GestureFlow

This Python-based project enables interactive control of presentation slides through hand gestures captured via a webcam. Using OpenCV and CVZone libraries, the application recognizes specific gestures to navigate slides and perform annotations in real-time. It's designed to provide an engaging and hands-free experience for presentations.

Description

The project offers an intuitive interface, allowing users to control presentation slides through recognized hand gestures captured in real-time via a webcam. With this system, presenters can effortlessly transition between slides, draw annotations, and use their finger as a pointer during presentations.

Key Features

• Gesture Control - Navigate slides with left and right hand gestures, mimicking page flipping for seamless transitions.

• Annotation - Draw on slides using hand gestures, enabling on-the-fly illustrations or emphasis during presentations.

• Pointer Mode - Use the index finger as a virtual pointer, enhancing interaction and engagement with specific elements on slides.

• Clear Annotations - Instantly clear drawn annotations with a specific gesture, ensuring a clean canvas for further interactions.

Technologies Used

• Python : The project's core language for developing the application's functionalities and logic.
• OpenCV (cv2) : Handles webcam access, image manipulation, and gesture recognition to control slide navigation and annotations.
• NumPy : Assists in efficient handling and manipulation of image data for gesture recognition and processing.
• CVZone : Provides specialized tools and functions for precise hand tracking and gesture-based interactions within the presentation slides.

Requirements and Configurations

Requirements -

• Python 3.x
• Webcam

Configurations -

• Adjust webcam resolution via width and height variables.
• Modify FolderPath to the directory containing presentation slides in main.py file.
• Fine-tune gestureThreshold, button_delay, and other parameters as needed.

Deployment

Accessing the project involves a few steps:

Step 1 : Clone the Repository :

  git clone https://github.com/AkshataKamerkar/GestureFlow.git

Step 2 : Set Up Environment and Dependencies

• Install Python : Ensure Python (preferably Python 3.x) is installed on your system.

• Install Required Libraries : Navigate to the project directory and install the necessary Python libraries by running -

  pip install -r requirements.txt

If there's a requirements.txt file in the project, this command installs all the dependencies needed for the project to run.

Step 3 : Configure and Run the Project

• Place Presentation Slides : Follow the project's instructions to place the presentation slides in the designated folder (ppt or as specified).

• Adjust Configuration (if required) : Modify any configuration parameters in the code if needed, such as webcam resolution or folder paths.

• Run the Script : Execute the Python script that controls the presentation slides -

  python main.py

• Interact with the Presentation : Use the hand gestures as specified in the project's README to control and interact with the presentation slides via the webcam.

Step 4 : Quitting the Application Press the specified keyboard key 'q' to exit or close the application when done.

Conclusion

The system offers a convenient gesture-based command to swiftly clear annotations. With a specific gesture, presenters can reset the slide, removing any drawn annotations instantly. This functionality ensures a clean slate for new annotations or a clear view of the original slide content.

Contributors

• ak_639
• shubham-murtadak
• ItachiUchiha08