ROBOT_IMAGE_PROCESS_OCR_MODEL_TRAIN_v2.0.1

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.