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Collector.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Thu May  2 19:19:15 2019
+
+@author: Omkar Shidore
+https://www.github.com/OmkarShidore
+"""
+import cv2
+import os
+def createFolder(directory):
+    try:
+        if not os.path.exists(directory):
+            os.makedirs(directory)
+    except OSError:
+        print ('Error: Creating directory. ' +  directory)
+#created folder for saving dataset images of user
+createFolder('./dataSet/')
+
+cam = cv2.VideoCapture(0)
+detector=cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
+Id=input('Enter your id: ')
+UserName=input('Enter Name: ')
+sampleNum=0
+while True:
+    ret, img = cam.read()
+    ret, img1 = cam.read()
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    faces = detector.detectMultiScale(gray, 1.3, 5)
+    for (x,y,w,h) in faces:
+        cv2.rectangle(img,(x,y),(x+w,y+h),(0,0,255),2)
+
+        #incrementing sample number 
+        sampleNum=sampleNum+1
+        sampleNum1=str(sampleNum)
+        text=sampleNum
+        #saving the captured face in the dataset folder
+        cv2.imwrite("dataSet/User."+Id +'.'+ UserName+'.'+str(sampleNum)+'.'+ ".jpg", gray[y:y+h,x:x+w])
+
+        cv2.putText(img1,sampleNum1, (70, 150), cv2.FONT_HERSHEY_SIMPLEX, 3,(255,255,255), 3)
+        cv2.imshow('Scans',img1)
+
+    if cv2.waitKey(1)==27:
+        break
+    # break if the sample number is morethan 20
+    elif sampleNum>100:
+        break
+cam.release()
+cv2.destroyAllWindows()

modelTrainer.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Thu May  2 20:19:45 2019
+
+@author: Omkar Shidore
+https://www.github.com/OmkarShidore
+"""
+
+import os
+import cv2
+import numpy as np
+from PIL import Image
+print('Module Versions: ')
+print('OpenCv: '+cv2.__version__, '\nNumpy: '+np.__version__,'\nPillow>>Image: '+Image.__version__)
+
+#Creatung directories
+def createFolder(directory):
+    try:
+        if not os.path.exists(directory):
+            os.makedirs(directory)
+    except OSError:
+        print ('Error: Creating directory. ' +  directory)
+createFolder('./trainner/')
+
+recognizer = cv2.face.LBPHFaceRecognizer_create()
+detector= cv2.CascadeClassifier("haarcascade_frontalface_default.xml");
+
+def getImagesAndLabels(path):
+    imagePaths=[os.path.join(path,f) for f in os.listdir(path)] 
+    #empty lists for storing Lables and features
+    faceSamples=[]
+    Ids=[]
+    for imagePath in imagePaths:
+
+        pilImage=Image.open(imagePath).convert('L')
+        imageNp=np.array(pilImage,'uint8')
+        Id=int(os.path.split(imagePath)[-1].split(".")[1])
+        faces=detector.detectMultiScale(imageNp)
+        for (x,y,w,h) in faces:
+            faceSamples.append(imageNp[y:y+h,x:x+w])
+            Ids.append(Id)
+    return faceSamples,Ids
+faces,Ids = getImagesAndLabels('dataSet')
+#training model on dataSet
+recognizer.train(faces, np.array(Ids))
+#trainer.yml stored in the folder trainner
+recognizer.save('trainner/trainner.yml')
+
+recognizer = cv2.face.LBPHFaceRecognizer_create()
+recognizer.read('trainner/trainner.yml')
+cascadePath = "haarcascade_frontalface_default.xml"
+faceCascade = cv2.CascadeClassifier(cascadePath);
+
+
+'''
+def keyValuePairs(path):
+    imagePaths=[os.path.join(path,f) for f in os.listdir(path)] 
+    Ids=[]
+    UserNames=[]
+    for imagePath in imagePaths:
+        Id=int(os.path.split(imagePath)[-1].split(".")[1])
+        UserName=str(os.path.split(imagePath)[-1].split(".")[2])  
+        Ids.append(Id)
+        UserNames.append(UserName)
+    keyValues = dict(zip(Ids, UserNames))
+    return Ids,UserNames,keyValues
+Ids,UserNames,keyValues=keyValuePairs('dataSet')
+cam = cv2.VideoCapture(0)
+font = cv2.FONT_HERSHEY_SIMPLEX
+while True:
+    ret, im =cam.read()
+    gray=cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
+    faces=faceCascade.detectMultiScale(gray, 1.3,5)
+    for(x,y,w,h) in faces:
+        cv2.rectangle(im,(x,y),(x+w,y+h),(0,255,0),2)
+        Id, conf = recognizer.predict(gray[y:y+h,x:x+w])
+        if(conf>50):
+            if Id in keyValues.keys():
+                Id1='User Id: '+str(Id)
+                Name='Name: '+keyValues[Id]
+            else:
+                Id="Null"
+                Name="Unknown"
+        else:
+            Id="Unknown"
+        cv2.putText(im,Id1,(x+w,y),font,0.7,(0,255,0), 2)
+        cv2.putText(im,Name,(x+w,y+123),font,0.7,(0,255,0), 2)
+    cv2.imshow('im',im) 
+    if cv2.waitKey(1)==27:
+        break
+cam.release()
+cv2.destroyAllWindows()
+'''

recognition.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Fri May  3 00:37:50 2019
+
+@author: Omkar Shidore
+https://www.github.com/OmkarShidore
+"""
+import os
+import cv2
+
+recognizer = cv2.face.LBPHFaceRecognizer_create()
+recognizer.read('trainner/trainner.yml')
+cascadePath = "haarcascade_frontalface_default.xml"
+faceCascade = cv2.CascadeClassifier(cascadePath);
+cam = cv2.VideoCapture(0)
+font = cv2.FONT_HERSHEY_SIMPLEX
+
+def keyValuePairs(path):
+    imagePaths=[os.path.join(path,f) for f in os.listdir(path)] 
+    Ids=[]
+    UserNames=[]
+    for imagePath in imagePaths:   
+        Id=int(os.path.split(imagePath)[-1].split(".")[1])
+        UserName=str(os.path.split(imagePath)[-1].split(".")[2])    
+        Ids.append(Id)
+        UserNames.append(UserName)
+    keyValues = dict(zip(Ids, UserNames))
+    return Ids,UserNames,keyValues
+Ids,UserNames,keyValues=keyValuePairs('dataSet')
+
+cam = cv2.VideoCapture(0)
+font = cv2.FONT_HERSHEY_SIMPLEX
+while True:
+    ret, im =cam.read()
+    gray=cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
+    faces=faceCascade.detectMultiScale(gray, 1.3,5)
+    for(x,y,w,h) in faces:
+        cv2.rectangle(im,(x,y),(x+w,y+h),(0,255,0),2)
+        Id, conf = recognizer.predict(gray[y:y+h,x:x+w])
+        if(conf>50):
+            if Id in keyValues.keys():
+                Id1= 'User Id  : '+str(Id)
+                Name='User Name: '+keyValues[Id]
+            else:
+                Id="Null"
+                Name="Unknown"
+        else:
+            Id="Unknown"
+        cv2.putText(im,Id1,(x,y+h+20),font,0.7,(0,255,0), 2)
+        cv2.putText(im,Name,(x,y+h+38),font,0.7,(0,255,0), 2)
+    cv2.imshow('im',im) 
+    if cv2.waitKey(1)==27:
+        break
+cam.release()
+cv2.destroyAllWindows()
+
+#(124,185,234)
+'''
+import cv2
+recognizer = cv2.face.LBPHFaceRecognizer_create()
+recognizer.read('trainner/trainner.yml')
+cascadePath = "haarcascade_frontalface_default.xml"
+faceCascade = cv2.CascadeClassifier(cascadePath);
+cam = cv2.VideoCapture(0)
+font = cv2.FONT_HERSHEY_SIMPLEX
+while True:
+    ret, im =cam.read()
+    gray=cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
+    faces=faceCascade.detectMultiScale(gray, 1.3,5)
+    for(x,y,w,h) in faces:
+        cv2.rectangle(im,(x,y),(x+w,y+h),(0,0,255),2)
+        Id, conf = recognizer.predict(gray[y:y+h,x:x+w])
+        if(conf>50):
+            if(Id==1):
+                Id="Anirban"
+            elif(Id==2):
+                Id="Sam"
+        else:
+            Id="Unknown"
+        cv2.putText(im,Id,(x,y+h),font,2,(0,255,0), 2)
+    cv2.imshow('im',im) 
+    if cv2.waitKey(1)==27:
+        break
+cam.release()
+cv2.destroyAllWindows()
+'''