batuhan-basoglu/Vehicle-Anti-Theft-Face-Recognition-System
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Fixed a Typo.

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Batuhan Berk Başoğlu 2020-11-14 20:38:37 -05:00
parent cf228272a8
commit 87dec86a71
3 changed files with 12 additions and 7 deletions
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15
Facial_Recognition_Wrapper.py
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@ -7,7 +7,8 @@ import numpy as np
import Facial_Recognition_Render as fr import Facial_Recognition_Render as fr
import _pickle as cPickle import _pickle as cPickle
import glob import glob
'import Hardware.Motor' #Line 225-228
'import Hardware.Motor' # Line 225-228
faceWidth = 320 faceWidth = 320
faceHeight = 320 faceHeight = 320
@ -172,13 +173,13 @@ def face_recognition_inference(rec_type):
print(sys.path[0]) print(sys.path[0])
landmarkDetector = dlib.shape_predictor(sys.path[0] + '/Facial_models/shape_predictor_68_face_landmarks.dat') landmarkDetector = dlib.shape_predictor(sys.path[0] + '/Facial_models/shape_predictor_68_face_landmarks.dat')
if (rec_type == 'LBPH'): if rec_type == 'LBPH':
faceRecognizer = cv2.face.LBPHFaceRecognizer_create() faceRecognizer = cv2.face.LBPHFaceRecognizer_create()
print("Test using LBPH Faces") print("Test using LBPH Faces")
elif (rec_type == 'Eigen'): elif rec_type == 'Eigen':
faceRecognizer = cv2.face.EigenFaceRecognizer_create() faceRecognizer = cv2.face.EigenFaceRecognizer_create()
print("Test using Eigen Faces") print("Test using Eigen Faces")
elif (rec_type == 'Fisher'): elif rec_type == 'Fisher':
faceRecognizer = cv2.face.FisherFaceRecognizer_create() faceRecognizer = cv2.face.FisherFaceRecognizer_create()
print("Test using Fisher Faces") print("Test using Fisher Faces")
@ -187,7 +188,7 @@ def face_recognition_inference(rec_type):
cam = cv2.VideoCapture(0) cam = cv2.VideoCapture(0)
while (True): while True:
# imagePath = testFiles[i] # imagePath = testFiles[i]
success, original = cam.read() success, original = cam.read()
im = cv2.resize(original, (640, 480)) im = cv2.resize(original, (640, 480))
@ -222,7 +223,7 @@ def face_recognition_inference(rec_type):
text = '{} {}%'.format(labelsMap[predictedLabel], round(score, 5)) text = '{} {}%'.format(labelsMap[predictedLabel], round(score, 5))
cv2.rectangle(original, (x1, y1), (x2, y2), (0, 255, 0), 5) cv2.rectangle(original, (x1, y1), (x2, y2), (0, 255, 0), 5)
cv2.putText(original, text, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 0), 3) cv2.putText(original, text, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 0), 3)
'Hardware.Motor.Motor.stop_motor()' 'Hardware.Motor.Motor.stop_alarm()'
'Hardware.Motor.Motor.start_motor()' 'Hardware.Motor.Motor.start_motor()'
'Hardware.Motor.Motor.stop_motor()' 'Hardware.Motor.Motor.stop_motor()'
'Hardware.Motor.Motor.start_alarm()' 'Hardware.Motor.Motor.start_alarm()'
@ -241,7 +242,7 @@ if __name__ == "__main__":
if mode == 'train': if mode == 'train':
training_recognizer(rec_type) training_recognizer(rec_type)
elif (mode == 'test'): elif mode == 'test':
face_recognition_inference(rec_type) face_recognition_inference(rec_type)
# video process (keep it in case if needed) # video process (keep it in case if needed)

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__pycache__/Facial_Recognition_Wrapper.cpython-36.pyc
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4
start_engine.py
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@ -28,3 +28,7 @@ def start():
print("No Thieves for now.") print("No Thieves for now.")
Facial_Recognition_Wrapper.training_recognizer("Fisher") Facial_Recognition_Wrapper.training_recognizer("Fisher")
Facial_Recognition_Wrapper.face_recognition_inference("Fisher") Facial_Recognition_Wrapper.face_recognition_inference("Fisher")