This Streamlit app provides a user-friendly interface for extracting and colorizing signatures from images.
- Image Upload: Upload images containing signatures in JPG, JPEG, or PNG format.
- Signature Selection: Draw a rectangle on the canvas to precisely select the signature region.
- Color Customization: Choose the desired color for your signature using a color picker.
- Threshold Adjustment: Fine-tune the extraction process by adjusting the threshold value.
- Processed Signature Output: View and download the extracted signature as an image file (PNG).
- New Image Upload: Easily upload a new image to extract a different signature.
-
Clone the Repository:
git clone https://github.com/pranaysuyash/img-ext.git cd img-ext -
Install Dependencies:
pip install -r requirements.txt
Note: Make sure you have a
requirements.txtfile in the root of your project with the following:streamlit opencv-python numpy pillow streamlit_drawable_canvas -
Run the App:
streamlit run app.py
- Streamlit Cloud may have limitations with OpenCV's graphics dependencies. You might need to simplify image processing or use cloud image processing services.
- To deploy to Streamlit Sharing, follow the instructions here.
- Heroku: Deploy to Heroku for more control over the environment. Visit Heroku for more information.
- Vultr: Deploy to a Vultr server for full customization. Visit Vultr for more information.
- Vultr: Follow the detailed instructions for setting up a Vultr server, installing dependencies, and configuring Nginx.
- Heroku: Refer to the Heroku documentation for Streamlit deployment.
Contributions are welcome! If you have any improvements or new features you'd like to add, please feel free to open an issue or submit a pull request.
This project is licensed under the MIT License. See the LICENSE file for details.
Check out the live demo: Signature Extractor Demo