PP LCNet x1 0 table cls Introduction The Table Classification Module is a key component in computer vision systems, responsible for classifying input table images. The performance of this module directly affects the accuracy and efficiency of the entire table recognition process. The Table Classification Module typically receives table images as input and, using deep learning algorithms, classifies them into predefined categories based on the characteristics and content of the images, such as wired and wireless tables. The classification results from the Table Classification Module serve as output for use in table recognition pipelines. The key metrics are as follow: Model Top1 Acc(%) GPU Inference Time (ms) [Regular Mode / High Performance Mode] CPU Inference Time (ms) [Regular Mode / High Performance Mode] Model Storage Size (M) PP LCNet x1 0 table cls 94.2 2.35 / 0.47 4.03 / 1.35 6.6M 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 Yo…
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