Image to Text Converter (OCR)

This project demonstrates an OCR (Optical Character Recognition) application built with EasyOCR and Streamlit. The app allows users to upload an image and extracts the text from the image using OCR technology.

Features

• OCR Functionality: Converts text from images (PNG, JPG, JPEG) to editable text using EasyOCR.
• Image Upload: Simple drag-and-drop image uploader in the UI.
• Text Output: Displays extracted text in a readable format.
• Easy Setup: Automatically initializes the OCR model and handles the image processing.

How it Works

1. Image Upload: The user uploads an image file (PNG, JPG, or JPEG).
2. Preprocessing: The image is converted to grayscale for improved OCR accuracy.
3. OCR Extraction: EasyOCR processes the image and extracts the text.
4. Text Display: The extracted text is displayed in a text area for easy copying.

Requirements

To run this project, you'll need the following libraries installed:

• streamlit
• easyocr
• numpy
• opencv-python
• Pillow

You can install these dependencies using pip:

pip install streamlit easyocr numpy opencv-python Pillow

Setup

1. Clone this repository or download the project files.
2. Install the required dependencies using the command above.
3. Run the Streamlit app:

streamlit run app.py

4. Open the app in your browser, upload an image, and view the extracted text!

Notes

• The OCR model is stored in the model_data directory. This directory will be created automatically if it doesn't exist.
• Currently, the app supports OCR for English text only. You can modify the language in the easyocr.Reader() initialization if you'd like to support other languages.

Contributing

Feel free to fork the project, make improvements, or add additional features! If you encounter any issues or have suggestions, please open an issue.

License

This project is licensed under the MIT License.