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#---------------------------------- IMPORTENT: TO RUN THESE APPLICATIONS YOU NEED TO HAVE ---------------------------------- #--------------------------------------------- OPENCV CONTRIB INSTALLED ---------------------------------------------
#Detector_Video.py: This file detects faces using Haar cascades. It works fine with multiple faces.
#Face_Capture_With_Rotate.py: Running this file will capture 50 images of a person infront of the camera. It will make sure photos are not dark and
#Free_Rotate.py: This file shows the rotate function. Make sure you uncomment line 153 in NameFind.py This will show the image correcting the offset.
#NameFind.py: This file contains all the functions.
#Trainer_All.py: This file will train all the recognition algorithms using the images in the dataSet folder.
#Recogniser_Image_All_Algorithms.py: This application will detect and recognise faces from images. Diffrent images can be selected.
#Recogniser_Video_EigenFace.py: This File is the will recognise faces from the camera feed using Eigen face algorithm.
#Recogniser_video_FisherFace.py: This File is the will recognise faces from the camera feed using Fisher face algorithm.
#Recogniser_Video_LBPHFace.py: This File is the will recognise faces from the camera feed using LBPH face algorithm.
#TestDataCollector_EiganFace.py: This file is the test application. It will take in an image the dataset will be loaded. A loop will run 200
times each time increamenting the number of components. Each time an Eigen face recogniser will be trained and
#TestDataCollector_EiganFace.py: This file is the test application. It will take in an image the dataset will be loaded. A loop will run 200
times each time increamenting the number of components. Each time an Fisher face recogniser will be trained and
#TestDataCollector_EiganFace.py: This file is the test application. It will take in an image the dataset will be loaded. A loop will run 54, 13, 50 times.
each time increamenting the Parameters. Each time an LBPH face recogniser will be trained and predicted on the input image.
#dataSet --> Contains the images that will be used to train the recogniser.
#FlowCharts --> Contains flow chart designed using Microsoft Visio and png files
#Haar --> Contains Haar Cascades of OpenCV used in the applications
#Plots --> Contains the plots taken using Me4.jpg and Sam.jpg
#Recogniser --> Contains the saved XML files by reconisers
#SaveData --> Contains the data saved by the tester applications
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