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PP LCNet X1 0 Table Cls

Developed by PaddlePaddle
PP-LCNet_x1_0_table_cls is an efficient table classification model used to classify input table images and supports the classification of lined tables and borderless tables.
Downloads 1,141
Release Time : 6/6/2025

Model Overview

This model is a key component in the table recognition process and can classify table images into predefined categories, such as lined tables and borderless tables, based on their features and content. The classification results directly affect the accuracy and efficiency of the entire table recognition process.

Model Features

Efficient inference
The model shows efficient inference speed on both GPUs and CPUs, making it suitable for practical application scenarios.
High accuracy
The Top1 accuracy reaches 94.2%, enabling reliable classification of table images.
Lightweight
The model's storage size is only 6.6M, making it suitable for resource-constrained environments.

Model Capabilities

Table image classification
Lined table recognition
Borderless table recognition

Use Cases

Document processing
Table recognition process
In the table recognition process, this model is first used to classify table images, and then subsequent processing is carried out based on the classification results.
Improve the accuracy and efficiency of table recognition.
Automated office
Table data extraction
Used for table data extraction in automated office scenarios, such as financial statements, invoices, etc.
Classify tables quickly and accurately to facilitate subsequent data extraction.
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