Version 1.1

• PDF crop
• Epub Converter

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Version 1.0 Initial realease

• OCR
• Font Converter

OCR App Setup Guide

This README provides instructions on how to set up and run the OCR application on macOS. Users of Windows or Linux can follow these instructions with minor adjustments.

Prerequisites

Ensure that Python (version 3.6 or later) is installed on your system. If not, download and install it from python.org.

Create Google Cloud Vision Service Account.

You need to replace cloud_vision_service_acc.json with your own credentials. Ref: https://daminion.net/docs/how-to-get-google-cloud-vision-api-key/

Step 1: Clone the Repository

First, clone the OCR application repository from GitHub. Open your terminal and execute the following command:

git clone https://github.com/nchanko/myanocr_pub.git
cd myanocr_pub

Step 2: Create a Virtual Environment

It is recommended to use a virtual environment to manage and isolate the application dependencies. Use the following commands to create and activate a virtual environment:

On macOS and Linux:

python3 -m venv venv               # Create a virtual environment
source venv/bin/activate  

On windows:

python -m venv venv                # Create a virtual environment
.\venv\Scripts\activate            # Activate the virtual environment

Step 3: Install Dependencies

With the virtual environment activated, install the required packages specified in the requirements.txt file: You may also need to install packages separately.

pip install -r packages.txt

pip install -r requirements.txt  

Step 4: Run the Application

After installing the dependencies, the application is ready to be launched. Start the OCR application using Streamlit by running the following command:

streamlit run ocr.py

This command will start the Streamlit server. You can access the application by navigating to http://localhost:8501 in your web browser.