.gitignore

@@ -1,4 +1 @@
 *.[Jj][Pp][Gg]
-*.pyc
-*.suo
-*.png

.project

@@ -1,17 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<projectDescription>
-	<name>FaceRecognition-python</name>
-	<comment></comment>
-	<projects>
-	</projects>
-	<buildSpec>
-		<buildCommand>
-			<name>org.python.pydev.PyDevBuilder</name>
-			<arguments>
-			</arguments>
-		</buildCommand>
-	</buildSpec>
-	<natures>
-		<nature>org.python.pydev.pythonNature</nature>
-	</natures>
-</projectDescription>

.pydevproject

@@ -1,5 +0,0 @@
-<?xml version="1.0" encoding="UTF-8" standalone="no"?>
-<?eclipse-pydev version="1.0"?><pydev_project>
-<pydev_property name="org.python.pydev.PYTHON_PROJECT_INTERPRETER">Default</pydev_property>
-<pydev_property name="org.python.pydev.PYTHON_PROJECT_VERSION">python interpreter</pydev_property>
-</pydev_project>

FaceRecognition-python.pyproj

@@ -1,26 +0,0 @@
-<?xml version="1.0" encoding="utf-8"?>
-<Project ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003" DefaultTargets="Build">
-  <PropertyGroup>
-    <Configuration Condition=" '$(Configuration)' == '' ">Debug</Configuration>
-    <SchemaVersion>2.0</SchemaVersion>
-    <ProjectGuid>{c5bcf1ad-e7a4-41be-8f0e-28db4b669eec}</ProjectGuid>
-    <ProjectHome />
-    <StartupFile>main.py</StartupFile>
-    <SearchPath />
-    <WorkingDirectory>.</WorkingDirectory>
-    <OutputPath>.</OutputPath>
-    <ProjectTypeGuids>{888888a0-9f3d-457c-b088-3a5042f75d52}</ProjectTypeGuids>
-    <LaunchProvider>Standard Python launcher</LaunchProvider>
-    <InterpreterId />
-  </PropertyGroup>
-  <PropertyGroup Condition="'$(Configuration)' == 'Debug'" />
-  <PropertyGroup Condition="'$(Configuration)' == 'Release'" />
-  <PropertyGroup>
-    <VisualStudioVersion Condition=" '$(VisualStudioVersion)' == '' ">10.0</VisualStudioVersion>
-  </PropertyGroup>
-  <ItemGroup>
-    <Compile Include="main.py" />
-    <Compile Include="Trainer.py" />
-  </ItemGroup>
-  <Import Project="$(MSBuildExtensionsPath32)\Microsoft\VisualStudio\v$(VisualStudioVersion)\Python Tools\Microsoft.PythonTools.targets" />
-</Project>

FaceRecognition-python.sln

@@ -1,23 +0,0 @@
-
-Microsoft Visual Studio Solution File, Format Version 12.00
-# Visual Studio 15
-VisualStudioVersion = 15.0.28307.102
-MinimumVisualStudioVersion = 10.0.40219.1
-Project("{888888A0-9F3D-457C-B088-3A5042F75D52}") = "FaceRecognition-python", "FaceRecognition-python.pyproj", "{C5BCF1AD-E7A4-41BE-8F0E-28DB4B669EEC}"
-EndProject
-Global
-	GlobalSection(SolutionConfigurationPlatforms) = preSolution
-		Debug|Any CPU = Debug|Any CPU
-		Release|Any CPU = Release|Any CPU
-	EndGlobalSection
-	GlobalSection(ProjectConfigurationPlatforms) = postSolution
-		{C5BCF1AD-E7A4-41BE-8F0E-28DB4B669EEC}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
-		{C5BCF1AD-E7A4-41BE-8F0E-28DB4B669EEC}.Release|Any CPU.ActiveCfg = Release|Any CPU
-	EndGlobalSection
-	GlobalSection(SolutionProperties) = preSolution
-		HideSolutionNode = FALSE
-	EndGlobalSection
-	GlobalSection(ExtensibilityGlobals) = postSolution
-		SolutionGuid = {29568353-A5E1-4ECF-9F70-31492869FB0D}
-	EndGlobalSection
-EndGlobal

README.md

@@ -1 +0,0 @@
-### Python code to run in Raspberry Pi with PiCamera to recognize certin faces.

SensorsArd/SensorsArd.ino

@@ -1,98 +0,0 @@
-
-const int trigPin = 9;
-const int echoPin = 10;
-const int ProxSensor = 2;
-const int relayPin = 12;
-const int buzzerPin = 3;
-int inputVal = 0;
-long duration;
-int distance;
-boolean IROK = false;
-boolean UltraOK = false;
-char pi = 'N';
-
-void setup() {
-  pinMode(trigPin, OUTPUT);
-  pinMode(echoPin, INPUT);
-  pinMode(LED_BUILTIN, OUTPUT);
-  pinMode(relayPin, OUTPUT);
-  pinMode(buzzerPin, OUTPUT);
-  pinMode(ProxSensor, INPUT);
-  digitalWrite(buzzerPin, LOW);
-  digitalWrite(relayPin, LOW);
-  Serial.begin(9600);
-
-}
-
-void loop() {
-
-  IROK = false;
-  UltraOK = false;
-  pi = 'N';
-
-  distance = readDistance();
-  if (distance < 70) UltraOK = true;
-  else UltraOK = false;
-  if (digitalRead(ProxSensor) == LOW ) IROK = true;
-  else  IROK = false;
-
-  
-  if (Serial.available() > 0) {
-    pi = Serial.read();
-  }
-
-  delay(500);
-
-  Serial.println(pi);
-  Serial.println(IROK);
-  Serial.println(UltraOK);
-
-  if (IROK && UltraOK && pi == 'o') {
-    openShifter();
-  }
-  IROK = false;
-  UltraOK = false;
-}
-
-void openShifter() {
-  digitalWrite(relayPin, HIGH);
-  playBuzzer(300, true);
-  delay(7000);
-  digitalWrite(relayPin, LOW);
-  IROK = false;
-  UltraOK = false;
-  pi = 'N';
-  serialFlush();
-}
-
-void serialFlush() {
-  while (Serial.available() > 0) {
-    char t = Serial.read();
-  }
-}
-
-void playBuzzer(int time, boolean ok) {
-  tone(buzzerPin, 3000);
-  delay(time / 2);
-  noTone(buzzerPin);
-  delay(100);
-  tone(buzzerPin, 3000);
-  delay(time / 2);
-  noTone(buzzerPin);
-
-}
-
-int readDistance() {
-  // Clears the trigPin
-  digitalWrite(trigPin, LOW);
-  delayMicroseconds(2);
-  // Sets the trigPin on HIGH state for 10 micro seconds
-  digitalWrite(trigPin, HIGH);
-  delayMicroseconds(10);
-  digitalWrite(trigPin, LOW);
-  // Reads the echoPin, returns the sound wave travel time in microseconds
-  duration = pulseIn(echoPin, HIGH);
-  // Calculating the distance
-  return duration * 0.034 / 2;
-
-}

Trainer.py

@@ -0,0 +1,28 @@
+from time import sleep
+from io import BytesIO
+import cv2
+import numpy as np
+
+def train(label, path):
+    try:
+        face_recognizer = cv2.createLBPHFaceRecognizer()
+        face_recognizer.load('/faces/hesham-saeed2')
+    except:
+        print('[ Error ] Problem in init/loading LBPHfacerecognizer')
+    images = []
+    labels = []
+    image_names = os.listdir(path)
+    for image_name in image_names:
+        if image_name.startswith('.'):
+            continue;
+        image_path = train_path + image_name
+		image = cv2.imread(image_path)
+		gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+        face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
+        faces = face_cascade.detectMultiScale(gray, 1.3, 5)
+        for (x,y,w,h) in faces:
+            images.append(gray[y:y+h, x:x+w])
+            labels.append(label)
+        face_recognizer.train(images, np.array(labels))
+    
+        

faces/names.json

@@ -1 +0,0 @@
-["", "Hesham", "Aidarous"]

main.py

@@ -1,29 +1,18 @@
 
 from time import sleep
-from PIL import Image
-import os
-import serial
-import sys
-import json
-import datetime
-
-try:
-    import numpy as np
 from picamera import PiCamera
-    from picamera.array import PiRGBArray
+from io import BytesIO
 import cv2
-    
-except Exception as ex:
-    print('[ Error ] some depandincies are missing\n'+ str(ex.args))
-    sys.exit()
+import numpy as np
+import os
 
 def init():
 	go = True
-	print('Initilizing..')
+	print('Initilizing Camera and cascade components..')
 	try:
 		camera = PiCamera()
 		camera.resolution = (640, 480)
-		sleep(0.2)
+		sleep(2)
 		print('[ OK ] Camera')
 	except:
 		print('[ Error ] Can not initialize PiCamera')
@@ -36,105 +25,79 @@ def init():
 	except:
 		print('[ Error ] Can not load cascade File')
 		go = False
-	try: 
-		os.mkdir('unknown')
-	except OSError as ex:
-		print('Found (unknown) folder')
-		
 	if (go):
 		print('Starting Photo loop..')
-		print('Known people are '+str(loadNames()))
 		start(camera, face_cascade)
-		
 	else: 
 		print('closing')
 	
 def start( camera, face_cascade):
 	j = 0
-	rawCapture = PiRGBArray(camera)
-	face_recognizer = cv2.createLBPHFaceRecognizer()
-	face_recognizer.load('faces/h')
-	names = loadNames()
-	while 1:
-		try:
-			camera.capture(rawCapture, format="bgr")
-		except:
-			print('[ Error ] Can not capture image. Restarting..')
-			init()
-		img = rawCapture.array
+	while True:
+		#try:			
+			camera.capture('img.jpg')			
+			img = cv2.imread('img.jpg',1)
 			gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)			
 			faces = face_cascade.detectMultiScale(gray, 1.3, 5)			
-		i = 0
+			i = 0;
 			for (x,y,w,h) in faces:
-			i += 1
-			j += 1
-			try:
+				i = i + 1
+				j = j + 1 				
+
 				roi_gray = gray[y:y+h, x:x+w]
 				roi_color = img[y:y+h, x:x+w]
-				person = recognize(roi_gray, face_recognizer, names)
-				cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),1)
-				cv2.putText(img, person, (x, y), cv2.FONT_HERSHEY_PLAIN, 1.7, (0,255,0), 2)
-			except:
-				print('[ Error ] Recognition fail')
-			if person == 'unknown':
-				print('Found unknown person')
 				try:
-					RGBImage = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
-					image = Image.fromarray(RGBImage)
-					image.save('unknown/'+str(datetime.datetime.now())+'.png')
+					cv2.imwrite('train/'+str(j)+'.jpg',roi_color)
 				except Exception as ex:
-					print('[ Error ] Saving unkown fail')
 					print(ex)
-			else:
-				print('Found '+person)
-				OpenShifter()
+				print('Drawing on face ', i)
+				
+				cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
+				cv2.putText(img, recognize(roi_gray), (x, y), cv2.FONT_HERSHEY_PLAIN, 1.7, (255, 0, 0), 2)
 			cv2.imshow('image',img) 
-		cv2.waitKey(1)
-		rawCapture.truncate(0)
+			cv2.waitKey(100)
 			if cv2.waitKey(1) & 0xFF == ord('q'):
 				cv2.destroyAllWindows()
 				break
 		
+		#except:
+			#print('[ Error ] Unexpected exception')
+			#print('Closing')
+			#break
 			
-def recognize(image,face_recognizer, names):
+def train(number):
 
-	try:
+	train_path = 'train/'
+	face_recognizer = cv2.createLBPHFaceRecognizer()
+	images = []
+	labels = []
+	image_names = os.listdir(train_path)
+	for image_name in image_names:
+		if image_name.startswith("."):
+			continue;
+		image_path = train_path + image_name
+		image = cv2.imread(image_path)
+		gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+		images.append(gray)
+		labels.append(number)
+	print('training')
+	face_recognizer.train(images, np.array(labels))
+	face_recognizer.save('faces/hesham')
+	
+
+def recognize(image):
+	
+	subjects = ['','Hesham','Unknown']
+	face_recognizer = cv2.createLBPHFaceRecognizer()
+	face_recognizer.load('faces/hesham')
 	img = image.copy()	
 	label= face_recognizer.predict(img)
-	except:
-		print('[ Error ] Error in Recognize() function')
-	if label[1] > 70:
-		print(str(label))
-		return 'unknown'
+	if label[0] == 1:
+		return 'Hesham'
 	else: 
-		print(str(label) + ' >>'+names[label[0]])
-		return names[label[0]]
-
-#def DrawSquares(image,gray,faces,color):
-
-def OpenShifter():
-	try:
-		ser = serial.Serial('/dev/ttyUSB0',9600)
-		ser.open()
-		ser.write('o')
-		ser.close()
-	except Exception as ex:
-		print('[ Error ] Can not connect to Arduino at /dev/ttyUSB0 ..')
-		try:
-			ser = serial.Serial('/dev/ttyUSB1',9600)
-			ser.open()
-			ser.write('o')
-			ser.close()
-		except:
-			print('[ Error ] Can not connect to Arduino at /dev/ttyUSB1 ..')
-			
-def loadNames():
-	try:
-		with open("faces/names.json", "r") as read_file:
-			data = json.load(read_file)
-			return list(data)
-	except:
-		print('[ Error ] Error in loadNames() function')
+		return 'Unknown'
 	
   
 init()
+
+

trainer.py

@@ -1,133 +0,0 @@
-from time import sleep
-from io import BytesIO
-from picamera import PiCamera
-import cv2
-import numpy as np
-import os
-import sys
-import json
-
-picCount = 0
-new = False
-
-
-def start():
-    print('Starting training..')
-    label = int(input('Label (Integer): '))
-    name = str(raw_input('Person name: '))
-    picCount = int(input('Number of Photos: '))
-    global new
-    new = promptNew()
-    if new:
-        newFileName = str(raw_input('New File name: '))
-        oldFileName = newFileName
-    else:
-        print('Found in faces:')
-        print(os.listdir('faces/'))
-        oldFileName = str(raw_input('Old File name: '))
-        newFileName = str(raw_input('New File name: '))
-    clearTrainFolder()
-    dum = input('Press any key to start capture..')
-    capture(picCount)
-    addPerson(label, newFileName, oldFileName)
-    addName(name)
-
-
-def clearTrainFolder():
-    print('clearing train folder')
-    filelist = [f for f in os.listdir('train/') if f.endswith(".jpg")]
-    for f in filelist:
-        os.remove(os.path.join('train/', f))
-
-
-def addPerson(label, newFileName, oldFileName):
-    try:
-        # faceFilePath = '/faces/hesham-saeed2'
-        faceFile = 'faces/' + oldFileName
-        face_recognizer = cv2.createLBPHFaceRecognizer()
-        global new
-        if new:
-            print('new file. skipping load function')
-        else:
-            print('loading old file')
-            face_recognizer.load(faceFile)
-    except:
-        print('[ Error ] Problem in init/loading LBPHfacerecognizer')
-        sys.exit()
-    images = []
-    labels = []
-    image_names = os.listdir('train/')
-    for image_name in image_names:
-        if image_name.startswith('.'):
-            continue;
-        image_path = 'train/' + image_name
-        image = cv2.imread(image_path)
-        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-        face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
-        faces = face_cascade.detectMultiScale(gray, 1.3, 5)
-        for (x, y, w, h) in faces:
-            images.append(gray[y:y + h, x:x + w])
-            labels.append(label)
-            cv2.imshow('face', gray[y:y + h, x:x + w])
-            cv2.waitKey(100)
-            print('Learning ' + image_name)
-    if new:
-        face_recognizer.train(images, np.array(labels))
-    else:
-        face_recognizer.update(images, np.array(labels))
-    face_recognizer.save('faces/' + newFileName)
-    print('Updated and saved file in faces/' + newFileName)
-
-
-def capture(count):
-    try:
-        print('Initializing camera')
-        camera = PiCamera()
-        camera.resolution = (640, 480)
-        print('[ OK ] Camera')
-        sleep(2)
-    except:
-        print('[ Error ] Can not initialize PiCamera')
-        sys.exit()
-    for i in range(1, count + 1):
-        pic = 'train/' + str(i) + '.jpg'
-        camera.capture(pic)
-        photo = cv2.imread(pic, 1)
-        cv2.imshow('Photo', photo)
-        print('Captured ' + str(i) + '\nPath ' + pic)
-        cv2.waitKey(100)
-        sleep(1)
-    cv2.destroyAllWindows()
-    print('Done!')
-
-
-def promptNew():
-    filemode = raw_input('Make new File? (y/n): ')
-    if filemode == 'y':
-        return True
-    elif filemode == 'n':
-        return False
-    else:
-        print('incorrect input')
-        promptNew()
-
-
-def addName(newName):
-    with open("faces/names.json", "r") as read_file:
-        exist = False
-        namesJson = json.load(read_file)
-        names = list(namesJson)
-        i = 0
-        for name in names:
-            if newName == name:
-                exist = True
-                print('name already in names list with index ' + str(i))
-            i += 1
-        if not exist:
-            names.append(newName)
-            print('Added ' + newName + 'to names.json file')
-    with open("faces/names.json", "w") as write_file:
-        json.dump(names, write_file)
-
-
-start()