Welcome to the Spycrop! This web application, built with Flask and Python, utilizes computer vision to detect whether a person is wearing a mask. If the app detects the absence of a mask, it triggers an alert mechanism, such as sending an email or displaying a notification. This app was made during the covid era to help control the spread of the virus in confined campuses
- Mask Detection: Utilizes computer vision to identify whether the user is wearing a mask.
- Alert Mechanism: Sends an email or displays a notification if a mask is not detected.
- Flask Web Application: Built with Flask for the server-side logic.
- Python Backend: The backend is implemented in Python.
- User-friendly Interface: Provides a simple and intuitive web interface for users.
These instructions will help you set up and run the project on your local machine.
- Python 3 installed on your machine.
- Pipenv installed (for managing dependencies).
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Clone the repository to your local machine:
git clone https://github.com/annuraggg/SpyCrop-Desktop-App
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Navigate to the project directory:
cd Spycrop-Desktop-App -
Install dependencies using Pipenv:
pipenv install
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Activate the virtual environment:
pipenv shell
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Run the Flask App
Run the Flask application:
Open the app. Grant necessary permissions for camera access. Position yourself in front of the camera. The app will detect whether you are wearing a mask. If no mask is detected, the alert mechanism will be triggered.
To configure the alert mechanism (e.g., email notifications), follow these steps:
Open the app settings. Navigate to the "Alerts" section. Enter your email credentials or configure the notification settings.