Formatting

.project

@@ -0,0 +1,17 @@
+<?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

@@ -0,0 +1,5 @@
+<?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>

README.md

@@ -1 +1 @@
-### Python code to run in Raspberry Pi with PiCamera to recognize certin faces and send a Serial signal 'o' to be received by arduino. 
+### Python code to run in Raspberry Pi with PiCamera to recognize certin faces.

SensorsArd/SensorsArd.ino

@@ -7,28 +7,84 @@ const int buzzerPin = 3;
 int inputVal = 0;
 long duration;
 int distance;
-char piInput = 'N';
+boolean IROK = false;
+boolean UltraOK = false;
+char pi = 'N';
 
 void setup() {
   pinMode(trigPin, OUTPUT);
-  pinMode(echoPin, INPUT); 
+  pinMode(echoPin, INPUT);
   pinMode(LED_BUILTIN, OUTPUT);
   pinMode(relayPin, OUTPUT);
   pinMode(buzzerPin, OUTPUT);
-  pinMode(ProxSensor,INPUT);
+  pinMode(ProxSensor, INPUT);
   digitalWrite(buzzerPin, LOW);
   digitalWrite(relayPin, LOW);
-  Serial.begin(9600); 
+  Serial.begin(9600);
 
 }
 
 void loop() {
 
+  IROK = false;
+  UltraOK = false;
+  pi = 'N';
 
-  boolean IROK = false;
-  boolean UltraOK = false;
+  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);  
+  digitalWrite(trigPin, LOW);
   delayMicroseconds(2);
   // Sets the trigPin on HIGH state for 10 micro seconds
   digitalWrite(trigPin, HIGH);
@@ -37,56 +93,6 @@ void loop() {
   // Reads the echoPin, returns the sound wave travel time in microseconds
   duration = pulseIn(echoPin, HIGH);
   // Calculating the distance
-  distance= duration*0.034/2;
+  return duration * 0.034 / 2;
 
-  if (distance < 70) UltraOK = true;  
-  else UltraOK = false;
-  if(digitalRead(ProxSensor) == LOW ) IROK = true;
-  else  IROK = false;
-  char pi = 'N';
-  if (Serial.available() > 0) { pi = Serial.read(); }
-  delay(500);
-  Serial.println(pi);
-  Serial.println(IROK);
-  Serial.println(UltraOK);
-  //if (IROK && UltraOK) Serial.println("A");
-  if (IROK && UltraOK && pi == 'o'){
-    //if (Serial.read() == 'o') {
-      digitalWrite(relayPin, HIGH);
-      playBuzzer(300,true);
-      delay(4000);
-      digitalWrite(relayPin, LOW);
-      IROK = false;
-      UltraOK = false;
-      pi = 'N';
-      serialFlush();
-    //}
-  }
-  IROK = false;
-  UltraOK = false;
 }
-
-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);
-  
-}
-
-
-
-
-
-
-
-

main.py

@@ -64,7 +64,7 @@ def start( camera, face_cascade):
 		img = rawCapture.array
 		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
@@ -109,7 +109,9 @@ def recognize(image,face_recognizer, names):
 	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)

trainer.py

@@ -7,122 +7,127 @@ 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)
+    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))
+    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) 
+    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!')
+    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()
+    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)
+    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()