Integrated hardware commands to Facial Recognition Software.
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parent
c5bf048621
commit
cf228272a8
7 changed files with 170 additions and 177 deletions
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@ -7,11 +7,13 @@ import numpy as np
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import Facial_Recognition_Render as fr
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import _pickle as cPickle
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import glob
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'import Hardware.Motor' #Line 225-228
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faceWidth = 320
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faceHeight = 320
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SKIP_FRAMES = 1
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def alignFace(imFace, landmarks):
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l_x = landmarks[39][0]
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l_y = landmarks[39][1]
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@ -28,8 +30,8 @@ def alignFace(imFace, landmarks):
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alignedImFace = cv2.warpAffine(imFace, rotMatrix, (imFace.shape[1], imFace.shape[0]))
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return alignedImFace
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def face_detector_haarcascade(image):
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def face_detector_haarcascade(image):
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grey = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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resize_fx = 1
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@ -52,10 +54,11 @@ def face_detector_haarcascade(image):
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return image
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def face_detector_ssd(image):
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def face_detector_ssd(image):
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pwd = sys.path[0]
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net = cv2.dnn.readNetFromCaffe(pwd+"/Facial_models/deploy.prototxt", pwd+"/Facial_models/res10_300x300_ssd_iter_140000_fp16.caffemodel")
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net = cv2.dnn.readNetFromCaffe(pwd + "/Facial_models/deploy.prototxt",
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pwd + "/Facial_models/res10_300x300_ssd_iter_140000_fp16.caffemodel")
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resize = (300, 300)
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confidence_thres = 0.65
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@ -81,6 +84,7 @@ def face_detector_ssd(image):
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return image
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def training_data_loader():
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imagesFolder = sys.path[0] + "/Facial_images/face_rec/train/"
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subfolders = []
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@ -137,8 +141,8 @@ def training_data_loader():
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return imagesFaceTrain, labelsFaceTrain, labelsMap
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def training_recognizer(rec_type):
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def training_recognizer(rec_type):
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imagesFaceTrain, labelsFaceTrain, labelsMap = training_data_loader()
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if (rec_type == 'LBPH'):
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@ -157,6 +161,7 @@ def training_recognizer(rec_type):
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with open(sys.path[0] + '/Facial_models/labels_map.pkl', 'wb') as f:
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cPickle.dump(labelsMap, f)
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def face_recognition_inference(rec_type):
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# testFiles = glob.glob(sys.path[0]+'/Facial_test_images/face_rec/test/*.jpg')
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# testFiles.sort()
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@ -217,12 +222,15 @@ def face_recognition_inference(rec_type):
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text = '{} {}%'.format(labelsMap[predictedLabel], round(score, 5))
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cv2.rectangle(original, (x1, y1), (x2, y2), (0, 255, 0), 5)
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cv2.putText(original, text, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 0), 3)
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'Hardware.Motor.Motor.stop_motor()'
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'Hardware.Motor.Motor.start_motor()'
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'Hardware.Motor.Motor.stop_motor()'
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'Hardware.Motor.Motor.start_alarm()'
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cv2.imshow('Face Recognition Demo', original)
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k = cv2.waitKey(10)
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cam.release()
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cv2.destroyAllWindows()
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@ -236,10 +244,6 @@ if __name__=="__main__":
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elif (mode == 'test'):
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face_recognition_inference(rec_type)
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# video process (keep it in case if needed)
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'''
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cameraCapture = cv2.VideoCapture(1)
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@ -274,6 +278,3 @@ if __name__=="__main__":
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cv2.waitKey()
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cv2.destroyAllWindows()
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'''
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@ -1,105 +0,0 @@
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import RPi.GPIO as GPIO
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from time import sleep
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class Motor:
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print("Starting of the program")
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def __init__(self):
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GPIO.setmode(GPIO.BCM)
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GPIO.setwarnings(False)
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#preset GPIO ports for 2 motors
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self.Motor1 = {'EN': 25, 'input1': 24, 'input2': 23}
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self.Motor2 = {'EN': 17, 'input1': 27, 'input2': 22}
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# preset the port for buttons and alarm
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GPIO.setup(5,GPIO.IN) # start motor button, initially True
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GPIO.setup(13,GPIO.IN) # stop motor button, initially True
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GPIO.setup(16,GPIO.IN) # start alarm button, initially True
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GPIO.setup(26,GPIO.OUT) # alarm output
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for x in self.Motor1:
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GPIO.setup(self.Motor1[x], GPIO.OUT)
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GPIO.setup(self.Motor2[x], GPIO.OUT)
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#utilize PWM function, enable motors and frequency is 100Hz
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self.EN1 = GPIO.PWM(self.Motor1['EN'], 100)
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self.EN2 = GPIO.PWM(self.Motor2['EN'], 100)
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self.EN1.start(0)
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self.EN2.start(0)
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#stop signals for motors and alarm
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self.motorStop=False
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self.alarmStop=False
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def start_motor(self):
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while (not self.motorStop) or (not GPIO.input(5)): #break the loop when motor stop signal is detected
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print ("FORWARD MOTION")
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self.motorStop=self.stop_motor()
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self.EN1.ChangeDutyCycle(50)
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self.EN2.ChangeDutyCycle(50)
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GPIO.output(self.Motor1['input1'], GPIO.HIGH)
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GPIO.output(self.Motor1['input2'], GPIO.LOW)
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GPIO.output(self.Motor2['input1'], GPIO.HIGH)
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GPIO.output(self.Motor2['input2'], GPIO.LOW)
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GPIO.cleanup()
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def stop_motor(self):
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userStop=input("Stop the motor? choose between Y/N")
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if (userStop=="Y") or (not GPIO.input(13)):
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print("stopping motor...")
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self.EN1.ChangeDutyCycle(0)
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self.EN2.ChangeDutyCycle(0)
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print("motor stops")
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return True
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elif userStop=="N":
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return False
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else:
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self.stop_motor(self)
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def start_alarm(self):
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while (not self.alarmStop) or (not GPIO.input(16)):
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self.alarmStop=self.stop_alarm()
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GPIO.output(26,True)
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GPIO.cleanup()
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def stop_alarm(self):
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stopRequest=input("Turn off the alarm? choose between Y/N")
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if stopRequest=="Y":
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print("Alarm turning off...")
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GPIO.output(26,False)
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print("Alarm is off")
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return True
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elif stopRequest=="N":
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return False
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else:
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self.stop_alarm()
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if __name__=="__main__":
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#print("Execute function...")
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motor1=Motor()
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#motor1.start_motor()
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motor1.start_alarm()
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98
Hardware/Motor.py
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98
Hardware/Motor.py
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@ -0,0 +1,98 @@
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import RPi.GPIO as GPIO
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from time import sleep
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class Motor:
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def __init__(self):
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print("Starting of the program")
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GPIO.setmode(GPIO.BCM)
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GPIO.setwarnings(False)
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# preset GPIO ports for 2 motors
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self.Motor1 = {'EN': 25, 'input1': 24, 'input2': 23}
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self.Motor2 = {'EN': 17, 'input1': 27, 'input2': 22}
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# preset the port for buttons and alarm
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GPIO.setup(5, GPIO.IN) # start motor button, initially True
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GPIO.setup(13, GPIO.IN) # stop motor button, initially True
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GPIO.setup(16, GPIO.IN) # start alarm button, initially True
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GPIO.setup(26, GPIO.OUT) # alarm output
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for x in self.Motor1:
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GPIO.setup(self.Motor1[x], GPIO.OUT)
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GPIO.setup(self.Motor2[x], GPIO.OUT)
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# utilize PWM function, enable motors and frequency is 100Hz
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self.EN1 = GPIO.PWM(self.Motor1['EN'], 100)
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self.EN2 = GPIO.PWM(self.Motor2['EN'], 100)
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self.EN1.start(0)
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self.EN2.start(0)
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# stop signals for motors and alarm
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self.motorStop = False
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self.alarmStop = False
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def start_motor(self):
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while (not self.motorStop) or (not GPIO.input(5)): # break the loop when motor stop signal is detected
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print("FORWARD MOTION")
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self.motorStop = self.stop_motor()
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self.EN1.ChangeDutyCycle(50)
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self.EN2.ChangeDutyCycle(50)
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GPIO.output(self.Motor1['input1'], GPIO.HIGH)
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GPIO.output(self.Motor1['input2'], GPIO.LOW)
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GPIO.output(self.Motor2['input1'], GPIO.HIGH)
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GPIO.output(self.Motor2['input2'], GPIO.LOW)
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GPIO.cleanup()
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def stop_motor(self):
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userStop = input("Stop the motor? choose between Y/N")
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if (userStop == "Y") or (not GPIO.input(13)):
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print("stopping motor...")
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self.EN1.ChangeDutyCycle(0)
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self.EN2.ChangeDutyCycle(0)
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print("motor stops")
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return True
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elif userStop == "N":
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return False
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else:
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self.stop_motor(self)
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def start_alarm(self):
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while (not self.alarmStop) or (not GPIO.input(16)):
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self.alarmStop = self.stop_alarm()
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GPIO.output(26, True)
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GPIO.cleanup()
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def stop_alarm(self):
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stopRequest = input("Turn off the alarm? choose between Y/N")
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if stopRequest == "Y":
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print("Alarm turning off...")
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GPIO.output(26, False)
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print("Alarm is off")
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return True
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elif stopRequest == "N":
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return False
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else:
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self.stop_alarm()
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if __name__ == "__main__":
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# print("Execute function...")
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motor1 = Motor()
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# motor1.start_motor()
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motor1.start_alarm()
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BIN
Hardware/__pycache__/Motor.cpython-36.pyc
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BIN
Hardware/__pycache__/Motor.cpython-36.pyc
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Binary file not shown.
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@ -8,24 +8,23 @@ def start():
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count = 0
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users = DBHelper.db.child("Users").get()
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try:
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for user in users.each():
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for x in users.each():
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count = +1
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for x in range(20):
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for y in range(20):
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if not os.path.isdir("Facial_images/face_rec/train/User_" + str(count)):
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os.makedirs("Photos_of_Users/User_" + str(count))
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DBHelper.download_user_photo("User_" + str(count) + "/" + str(x) + ".jpg")
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DBHelper.download_user_photo("User_" + str(count) + "/" + str(y) + ".jpg")
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except:
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print("No Users are registered.")
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count = 0
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try:
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for user in users.each():
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for x in users.each():
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count = +1
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for x in range(20):
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for y in range(20):
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if not os.path.isdir("Photos_of_Thieves/Thief_" + str(count)):
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os.makedirs("Photos_of_Thieves/Thief_" + str(count))
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DBHelper.download_thief_photo("Thief_" + str(count) + "/" + str(x) + ".jpg")
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DBHelper.download_thief_photo("Thief_" + str(count) + "/" + str(y) + ".jpg")
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except:
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print("No Thieves for now.")
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Facial_Recognition_Wrapper.training_recognizer("Fisher")
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Facial_Recognition_Wrapper.face_recognition_inference("Fisher")
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