SLANet plus Introduction Table structure recognition is an important component of table recognition systems, capable of converting non editable table images into editable table formats (such as HTML). The goal of table structure recognition is to identify the positions of rows, columns, and cells in tables. The performance of this module directly affects the accuracy and efficiency of the entire table recognition system. The table structure recognition module usually outputs HTML code for the table area, which is then passed as input to the tabl recognition pipeline for further processing. Model Accuracy (%) GPU Inference Time (ms) [Normal Mode / High Performance Mode] CPU Inference Time (ms) [Normal Mode / High Performance Mode] Model Storage Size (M) SLANet plus 63.69 140.29 / 140.29 195.39 / 195.39 6.9 M Installation 1. PaddlePaddle Please refer to the following commands to install PaddlePaddle using pip: For details about PaddlePaddle installation, please refer to the PaddlePaddle official website. 2. PaddleOCR Install the latest version of the PaddleOCR inference package from PyPI: Model Usage You can quickly experience the functionality with a single command: You can also int…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy