_\cdots\cdots P_\cdots\cdots\cdots P_\cdots\cdots P_\cdots P_{\cdots\cdots P_\cdots P_\cdots\cdots\cdots\cdots P_\cdots P_\cdots\cdots\cdots P_\cdots\cdots P_\cdots P_\cdots\cdots P_\cdots\cdots P_\cdots P_{\cdots\cdots\cdots\cdots P_\cdots P_\cdots\cdots P_\cdots P_\cdots P_\cdots P_\cdots\cdots P_\cdots P_{\cdots P_\cdots\cdots P_\cdots\cdots\cdots P_\cdots P_\cdots\cdots P_\cdots P_\cdots P_\cdots P_\cdots P_\cdots\cdots P_\cdots P_\cdots P_\cdots P_\cdots P_{\cdots P_\cdots P_\cdots P_\cdots\cdots P_\cdots P_\cdots\cdots P_\cdots P_{\cdots P_\cdots P_\cdots P_\cdots P_\cdots P_\cdots P_\cdots\cdots\cdots P_\cdots P_\cdots P_\cdots P_\cdots P_\cdots\cdots P_\cdots P_\cdots\cdots P_\cdots P_\cdots P_\cdots\cdots P_\cdots P_\cdots P_{\cdots P_\cdots P_\cdots P_\cdots P_\cdots\cdots P_\cdots P_\cdots P_\cdots P_\cdots P_\cdots\cdots P_\cdots P_\cdots P_\cdots P_\cdots\cdots P_\cdots P_\cdots P_\cdots{\cdots P_\cdots P_\cdots P_\cdots\cdots P_\cdots P_\cdots P_\cdots P_\cdots $$

[liuhongen1234567]

您好，能否提供一下测试的图片呢？由于公式采用的是自回归架构，在一些域外数据上确实可能出现幻觉，导致输出乱码。

[kyle-hy]

《070 泵类系统电能平衡测试与计算方法-GBT13468-1992.pdf》这篇国标文档。找不到上传图片或文件的地方

[kyle-hy]

不对表格做提取，但如果表格中有公式，则表格图片中的公式就会被抠掉。咋整？？

[Mirorrn]

Hi :)
Is there an official way to extract tables with captions?

[deepak7376]

can we quantize the model into less precision like int8 for this pipeline

from paddleocr import PPStructureV3