This repository contains the source code for a facial recognition software built using JavaScript. The software is designed to detect and recognize human facial emotions in images or real-time video streams.
- Face detection: The software utilizes machine learning algorithms to detect human faces in images or video streams. It can detect multiple faces in an image or video frame, and it provides bounding box coordinates around each detected face.
- Facial emotion recognition: The software includes facial emotion recognition capabilities, allowing it to recognize known facial from a pre-trained database. It can match detected faces with known facial emotions based on facial features, and it can identify the recognized facial expression with labels or names.
- Real-time detection: The software supports real-time facial emotion detection and recognition in video streams, allowing it to be used for live applications, such as video surveillance, access control, or user authentication.
- Customizable recognition database: The software allows users to create and manage their own recognition database, where they can add, update, or remove known faces for recognition. The database can be easily customized to suit specific recognition requirements.
- User-friendly interface: The software provides a user-friendly interface for configuring settings, managing the recognition database, and visualizing the detected and recognized faces. It may include a graphical user interface (GUI) or a web-based interface for easy interaction.
- JavaScript: The software is built using JavaScript, a popular programming language for web development and machine learning.
- Face detection and recognition libraries: The software may utilize existing JavaScript libraries for face detection and recognition, such as face-api.js, tensorflow.js, or OpenCV.js.
- Web-based interface: If the software includes a web-based interface, it may use HTML, CSS, and other web technologies for rendering the user interface and displaying the detected and recognized faces.
- Backend server: The software may require a backend server for handling image or video processing tasks, managing the recognition database, and serving the web-based interface.
- Machine learning models: The software may use pre-trained machine learning models for face detection and recognition. These models may be trained using deep learning algorithms and large datasets of labeled facial images.
To set up the facial recognition software locally, follow these steps:
- Clone the repository to your local machine using the following command:
git clone https://github.com/pharaohmak/facial-recognition-software.git
- Navigate to the project directory:
cd facial-recognition-software
- Install any dependencies or libraries required for the software.
- Configure the recognition database, if applicable, with known faces and labels.
- Run the software using the provided scripts or commands, and follow any instructions for usage.
If you would like to contribute to the project, please follow these steps:
- Fork the repository to your own GitHub account.
- Create a new branch from the
mainbranch with a descriptive name for your changes. - Make your changes to the code and test them thoroughly.
- Submit a pull request to the
mainbranch of the original repository. - Provide a clear description of the changes made and any relevant information for review.
This facial recognition software is open source and available under the MIT License.
For any inquiries or questions, please contact the project owner at alchemist@sleepingpharaoh.com.
Thank you for your interest in the Facial Recognition Software!
Web Dev Simplified
1.42M subscribers
🌎 Find Me Here: