Hesham/FaceRecognition-python
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base: Hesham:master
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Hesham:master
Hesham:webcam-support
Hesham:fix-imports
Hesham:ard-refactor
Hesham:0.5
Hesham:0.4
Hesham:0.3
Hesham:0.2
Hesham:0.1
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compare: Hesham:0.3
Branches Tags
Hesham:master
Hesham:webcam-support
Hesham:fix-imports
Hesham:ard-refactor
Hesham:0.5
Hesham:0.4
Hesham:0.3
Hesham:0.2
Hesham:0.1

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10 changed files with 209 additions and 270572 deletions
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3
.gitignore vendored
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@ -1,4 +1,3 @@
*.[Jj][Pp][Gg]
*.pyc
*.suo
*.png
*.suo

17
.project
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@ -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>

5
.pydevproject
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@ -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>

2
README.md
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@ -1 +1 @@
### Python code to run in Raspberry Pi with PiCamera to recognize certin faces.
### Python code to run in Raspberry Pi with PiCamera to recognize certin faces and send a Serial signal 'o' to be received by arduino.

123
SensorsArd/SensorsArd.ino
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@ -7,84 +7,28 @@ const int buzzerPin = 3;
int inputVal = 0;
long duration;
int distance;
boolean IROK = false;
boolean UltraOK = false;
char pi = 'N';
char piInput = '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';
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() {
boolean IROK = false;
boolean UltraOK = false;
// Clears the trigPin
digitalWrite(trigPin, LOW);
digitalWrite(trigPin, LOW);
delayMicroseconds(2);
// Sets the trigPin on HIGH state for 10 micro seconds
digitalWrite(trigPin, HIGH);
@ -93,6 +37,57 @@ int readDistance() {
// Reads the echoPin, returns the sound wave travel time in microseconds
duration = pulseIn(echoPin, HIGH);
// Calculating the distance
return duration * 0.034 / 2;
distance= 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(7000);
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);
}

73686
faces/h
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File diff suppressed because it is too large Load Diff

196621
faces/m
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File diff suppressed because it is too large Load Diff

2
faces/names.json
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@ -1 +1 @@
["", "Hesham", "Aidarous"]
["", "Hesham", "Saeed"]

110
main.py
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@ -1,11 +1,10 @@
from time import sleep
from PIL import Image
from io import BytesIO
import os
import serial
import sys
import json
import datetime
try:
import numpy as np
@ -19,7 +18,7 @@ except Exception as ex:
def init():
go = True
print('Initilizing..')
print('Initilizing Camera and cascade components..')
try:
camera = PiCamera()
camera.resolution = (640, 480)
@ -36,82 +35,66 @@ 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')
#else:
#print('Sensors not Satisfied')
def start( camera, face_cascade):
j = 0
rawCapture = PiRGBArray(camera)
face_recognizer = cv2.createLBPHFaceRecognizer()
face_recognizer.load('faces/h')
names = loadNames()
#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(rawCapture, format="bgr")
except:
print('[ Error ] Can not capture image. Restarting..')
init()
#try:
#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, 1.3,5)
i = 0
faces = face_cascade.detectMultiScale(gray, 1.2,5)
i = 0;
for (x,y,w,h) in faces:
i += 1
j += 1
try:
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')
except Exception as ex :
print('[ Error ] Saving unkown fail')
print(ex)
else:
print('Found '+person)
roi_gray = gray[y:y+h, x:x+w]
roi_color = img[y:y+h, x:x+w]
person = recognize(roi_gray)
if person == 'Hesham' or person == 'Saeed':#Change to if 'unknown' elif openShifter
OpenShifter()
print('Sending to Arduino!')
cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
cv2.putText(img, person, (x, y), cv2.FONT_HERSHEY_PLAIN, 1.7, (255, 0, 0), 2)
cv2.imshow('image',img)
cv2.waitKey(1)
cv2.waitKey(100)
rawCapture.truncate(0)
if cv2.waitKey(1) & 0xFF == ord('q'):
cv2.destroyAllWindows()
break
#except:
#print('[ Error ] Unexpected exception')
#print('Closing')
#break
def recognize(image,face_recognizer, names):
try:
img = image.copy()
label= face_recognizer.predict(img)
except:
print('[ Error ] Error in Recognize() function')
if label[1] > 70:
print(str(label))
def recognize(image):
names = loadNames()
face_recognizer = cv2.createLBPHFaceRecognizer()
face_recognizer.load('faces/m')
img = image.copy()
label= face_recognizer.predict(img)
if label[1] > 120:
return 'unknown'
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)
@ -119,22 +102,13 @@ def OpenShifter():
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 ..')
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')
with open("faces/names.json", "r") as read_file:
data = json.load(read_file)
return list(data)
init()

212
trainer.py
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@ -7,127 +7,121 @@ 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()