https://github.com/mrigank005/ocr
This Python script automates the extraction of text from images using Tesseract OCR. It processes all images in the test_images/ folder and saves the extracted text as .txt files in the extracted_texts/ directory, maintaining the original image filenames.
https://github.com/mrigank005/ocr
Last synced: about 1 year ago
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This Python script automates the extraction of text from images using Tesseract OCR. It processes all images in the test_images/ folder and saves the extracted text as .txt files in the extracted_texts/ directory, maintaining the original image filenames.
- Host: GitHub
- URL: https://github.com/mrigank005/ocr
- Owner: Mrigank005
- Created: 2025-05-02T23:09:16.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-05-02T23:27:11.000Z (about 1 year ago)
- Last Synced: 2025-05-13T20:28:08.134Z (about 1 year ago)
- Language: Python
- Homepage:
- Size: 336 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🖼️ OCR Text Extractor
This Python script automates the extraction of text from images using Tesseract OCR. It processes all images in the `test_images/` folder and saves the extracted text as `.txt` files in the `extracted_texts/` directory, maintaining the original image filenames.
---
## 📁 Project Structure
```
OCR-Text-Extractor/
├── OCR.py
├── test_images/
│ └── image1.jpg
│ └── image2.png
├── extracted_texts/
│ └── image1.txt
│ └── image2.txt
└── README.md
```
---
## ⚙️ Features
* Batch processes `.jpg`, `.jpeg`, and `.png` images.
* Supports multiple languages (default: English and Hindi).
* Automatically creates the `extracted_texts/` folder if it doesn't exist.
* Provides informative logging for each processed file.([GitHub][2])
---
## 🚀 Getting Started
### 1. Clone the Repository
```bash
git clone https://github.com/Mrigank005/OCR
cd OCR
```
### 2. Install Dependencies
Ensure you have Python 3 installed. Then, install the required Python libraries:
```bash
pip install pillow pytesseract
```
### 3. Install Tesseract OCR Engine
* **Windows**: Download and install from [Tesseract OCR Windows Installer](https://github.com/tesseract-ocr/tesseract/wiki).
* **macOS**: Use Homebrew:([GitHub][1])
```bash
brew install tesseract
```
* **Linux (Debian/Ubuntu)**:
```bash
sudo apt-get install tesseract-ocr
```
Ensure Tesseract is added to your system's PATH.
### 4. Add Images
Place the images you want to process into the `test_images/` directory.
### 5. Run the Script
```bash
python OCR.py
```
The extracted text files will be saved in the `extracted_texts/` directory.
---
## 📝 Customization
* **Language Support**: The script defaults to English and Hindi. To modify the languages, edit the `langs` parameter in the `extract_text_and_save` function within `OCR.py`:
```python
def extract_text_and_save(image_path, langs=["eng", "hin"]):
```
Refer to [Tesseract OCR Language Data](https://github.com/tesseract-ocr/tesseract/blob/main/doc/tesseract.1.asc#languages) for available language codes.([GitHub][1])
* **Tesseract Path**: If Tesseract isn't in your system's PATH, specify its location in `OCR.py`:
```python
import pytesseract
pytesseract.pytesseract.tesseract_cmd = r'/path/to/tesseract'
```
---
## 🧪 Sample Output
For an image named `page1.jpg` in `test_images/`, the script will generate `page1.txt` in `extracted_texts/` containing the recognized text.
---
## 🙌 Acknowledgements
* [Tesseract OCR](https://github.com/tesseract-ocr/tesseract)
* [pytesseract](https://pypi.org/project/pytesseract/)
* [Pillow](https://pypi.org/project/Pillow/)
---