MusaTahawar/Video-Recorder

README

Video Capture and Recording with OpenCV

This Python script demonstrates how to capture video from the default camera using OpenCV, display it in real-time, and save it to a file. The script utilizes the OpenCV library, which provides a comprehensive suite of tools for computer vision tasks, including video processing.

Requirements:

• Python 3.x
• OpenCV library (opencv-python)

Installation:

1. Ensure you have Python installed on your system. If not, download and install it from python.org.
2. Install the OpenCV library by running the following command in your terminal or command prompt:

   pip install opencv-python
   

Usage:

1. Clone or download the repository containing the script.
2. Open a terminal or command prompt and navigate to the directory containing the script.
3. Run the script using the following command:

   python video_capture_and_record.py
   

4. Once the script is running, it will capture video from the default camera and display it in a window titled "frame".
5. Press the 'q' key to exit the video capture loop.
6. After exiting the loop, the captured video will be saved to a file named "output.avi" in the same directory as the script.

Notes:

• Ensure that your system has a camera connected and properly configured.
• The default codec used for video encoding is XVID. You can change it by modifying the fourcc variable in the script according to your requirements.
• Adjust the frame size and frame rate as needed by modifying the parameters in the cv2.VideoWriter constructor.
• This script captures video until the 'q' key is pressed. Modify the exit condition in the while loop as per your application's requirements.

References:

• OpenCV Documentation: https://docs.opencv.org
• Python Package Index (PyPI) - opencv-python: https://pypi.org/project/opencv-python/

For any issues or inquiries, please feel free to contact [Musa Tahawar/[email protected]/musatahawar.epizy.com].

Author: [Musa Tahawar]

License: This project is licensed under the [MIT], see the LICENSE file for details.

Acknowledgements: Special thanks to the OpenCV development team for providing such a powerful library for computer vision tasks.