# Screenshot Capture Using Hand Gestures
This project enables users to take screenshots using hand gestures detected via a webcam. It leverages the MediaPipe library for hand detection and OpenCV for video processing. The logic uses the transition of hand gestures (from an open palm to a fist) to trigger a screenshot.
## Features
- Real-time hand gesture recognition.
- Screenshot capture when an open palm transitions to a fist gesture.
- Configurable and extensible for other gesture-based controls.
## Requirements
To run this project, you need the following dependencies:
- Python 3.7+
- OpenCV (`cv2`)
- MediaPipe (`mediapipe`)
- A library or function for taking screenshots, such as `ss_taker`. Replace `take_screenshot` in the code with your screenshot functionality.
## Installation
1. Clone the repository or download the source code.
2. Install the required Python packages:
```bash
pip install opencv-python mediapipe
```
3. Ensure your Python environment includes the `ss_taker` library or a custom implementation for taking screenshots.
## Usage
1. Save the script to a file, e.g., `gesture_screenshot.py`.
2. Run the script:
```bash
python gesture_screenshot.py
```
3. The webcam will activate, and the program will begin detecting hand gestures.
4. Show an open palm to the camera, then transition to a fist gesture to capture a screenshot.
5. Press `q` to quit the program.
## Usage Example
```python
from project_Screenshot.r_screenshot import take_screenshot , capture_screenshot
# to take normal screenshot
take_screenshot()
# for Gesture recognizer screenshot
capture_screenshot()
```
## How It Works
### Gesture Detection
The script uses the MediaPipe library to detect hand landmarks and determine whether the hand is open or closed:
- **Open palm:** All fingers extended (based on landmark positions).
- **Fist:** All fingers closed.
### Screenshot Trigger
When the script detects a transition from an open palm to a fist, it calls the `take_screenshot()` function to capture the current screen.
### Core Functions
#### `is_palm_open(landmarks)`
Determines whether the hand is open by comparing the positions of finger landmarks.
#### `capture_screenshot()`
Main function that:
- Captures video from the webcam.
- Processes each frame for hand landmarks.
- Detects gesture transitions and triggers screenshot capture.
## Customization
You can modify the script to:
- Recognize additional gestures.
- Perform other actions (e.g., send alerts or control devices) based on gestures.
## Limitations
- Requires a clear view of the hand for accurate detection.
- Designed for a single hand; might need enhancements for multi-hand detection.
## Acknowledgments
- [OpenCV](https://opencv.org/) for image processing.
- [MediaPipe](https://mediapipe.dev/) for hand landmark detection.
- [Github] (https://github.com/rohitkumyadav/Gesture-Screenshot.git) to view full source code
## Contributing
Contributions are welcome! If you have ideas for improvements or additional features, feel free to submit a pull request or open an issue.
## License
This project is licensed under the MIT License. See the LICENSE file for details.
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"description": "\n# Screenshot Capture Using Hand Gestures\n\nThis project enables users to take screenshots using hand gestures detected via a webcam. It leverages the MediaPipe library for hand detection and OpenCV for video processing. The logic uses the transition of hand gestures (from an open palm to a fist) to trigger a screenshot.\n\n## Features\n\n- Real-time hand gesture recognition.\n- Screenshot capture when an open palm transitions to a fist gesture.\n- Configurable and extensible for other gesture-based controls.\n\n## Requirements\n\nTo run this project, you need the following dependencies:\n\n- Python 3.7+\n- OpenCV (`cv2`)\n- MediaPipe (`mediapipe`)\n- A library or function for taking screenshots, such as `ss_taker`. Replace `take_screenshot` in the code with your screenshot functionality.\n\n## Installation\n\n1. Clone the repository or download the source code.\n2. Install the required Python packages:\n ```bash\n pip install opencv-python mediapipe\n ```\n3. Ensure your Python environment includes the `ss_taker` library or a custom implementation for taking screenshots.\n\n## Usage\n\n1. Save the script to a file, e.g., `gesture_screenshot.py`.\n2. Run the script:\n ```bash\n python gesture_screenshot.py\n ```\n3. The webcam will activate, and the program will begin detecting hand gestures.\n4. Show an open palm to the camera, then transition to a fist gesture to capture a screenshot.\n5. Press `q` to quit the program.\n\n## Usage Example\n\n```python\nfrom project_Screenshot.r_screenshot import take_screenshot , capture_screenshot\n\n# to take normal screenshot\ntake_screenshot()\n\n# for Gesture recognizer screenshot\ncapture_screenshot()\n```\n\n## How It Works\n\n### Gesture Detection\n\nThe script uses the MediaPipe library to detect hand landmarks and determine whether the hand is open or closed:\n- **Open palm:** All fingers extended (based on landmark positions).\n- **Fist:** All fingers closed.\n\n### Screenshot Trigger\n\nWhen the script detects a transition from an open palm to a fist, it calls the `take_screenshot()` function to capture the current screen.\n\n### Core Functions\n#### `is_palm_open(landmarks)`\nDetermines whether the hand is open by comparing the positions of finger landmarks.\n\n#### `capture_screenshot()`\nMain function that:\n- Captures video from the webcam.\n- Processes each frame for hand landmarks.\n- Detects gesture transitions and triggers screenshot capture.\n\n## Customization\nYou can modify the script to:\n- Recognize additional gestures.\n- Perform other actions (e.g., send alerts or control devices) based on gestures.\n\n## Limitations\n- Requires a clear view of the hand for accurate detection.\n- Designed for a single hand; might need enhancements for multi-hand detection.\n\n## Acknowledgments\n- [OpenCV](https://opencv.org/) for image processing.\n- [MediaPipe](https://mediapipe.dev/) for hand landmark detection.\n- [Github] (https://github.com/rohitkumyadav/Gesture-Screenshot.git) to view full source code\n\n## Contributing\nContributions are welcome! If you have ideas for improvements or additional features, feel free to submit a pull request or open an issue.\n\n## License\nThis project is licensed under the MIT License. See the LICENSE file for details.\n\n",
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