Readme.txt

{\rtf1\ansi\ansicpg1252\cocoartf2576
\cocoatextscaling0\cocoaplatform0{\fonttbl\f0\fswiss\fcharset0 Helvetica;}
{\colortbl;\red255\green255\blue255;}
{\*\expandedcolortbl;;}
\paperw11900\paperh16840\margl1440\margr1440\vieww11520\viewh8400\viewkind0
\pard\tx566\tx1133\tx1700\tx2267\tx2834\tx3401\tx3968\tx4535\tx5102\tx5669\tx6236\tx6803\pardirnatural\partightenfactor0

\f0\fs24 \cf0 This repository represents the final year project Software Development Project.\
\
It has 2 directory:\
1. face_recog_model :- folder for machine learning model\
2. FaceRecogAttendance :- folder for client application code\
\
****face_recog_model*****\
1. Demo2 :- the machine learning model code\
2. Face_extraction :- the script to extract faces from images\
3. convert_to_coreml :- a script to convert the tensorflow model to cormel format\
\
*****FaceRecogAttendance*****\
1. To test the application, simply run FaceRecogAttendance.xcworkspace in Xcode. You might need to change the bundle identifier and signing capabilities in Xcode.\
\
2. The directory have 3 main folders:\
	1. Model - the data model in the application is all stored here\
	2. View - the user interfaces of the application - the storyboard \
	3. Controllers - all the controllers in the application are stored here\
\
	4. Some important file:\
	GoogleService-info.plist :- a configuration file to access Firebase Storage\
	Info.plist :- the client application configuration file\
	FaceClassifierV3.mlmodel :- the coreml machine model converted from the tensorflow model.\
	Pods :- cocoa pods file that is used in this application
}