Face Detection Project code using Python


  • In our system the face detection is performed on frames acquired from real time video.
  • Then a face classification method that uses Convolutional Neural Network is integrated in the system.
  • The system use standard images, and detection algorithm to train itself, extract faces, and detect the face.

Objectives of Face Detection

To implement a face net system to produce facial Detection application.

To design a system that can detect and recognize faces in real time.

Functional requirements of Face Detection

  • Can detect multiple faces in a real-time video.
  • Acquiring frames from real time video.
  • Train the system module.
  • Create classifier files of the data set.
  • User friendly interface.
  • Enter new data or check user.
  • Robust and machine friendly.
  • Enter user Id/Name.
  • Collect Data Set.
  • Train Data model.
  • Create classifiers.
  • Select user.
  • Recognize face.
  • Show Id/Name.

Non-Functional Requirements of Face Detection

  • Robustness
  • Stability
  • Accuracy
  • Security

Tools and Technologies used in Face Detection

Operating System : Linux (Ubuntu)  64 bit / Windows 64 bit

Hardware : 4 GB-RAM, Webcam

Programming Language : Python

Computer Vision Library : OpenCV

GUI Library: Tkinter

Algorithm : LBPH (Local Binary Pattern Histogram)

Modules of Face Detection

Our system have following Modules.

  • App_GUI: Runs the application of user interface.
  • Collect data set: Collect frames from runtime video.
  • Trainer: Train the dataset and create classifiers.
  • Face Recognizer: By using data classifiers recognizes the person in real-time and displays the Id.






Download full project code of Face Detection in Python

Download Face Detection PPT Presentation of Project

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