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https://github.com/anant2003jain/textextractify

TextExtractify is an AI-powered tool that extracts text from images and PDFs using both Azure OCR and EasyOCR. It offers features like multi-image upload, text entity extraction, and .docx export for premium users. Designed to streamline document processing with fast, accurate text extraction.
https://github.com/anant2003jain/textextractify

azure login-system ocr ocr-python pillow python3 streamlit text-extraction

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TextExtractify is an AI-powered tool that extracts text from images and PDFs using both Azure OCR and EasyOCR. It offers features like multi-image upload, text entity extraction, and .docx export for premium users. Designed to streamline document processing with fast, accurate text extraction.

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README 

        
# **TextExtractify 📄🔍**

TextExtractify is a cutting-edge application designed to extract text from images and PDFs using powerful OCR technologies. With Azure OCR and EasyOCR at its core, TextExtractify offers a streamlined experience for users across different roles—whether you’re a free user or a premium subscriber looking for advanced features like PDF conversion and text extraction to .docx.



## Demo 🎥

https://github.com/user-attachments/assets/b3432af0-8f2e-43b5-814d-fda2723a8f46

## 🚀 Features

### 🔑 Free User Features:

* Single Image Upload: Upload an image to extract text using Azure OCR or EasyOCR.

* Text Entity Extraction: Detect entities within the extracted text for structured information.

* Basic PDF Processing: Convert and extract text from PDFs.

### 💼 Premium User Features:

* Batch Image Upload: Upload and process multiple images in one go.

* PDF to Text Conversion: Extract text from PDFs and convert it to .docx format.

* Download .docx Files: Each extracted text from images and PDFs can be downloaded as a .docx document.

* Optimized for Performance: Faster extraction time and priority access to new features.

### 🔥 Coming Soon:

* Multiple Language Support: Translate extracted text into various languages.

* Additional File Format Support: Expand beyond PDFs to Word, Excel, and other document types.

## 💡 How It Works

1. Upload Files: Users can upload image or PDF files from their system.

2. Choose OCR Engine: Select either Azure OCR or EasyOCR for processing.

3. Extract & Display: The app extracts text and displays it on the result page.

4. Download Options: Free users can copy or view the text, while premium users can download .docx files or process multiple images in one go.

## 🎨 User Interface

TextExtractify has a modern and responsive UI designed for a seamless user experience. The interface adapts to different devices and ensures smooth navigation for both free and premium users.



### Screenshots



**1. Login Page:**



   ![Login Page](https://github.com/user-attachments/assets/b7b2a81b-4c92-4cb2-b071-823eb4bb9172)



**2. Signup Page:**

  

  ![SignUp Page](https://github.com/user-attachments/assets/44fc4f2d-688c-47bf-b1d6-538a82de852e)



**3. Home Page:**



  ![Home Page](https://github.com/user-attachments/assets/4279c830-7423-4570-834c-a180115ee1fa)



**4. Free User Features**



![Free Features](https://github.com/user-attachments/assets/65f7f004-3387-44d0-ab51-6103729f754f)



**5. Premium User PDF View:**

  

  ![Premium PDF](https://github.com/user-attachments/assets/24963b86-8d75-40fa-aed8-f1f7e338c942)



## 🛠️ Tech Stack

### Backend:

* Python: Core language for all processing.

* Azure OCR / EasyOCR: OCR engines for text extraction.

* Streamlit: Web framework for creating interactive UIs.

* Pillow: For image handling.

### Frontend:

* HTML/CSS: For custom designs and styling.

### Database:

* Json: Used for managing user authentication and subscription data.

## 🧑‍💻 Installation & Setup

### Requirements:

* Python 3.7+

* Azure OCR API Key (for Azure OCR functionality)

### Instructions:

#### 1. Clone the repository:



* git clone https://github.com/Anant2003jain/TextExtractify.git



* cd TextExtractify



#### 2. Install the required packages:



* pip install -r requirements.txt

  

#### 3. Set up environment variables for Azure OCR:



* export AZURE_OCR_KEY=your_key_here

* export AZURE_OCR_ENDPOINT=your_endpoint_here

#### 4. Run the application:



* python -m streamlit run textex_app.py



* Visit http://localhost:8501 in your browser.



## 🔐 User Roles

* Free Users: Access basic OCR and text extraction features.

* Premium Users: Unlock advanced functionalities like batch image processing and downloadable .docx files.

## 🎯 Future Roadmap

* AI-powered Translations: Expanding language detection and translation capabilities.

* Improved Performance: Reducing processing time for large PDFs and image batches.

## 📝 License

* This project is licensed under the MIT License - see the [LICENSE](https://github.com/Anant2003jain/TextExtractify/blob/main/LICENSE) file for details.



## 🤝 Contributing

We welcome contributions from the community! To contribute:



1. Fork the repo.

2. Create your feature branch: git checkout -b feature/your-feature.

3. Commit your changes: git commit -m 'Add feature'.

4. Push to the branch: git push origin feature/your-feature.

5. Open a pull request.

## 🌟 Acknowledgements

* Azure OCR for their comprehensive OCR API.

* EasyOCR for providing a flexible open-source OCR solution.

* Streamlit for making app deployment seamless.