v1.0.0

Release v1.0.0 - Facial Attribute Extraction with OpenCV/Deep Learning

We are excited to announce the release of our Python library for facial attribute extraction using OpenCV and Deep Learning. This library allows you to extract various facial attributes from images or live webcam feeds. Whether you want to analyze facial expressions, detect gender, estimate age, or identify facial landmarks, this library has got you covered.

Key Features:

• Facial attribute extraction: Extract facial attributes such as Smiling, Wearing_Earrings, Young, and Big_Lips etc.
• OpenCV integration: Leverage the power of OpenCV for face detection and image preprocessing.
• Deep Learning models: Utilize state-of-the-art Deep Learning models to achieve accurate facial attribute extraction.
• Docker file included: We provide a Docker file for easy deployment and containerization of the library.
• Real-time testing: Test the library's functionality in real-time using a webcam.

Getting Started:

To get started, simply follow the instructions in the README file to install the library and its dependencies. You can find examples and documentation to guide you through the usage of various facial attribute extraction functionalities. We have also included a comprehensive guide on how to set up the Docker environment for deployment.

Contributions and Feedback:

We welcome contributions from the community to further enhance this library. If you encounter any issues or have suggestions for improvement, please feel free to open an issue on GitHub. We value your feedback and strive to make this library as robust and user-friendly as possible.

Try it Out:

We invite you to explore the capabilities of our facial attribute extraction library. Extract facial attributes from images, experiment with real-time webcam analysis, and integrate it into your own applications. We look forward to seeing the creative ways you leverage this library for facial attribute analysis.