Using warping feature to detect documents and correct them for the viewer

This mini project focuses on detecting documents in a video stream or image using computer vision techniques and applying a perspective transformation to obtain a flattened view of the document. The primary goal is to automate the process of identifying documents within a scene, even when the documents are tilted or skewed, and then rectify them to appear as if viewed from directly above.

• Live Document Detection: The project supports real-time document detection from a video stream, making it applicable for scenarios where documents are present in dynamic environments.

• Perspective Transformation: Once a document is detected, the program performs a perspective transformation to warp the document into a flat, top-down view, facilitating easier analysis or processing.

• User Interaction: Users can interact with the system by adjusting parameters such as video source, frame size, and contour area threshold to fine-tune the document detection process.

To run this project, ensure that you have the following prerequisites installed:

• Python 3.x
• OpenCV
• NumPy

1. Clone the repository to your local machine.

   git clone https://github.com/Abdelghafour2001/Document_Warping_OpenCV.git
   cd Document_Warping_OpenCV