Updating the code for Python 3.6 and OpenCV 4.1.2

README.md

@@ -9,61 +9,14 @@ Thanks to OpenCV, coding facial recognition is now easier than ever. There are t
 01:Data Gathering: Gather face data (face images in this case) of the persons you want to identify.<br>
 02:Train the Recognizer: Feed that face data and respective names of each face to the recognizer so that it can learn.<br>
 03:Recognition: Feed new faces of that people and see if the face recognizer you just trained recognizes them.<br>
-
-First Download SQLite Studio For python: https://sqlitestudio.pl/index.rvt?act=download <br>
-After download you may goto download folder and extract the tools and click SQLiteStudio <br>
-Then create database and create column of the table and set all attribute whatver you want. <br>
-
-Follow this step now: <br>
-
-
-import numpy as np<br>
-import cv2<br>
-import sqlite3<br>
-cap = cv2.VideoCapture(0)<br>
-detector= cv2.CascadeClassifier('haarcascade_frontalface_default.xml')<br>
-
-def insertOrUpdate(Id,Name):<br>
-    conn=sqlite3.connect("FaceBase.db")<br>
-    cmd="SELECT * FROM People WHERE ID="+str(Id)<br>
-    cursor=conn.execute(cmd)<br>
-    isRecordExist=0<br>
-    for row in cursor:<br>
-        isRecordExist=1<br>
-    if(isRecordExist==1):<br>
-           cmd="UPDATE people SET Name=' "+str(name)+" ' WHERE ID="+str(Id)<br>
-
-    else:<br>
-         cmd="INSERT INTO people(ID,Name) Values("+str(Id)+",' "+str(name)+" ' )"<br>
-
-    conn.execute(cmd)<br>
-    conn.commit()<br>
-    conn.close()<br>
-
-
-id=raw_input('enter user id')<br>
-name=raw_input('enter your name')<br>
-insertOrUpdate(id,name)<br>
-sampleNum=0;<br>
-
-while(True):<br>
-    ret, img = cap.read()<br>
-    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)<br>
-    faces = detector.detectMultiScale(gray, 1.3, 5)<br>
-    for (x,y,w,h) in faces:<br>
-        sampleNum=sampleNum+1;<br>
-        cv2.imwrite("dataSet/User."+str(id)+"."+str(sampleNum)+".jpg",gray[y:y+h,x:x+w])<br>
-        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)<br>
-        cv2.waitKey(100);<br>
-
-    cv2.imshow('Face',img)<br>
-    cv2.waitKey(1);<br>
-    if(sampleNum>20):<br>
-        break<br>
-
-cap.release()<br>
-cv2.destroyAllWindows()<br>
-
-
-
-
+<h2>Requirements: </h2>
+1. Python 3.7 <br>
+2. Sqlite <br>
+3. OpenCV2 <br>
+4. Haarcascade file(usually comes with openCV) <br>
+
+<h2>Follow this step now: </h2>
+1. To check if all the dependencies are installed and the project will run, run `IntroPy.py` <br>
+2. If `IntroPy.py` runs, then create the data set by running datasetCreator.py<br>
+3. Now to train the recognizer run `trainner.py` <br>
+4. After training the code, its time to test it out so run `detector.py`<br>

dataSetCreator.py

@@ -1,47 +1,50 @@
 import numpy as np
 import cv2
 import sqlite3
+import os
+import shutil
+
 cap = cv2.VideoCapture(0)
 detector= cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
 
-def insertOrUpdate(Id,Name):
+def convertToBinaryData(filename):
+    with open(filename, 'rb') as file:
+        blobData = file.read()
+    return blobData
+
+def insert(Name,img):
     conn=sqlite3.connect("FaceBase.db")
-    cmd="SELECT * FROM People WHERE ID="+str(Id)
-    cursor=conn.execute(cmd)
-    isRecordExist=0
-    for row in cursor:
-        isRecordExist=1
-    if(isRecordExist==1):
-           cmd="UPDATE people SET Name=' "+str(name)+" ' WHERE ID="+str(Id)
-
-    else:
-         cmd="INSERT INTO people(ID,Name) Values("+str(Id)+",' "+str(name)+" ' )"
-
-    conn.execute(cmd)
+    cmd="INSERT INTO people(name,face) Values(?,?)"
+    conn.execute(cmd,(Name,img))
     conn.commit()
     conn.close()
-    
-    
-id=raw_input('enter user id')
-name=raw_input('enter your name')
-insertOrUpdate(id,name)
-sampleNum=0;
+
+def cleanup():
+    shutil.rmtree("dataSet")
+
+name=str(input('enter your name'))
+sampleNum=0
 
 while(True):
     ret, img = cap.read()
     gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
     faces = detector.detectMultiScale(gray, 1.3, 5)
     for (x,y,w,h) in faces:
-        sampleNum=sampleNum+1;
-        cv2.imwrite("dataSet/User."+str(id)+"."+str(sampleNum)+".jpg",gray[y:y+h,x:x+w])
+        sampleNum=sampleNum+1
+        if sampleNum == 1:
+            os.mkdir("dataSet")
+        cv2.imwrite("dataSet/User."+str(sampleNum)+".jpg",gray[y:y+h,x:x+w])
+        face = convertToBinaryData("dataSet/User."+str(sampleNum)+".jpg")
+        insert(name,face)
         cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
-        cv2.waitKey(100);
+        cv2.waitKey(100)
 
     cv2.imshow('Face',img)
-    cv2.waitKey(1);
-    if(sampleNum>20):
+    cv2.waitKey(1)
+    if(sampleNum>300):
         break
-
+
+cleanup()
 cap.release()
 cv2.destroyAllWindows()
 

detector.py

@@ -7,8 +7,8 @@
 
 detector= cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
 
-rec=cv2.createLBPHFaceRecognizer();
-rec.load("recognizer/trainningData.yml")
+rec=cv2.face.LBPHFaceRecognizer_create()
+rec.read("recognizer/trainningData.yml")
 id=0
 def getProfile(id):
     conn=sqlite3.connect("FaceBase.db")
@@ -23,7 +23,7 @@ def getProfile(id):
 
 
 cap = cv2.VideoCapture(0)    
-font = cv2.cv.InitFont(cv2.cv.CV_FONT_HERSHEY_COMPLEX_SMALL, 5, 1, 0, 4) 
+font = cv2.FONT_HERSHEY_SIMPLEX
 while(True):
     ret, img = cap.read()
     gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
@@ -33,15 +33,9 @@ def getProfile(id):
         id,conf=rec.predict(gray[y:y+h,x:x+w])
         profile=getProfile(id)
         if(profile!=None):
-            cv2.cv.PutText(cv2.cv.fromarray(img),str(profile[1]),(x,y+h+30),font,255)#Draw the text
-            cv2.cv.PutText(cv2.cv.fromarray(img),str(profile[2]),(x,y+h+60),font,255)#Draw the text
-            cv2.cv.PutText(cv2.cv.fromarray(img),str(profile[3]),(x,y+h+90),font,255)#Draw the text
-            cv2.cv.PutText(cv2.cv.fromarray(img),str(profile[4]),(x,y+h+120),font,255)#Draw the text
-
-
-
+            cv2.putText(img,str(profile[1]),(x,y+h+30),font,1,255)#Draw the text
 
-    cv2.imshow('frame',img)
+    cv2.imshow('Press q to quit',img)
     if cv2.waitKey(1) & 0xFF == ord('q'):
         break