abdullah-129 / adidentity-scan-personalized-ads-powered-by-face-detection

This project contains, Winforms application for Desktop and Python Script for playing ads and detecting age and gender

Ads using Face Detection

This project involves a Winforms application for desktop and a Python script for playing ads and performing age and gender detection using face detection.

Additional Python Libraries Required:

• OpenCV
• Install with: pip install opencv-python
• argparse
• Install with: pip install argparse

Contents of the Main/Script File:

• opencv_face_detector.pbtxt
• opencv_face_detector_uint8.pb
• age_deploy.prototxt
• age_net.caffemodel
• gender_deploy.prototxt
• gender_net.caffemodel

The .pb and .pbtxt files are protobuf files that define the graph and trained weights of the face detection model. The .prototxt files describe the network configuration, and the .caffemodel files define the internal states of the parameters for age and gender detection.

Usage:

Downloading the Repository:

• Download the repository or the Setup.exe file from the following link: link

Using the Downloaded Repository:

• Change the directory to the folder where all the files are located.
• Navigate to Ads_system/bin/Debug/net6.0-windows/.
• Run the Ads_system.exe file.

Using the Downloaded Setup:

• Open the Ads_system.exe file.
• Enter the setup password: 12345678.
• Install the setup only at D: drive (otherwise, it won't work).
• After installation, a shortcut will appear on the desktop.

Features:

• The interface contains three buttons.
• 👨 Male button: Opens a folder to manage ads for males.
• 👩 Female button: Opens a folder to manage ads for females.
• ▶️ Run button: Runs the script.

For Script:

Visit: GitHub Repository

🤝 Contributing

Contributions to this project are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request.

📄 License

This project is licensed under the MIT License.

🙏 Acknowledgments

• The age and gender prediction models are based on the work of Gil Levi and Tal Hassner.
• The face detection model is based on the work of OpenCV.

🔗 References

• OpenCV
• Age and Gender Classification Using Convolutional Neural Networks