Merge branch 'perf' of Hesham/FaceRecognition-python into master

SensorsArd/SensorsArd.ino

@@ -3,24 +3,28 @@ 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;
 char piInput = 'N';
 
 void setup() {
-  pinMode(trigPin, OUTPUT); // Sets the trigPin as an Output
-  pinMode(echoPin, INPUT); // Sets the echoPin as an Input
+  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); // Starts the serial communication
-  pinMode(ProxSensor,INPUT);    //Pin 2 is connected to the output of proximity sensor
+  Serial.begin(9600); 
 
 }
 
 void loop() {
 
+
   boolean IROK = false;
   boolean UltraOK = false;
   // Clears the trigPin
@@ -45,6 +49,7 @@ void loop() {
   if (IROK && UltraOK && Serial.available() > 0 ){
     if (Serial.read() == 'O') {
       digitalWrite(relayPin, HIGH);
+      playBuzzer(2,false);
       delay(5000);
       digitalWrite(relayPin, LOW);
       IROK = false;
@@ -66,6 +71,25 @@ void serialFlush(){
   }
 }
 
+void playBuzzer(int time, boolean ok){
+  if (ok) {
+    tone(buzzerPin, 1000);
+    delay(time/3);
+    noTone(buzzerPin);
+    delay(time/5);
+    tone(buzzerPin,1000);
+    delay(time/3);
+    noTone(buzzerPin);
+  } 
+  else {
+    tone(buzzerPin, 1000);
+    delay(time);
+    noTone(buzzerPin);
+    
+  }
+}
+
+
 
 
 

main.py

@@ -4,10 +4,12 @@ from io import BytesIO
 import os
 import serial
 import sys
+import json
 
 try:
     import numpy as np
     from picamera import PiCamera
+    from picamera.array import PiRGBArray
     import cv2
     
 except Exception as ex:
@@ -20,7 +22,7 @@ def init():
 	try:
 		camera = PiCamera()
 		camera.resolution = (640, 480)
-		sleep(2)
+		sleep(0.2)
 		print('[ OK ] Camera')
 	except:
 		print('[ Error ] Can not initialize PiCamera')
@@ -44,12 +46,18 @@ def init():
 	
 def start( camera, face_cascade):
 	j = 0
-	while True:
+	rawCapture = PiRGBArray(camera)
+	#camera.framerate = 32
+	#rawCapture = PiRGBArray(camera, size=(640, 480))
+	#for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):	
+	while 1:
 	#try:
-		camera.capture('img.jpg')			
-		img = cv2.imread('img.jpg',1)
+		#camera.capture('img.jpg')
+		#img = cv2.imread('img.jpg',1)
+		camera.capture(rawCapture, format="bgr")
+		img = rawCapture.array
 		gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-		faces = face_cascade.detectMultiScale(gray, 1.1, 4)			
+		faces = face_cascade.detectMultiScale(gray, 1.2,5)
 		i = 0;
 		for (x,y,w,h) in faces:
 			i += 1
@@ -65,6 +73,7 @@ def start( camera, face_cascade):
 			
 		cv2.imshow('image',img) 
 		cv2.waitKey(100)
+		rawCapture.truncate(0)
 		if cv2.waitKey(1) & 0xFF == ord('q'):
 			cv2.destroyAllWindows()
 			break
@@ -74,51 +83,32 @@ def start( camera, face_cascade):
 			#print('Closing')
 			#break
 
-def train(number):
-
-	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','Saeed']
+	names = loadNames()
 	face_recognizer = cv2.createLBPHFaceRecognizer()
 	face_recognizer.load('faces/m')
 	img = image.copy()
 	label= face_recognizer.predict(img)
 	print(label)
-	if label[0] == 1 and int(label[1]) < 120:
-		return 'Hesham'
-	elif label[0] == 2 and int(label[1]) < 120:
-		return 'Safwan'
-	elif label[0] == 4 and int(label[1]) < 120:
-		return 'Hesham2'
+	if label[1] > 120:
+		return 'unknown'
 	else:
-		return 'Unknown'
+		return names[label[0]]
 		
 def OpenShifter():
 	try:
-		ser = serial.Serial('/dev/ttyUSB1',9600)
+		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/ttyUSB1 ..')
 
+def loadNames():
+	
+	with open("faces/names.json", "r") as read_file:
+		data = json.load(read_file)
+		return list(data)
+
 
 init()

trainer.py

@@ -5,6 +5,7 @@ import cv2
 import numpy as np
 import os
 import sys
+import json
 
 
 picCount = 0
@@ -13,6 +14,7 @@ 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()
@@ -25,10 +27,10 @@ def start():
 		oldFileName = str(raw_input('Old File name: '))
 		newFileName = str(raw_input('New File name: '))
 	clearTrainFolder()
-	print('Press any key to start capture..')
-	dum = input('')
+	dum = input('Press any key to start capture..')
 	capture(picCount)
 	addPerson(label, newFileName, oldFileName)
+	addName(name)
 
 def clearTrainFolder():
 	print('clearing train folder')
@@ -64,6 +66,8 @@ def addPerson(label, newFileName, oldFileName):
 		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))
@@ -103,4 +107,21 @@ def promptNew():
 		print('incorrect input')
 		promptNew()
 
-start()
+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)
+