# 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.