数据预处理和增广;算法模型训练

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readme.md

FOT OCR Model Deployment Project

This project involves the deployment of an FOTS model for OCR (Optical Character Recognition) on-site data collected from digital meters. The pipeline includes preprocessing the collected OCR image data, fine-tuning the FOTS model, and evaluating the model performance. This repository includes code for data preprocessing, training, and model evaluation.

Project Steps

  1. Data Import: Import the new data to be processed into the field_data directory.
  2. Navigate to OCR Code: Enter the code_ocr folder.
  3. Run Evaluation: Execute the evaluation script by running: bash ./eval.sh ## Code and Data Location - Server URL: 192.168.20.250 - Directory: /data/liudan/ocr ## Features - Data Preprocessing: Scripts to preprocess OCR images before feeding into the model. - Model Training: Code to fine-tune the FOTS model with the new data. - Model Evaluation: Scripts to assess the model's performance after fine-tuning. ## Contact For any inquiries, please contact the project team.