This project is a Streamlit web application that detects whether a person is wearing a face mask using a Convolutional Neural Network (CNN). The application offers three options for input: uploading an image, entering an image URL, or capturing a live image using a webcam.

• Image Upload: Upload an image from your device, and the app will classify whether the person in the image is wearing a mask or not.
• URL Input: Enter the URL of an image, and the app will fetch and classify the image.
• Live Image Capture: Capture a live image from your webcam and classify it.

1. Clone the repository:

   git clone https://github.com/alihassanml/Face-mask-detection-By-CNN.git

2. Navigate to the project directory:

   cd Face-mask-detection-By-CNN

3. Create a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

4. Install the required packages:

   pip install -r requirements.txt

1. Run the Streamlit application:

   streamlit run your_app.py

2. Open your web browser and go to the URL provided by Streamlit (usually http://localhost:8501).

3. Select the input method from the sidebar:

   • Image Upload: Upload an image file.
   • URL Input: Enter the URL of an image.
   • Live Image Capture: Capture an image from your webcam.

• Python 3.x
• TensorFlow
• OpenCV
• Pillow
• Requests
• Streamlit
• NumPy

You can find the requirements.txt file in the repository to install all dependencies.

• LinkedIn: Ali Hassan
• GitHub: alihassanml

Developed by: Ali Hassan