This is a simple Flask web application for signature detection using a pre-trained deep learning model. Users can upload an image, and the application will determine whether a signature is present in the image or not.
Before running this application, make sure you have the following dependencies installed:
- Python 3.x
- Flask
- OpenCV (cv2)
- NumPy
- Keras (with a pre-trained signature detection model)
- HTML/CSS for web templates
You can install Python dependencies using pip:
pip install flask opencv-python-headless numpy keras
Customization: You can customize this application for your specific needs:
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Modify the model: Replace signature_detection_model.h5 with your trained model for signature detection.
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Adjust the image preprocessing: Modify the preprocess_image function in app.py to match your model's input requirements.
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Update the HTML templates: Customize the index.html and results.html templates to match your application's branding and user interface.
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Tune the confidence threshold: In app.py, you can change the confidence threshold (0.5 by default) to control when the application classifies an image as having a signature or not.
