This article provides a full-process guide for the PaddleOCR table recognition model, including data preparation, model training, tuning, evaluation, prediction, and detailed descriptions of each stage:
After the operation is completed, the acc indicator of the model will be output. If you evaluate the English table recognition model, you will see the following output.
Using the model trained by PaddleOCR, you can quickly get prediction through the following script.
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# 4. Model export and prediction
## 4.1 Model export
inference model (model saved by `paddle.jit.save`)
Generally, it is model training, a solidified model that saves the model structure and model parameters in a file, and is mostly used to predict deployment scenarios.
The model saved during the training process is the checkpoints model, and only the parameters of the model are saved, which are mostly used to resume training.
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└── inference.pdmodel # The program file of model
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## 5. FAQ
## 4.2 Prediction
After the model is exported, use the following command to complete the prediction of the inference model
