Metasebiya-21/amharic-ocr-prepocessor

Amharic Hand Written Text Preprocessor for Training BLSTM Model # Amharic Handwritten Text Preprocessing This project involves preprocessing scanned handwritten Amharic text images and segmenting them into individual sentences. The provided image preprocessing script processes the input image to detect and extract each sentence. ## Features - Image preprocessing for scanned handwritten text - Sentence segmentation - Support for Amharic script ## Requirements - Python 3.x - OpenCV - NumPy - Matplotlib (optional, for visualization) ## Installation 1. Clone this repository: ```bash git clone github.com ``` 2. Navigate into the project directory: ```bash cd amharic-image-preprocessing ``` 3. Install the required Python packages: ```bash pip install -r requirements.txt ``` ## Usage 1. Place your scanned handwritten text image in the `images` directory. Ensure the image is in a format supported by OpenCV (e.g., PNG, JPEG). 2. Run the preprocessing script: ```bash python preprocess.py --image images/your_image.png ``` Replace `your_image.png` with the name of your image file. 3. The script will output the segmented sentences as individual images in the `output` directory. ## Example Below is an example of the preprocessing steps: ### After Image Pre-Processing #### input image with pre-processed image after projection ### Segmented Sentences The output will be individual images for each sentence, saved in the `output` directory. ## Contributing Contributions are welcome! Please feel free to open issues or submit pull requests. ## License This project is licensed under the MIT License. See the LICENSE file for details. ## Acknowledgements - OpenCV - Open Source Computer Vision Library. - NumPy - Library for scientific computing with Python. - Matplotlib - Plotting library for Python (optional, for visualization). ## Contact For any inquiries or support, please contact [your.email@example.com].