From eae512586e326141596f996f4db127e10644cc65 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Batuhan=20Berk=20Ba=C5=9Fo=C4=9Flu?= Date: Sun, 24 Jan 2021 12:20:01 -0500 Subject: [PATCH] Updated the Integration. Tested the system, it works. --- Facial_Recognition_Inference.py | 148 +++++++++--------- Facial_images/face_rec/train/User_1/0.jpg | Bin 77037 -> 76142 bytes Facial_images/face_rec/train/User_1/1.jpg | Bin 76183 -> 76005 bytes Facial_images/face_rec/train/User_1/10.jpg | Bin 80879 -> 77264 bytes Facial_images/face_rec/train/User_1/11.jpg | Bin 81186 -> 75082 bytes Facial_images/face_rec/train/User_1/12.jpg | Bin 83736 -> 75207 bytes Facial_images/face_rec/train/User_1/13.jpg | Bin 84857 -> 75352 bytes Facial_images/face_rec/train/User_1/14.jpg | Bin 83711 -> 75334 bytes Facial_images/face_rec/train/User_1/15.jpg | Bin 84122 -> 75052 bytes Facial_images/face_rec/train/User_1/16.jpg | Bin 84063 -> 75681 bytes Facial_images/face_rec/train/User_1/17.jpg | Bin 83659 -> 74606 bytes Facial_images/face_rec/train/User_1/18.jpg | Bin 83550 -> 74889 bytes Facial_images/face_rec/train/User_1/19.jpg | Bin 82686 -> 74673 bytes Facial_images/face_rec/train/User_1/2.jpg | Bin 76222 -> 76884 bytes Facial_images/face_rec/train/User_1/3.jpg | Bin 76042 -> 77130 bytes Facial_images/face_rec/train/User_1/4.jpg | Bin 75207 -> 77359 bytes Facial_images/face_rec/train/User_1/5.jpg | Bin 77734 -> 76997 bytes Facial_images/face_rec/train/User_1/6.jpg | Bin 77402 -> 76766 bytes Facial_images/face_rec/train/User_1/7.jpg | Bin 78518 -> 76563 bytes Facial_images/face_rec/train/User_1/8.jpg | Bin 81075 -> 76929 bytes Facial_images/face_rec/train/User_1/9.jpg | Bin 81762 -> 77021 bytes Facial_images/face_rec/train/User_2/0.jpg | Bin 88301 -> 81792 bytes Facial_images/face_rec/train/User_2/1.jpg | Bin 89924 -> 81956 bytes Facial_images/face_rec/train/User_2/10.jpg | Bin 89019 -> 80072 bytes Facial_images/face_rec/train/User_2/11.jpg | Bin 89892 -> 79745 bytes Facial_images/face_rec/train/User_2/12.jpg | Bin 90194 -> 80230 bytes Facial_images/face_rec/train/User_2/13.jpg | Bin 88699 -> 79451 bytes Facial_images/face_rec/train/User_2/14.jpg | Bin 85448 -> 80195 bytes Facial_images/face_rec/train/User_2/15.jpg | Bin 83875 -> 79975 bytes Facial_images/face_rec/train/User_2/16.jpg | Bin 84206 -> 80803 bytes Facial_images/face_rec/train/User_2/17.jpg | Bin 85817 -> 80736 bytes Facial_images/face_rec/train/User_2/18.jpg | Bin 88714 -> 80541 bytes Facial_images/face_rec/train/User_2/19.jpg | Bin 88106 -> 80751 bytes Facial_images/face_rec/train/User_2/2.jpg | Bin 86596 -> 79038 bytes Facial_images/face_rec/train/User_2/3.jpg | Bin 86986 -> 79580 bytes Facial_images/face_rec/train/User_2/4.jpg | Bin 87133 -> 79724 bytes Facial_images/face_rec/train/User_2/5.jpg | Bin 90389 -> 80440 bytes Facial_images/face_rec/train/User_2/6.jpg | Bin 89720 -> 80055 bytes Facial_images/face_rec/train/User_2/7.jpg | Bin 89457 -> 80393 bytes Facial_images/face_rec/train/User_2/8.jpg | Bin 88964 -> 79444 bytes Facial_images/face_rec/train/User_2/9.jpg | Bin 88844 -> 79526 bytes ...cial_Recognition_Enrollment.cpython-36.pyc | Bin 0 -> 2190 bytes ...acial_Recognition_Inference.cpython-36.pyc | Bin 0 -> 2616 bytes ...al_Recognition_Registration.cpython-36.pyc | Bin 883 -> 1125 bytes __pycache__/Start_Engine.cpython-36.pyc | Bin 1331 -> 1275 bytes __pycache__/Upload_Face.cpython-36.pyc | Bin 1057 -> 1085 bytes start_engine.py | 2 +- 47 files changed, 78 insertions(+), 72 deletions(-) create mode 100644 __pycache__/Facial_Recognition_Enrollment.cpython-36.pyc create mode 100644 __pycache__/Facial_Recognition_Inference.cpython-36.pyc diff --git a/Facial_Recognition_Inference.py b/Facial_Recognition_Inference.py index 271a89510..78615670a 100644 --- a/Facial_Recognition_Inference.py +++ b/Facial_Recognition_Inference.py @@ -4,99 +4,105 @@ import cv2 import numpy as np import DBHelper -try: - import cPickle # Python 2 -except ImportError: - import _pickle as cPickle # Python 3 -pwd = sys.path[0] -PREDICTOR_PATH = pwd + '/Facial_models/shape_predictor_68_face_landmarks.dat' -FACE_RECOGNITION_MODEL_PATH = pwd + '/Facial_models/dlib_face_recognition_resnet_model_v1.dat' +def inference(): + try: + import cPickle # Python 2 + except ImportError: + import _pickle as cPickle # Python 3 -SKIP_FRAMES = 1 -THRESHOLD = 0.4 + pwd = sys.path[0] + PREDICTOR_PATH = pwd + '/Facial_models/shape_predictor_68_face_landmarks.dat' + FACE_RECOGNITION_MODEL_PATH = pwd + '/Facial_models/dlib_face_recognition_resnet_model_v1.dat' -faceDetector = dlib.get_frontal_face_detector() -shapePredictor = dlib.shape_predictor(PREDICTOR_PATH) -faceRecognizer = dlib.face_recognition_model_v1(FACE_RECOGNITION_MODEL_PATH) + SKIP_FRAMES = 1 + THRESHOLD = 0.4 -index = np.load(pwd + '/Facial_models/index.pkl', allow_pickle=True) -faceDescriptorsEnrolled = np.load(pwd + '/Facial_models/descriptors.npy') + faceDetector = dlib.get_frontal_face_detector() + shapePredictor = dlib.shape_predictor(PREDICTOR_PATH) + faceRecognizer = dlib.face_recognition_model_v1(FACE_RECOGNITION_MODEL_PATH) -cam = cv2.VideoCapture(0) -count = 0 + index = np.load(pwd + '/Facial_models/index.pkl', allow_pickle=True) + faceDescriptorsEnrolled = np.load(pwd + '/Facial_models/descriptors.npy') -x1 = x2 = y1 = y2 = 0 + cam = cv2.VideoCapture(0) + count = 0 -cond = False + x1 = x2 = y1 = y2 = 0 -while DBHelper.get_power() == "on": - t = time.time() - success, im = cam.read() + cond = False - if not success: - print('cannot capture input from camera') - break + while DBHelper.get_power() == "on": + t = time.time() + success, im = cam.read() - if (count % SKIP_FRAMES) == 0: + if not success: + print('cannot capture input from camera') + break - img = cv2.cvtColor(im, cv2.COLOR_BGR2RGB) - faces = faceDetector(cv2.cvtColor(img, cv2.COLOR_BGR2RGB)) + if (count % SKIP_FRAMES) == 0: - for face in faces: + img = cv2.cvtColor(im, cv2.COLOR_BGR2RGB) + faces = faceDetector(cv2.cvtColor(img, cv2.COLOR_BGR2RGB)) - shape = shapePredictor(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), face) + for face in faces: - x1 = face.left() - y1 = face.top() - x2 = face.right() - y2 = face.bottom() + shape = shapePredictor(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), face) - faceDescriptor = faceRecognizer.compute_face_descriptor(img, shape) + x1 = face.left() + y1 = face.top() + x2 = face.right() + y2 = face.bottom() - # dlib format to list - faceDescriptorList = [m for m in faceDescriptor] - # to numpy array - faceDescriptorNdarray = np.asarray(faceDescriptorList, dtype=np.float64) - faceDescriptorNdarray = faceDescriptorNdarray[np.newaxis, :] + faceDescriptor = faceRecognizer.compute_face_descriptor(img, shape) - # Euclidean distances - distances = np.linalg.norm(faceDescriptorsEnrolled - faceDescriptorNdarray, axis=1) + # dlib format to list + faceDescriptorList = [m for m in faceDescriptor] + # to numpy array + faceDescriptorNdarray = np.asarray(faceDescriptorList, dtype=np.float64) + faceDescriptorNdarray = faceDescriptorNdarray[np.newaxis, :] - # Calculate minimum distance and index of face - argmin = np.argmin(distances) # index - minDistance = distances[argmin] # minimum distance + # Euclidean distances + distances = np.linalg.norm(faceDescriptorsEnrolled - faceDescriptorNdarray, axis=1) - if minDistance <= THRESHOLD: - label = DBHelper.get_firstname(index[argmin]) + "_" + DBHelper.get_lastname(index[argmin]) - cond = True - else: - label = 'unknown' - cond = False + # Calculate minimum distance and index of face + argmin = np.argmin(distances) # index + minDistance = distances[argmin] # minimum distance - # print("time taken = {:.3f} seconds".format(time.time() - t)) + if minDistance <= THRESHOLD: + label = DBHelper.get_firstname(index[argmin]) + "_" + DBHelper.get_lastname(index[argmin]) + cond = True + else: + label = 'unknown' + cond = False - cv2.rectangle(im, (x1, y1), (x2, y2), (0, 255, 0), 2) - font_face = cv2.FONT_HERSHEY_SIMPLEX - font_scale = 0.8 - text_color = (0, 255, 0) - printLabel = '{} {:0.4f}'.format(label, minDistance) - cv2.putText(im, printLabel, (int(x1), int(y1)), font_face, font_scale, text_color, thickness=2) + # print("time taken = {:.3f} seconds".format(time.time() - t)) - cv2.imshow('img', im) + cv2.rectangle(im, (x1, y1), (x2, y2), (0, 255, 0), 2) + font_face = cv2.FONT_HERSHEY_SIMPLEX + font_scale = 0.8 + text_color = (0, 255, 0) + printLabel = '{} {:0.4f}'.format(label, minDistance) + cv2.putText(im, printLabel, (int(x1), int(y1)), font_face, font_scale, text_color, thickness=2) - k = cv2.waitKey(1) & 0xff - if k == 27: - break + cv2.imshow('img', im) - count += 1 - if cond: - DBHelper.set_motor("on") - DBHelper.set_alarm("off") - elif not cond: - DBHelper.set_motor("off") - DBHelper.set_alarm("on") + k = cv2.waitKey(1) & 0xff + if k == 27: + break -DBHelper.set_alarm("off") -DBHelper.set_motor("off") -cv2.destroyAllWindows() + count += 1 + if cond: + DBHelper.set_motor("on") + DBHelper.set_alarm("off") + elif not cond: + DBHelper.set_motor("off") + DBHelper.set_alarm("on") + + DBHelper.set_alarm("off") + DBHelper.set_motor("off") + cv2.destroyAllWindows() + + +if __name__ == "__main__": + inference() diff --git a/Facial_images/face_rec/train/User_1/0.jpg b/Facial_images/face_rec/train/User_1/0.jpg index 536e60dafde398da402d7853d3f5c595d39049ac..a900455b9a0ea0c71078135285b525c18ddea1f3 100644 GIT binary patch literal 76142 zcmbTdXH-*L)CG#yE@B51R1^@Ds#KMB1p#RyB?&!O>4YTG0+Et?Eg)S$KtSZuO9)5_ z0RrSohft&hgb*TNLQQBwh$+1IedE3N=lyu^9Y)RovUA2>IeV`)=Unsbf7|~qbjIAo z%tYwG0U@CSf*+xMvXGI`9|wLPzt4aCJ`NrHeLj5X(7{7T4j(!4Kd+<5j~zLB{OFM* z$Apg^Kk@qz{B~0K#L3@({JzNle)NyS2M-=TarDU1{~7ZC>9qf!(Ai@LzW?#}!2{Al zf1EvV@a%#8P9Z75JP-fR^aPXr-{Zg^2M--Sa#S!4VZi|G8Nu`q9u!Rauwcf5(UF4p zg$|uPeD3<42S?7^JUuEMa6#>#l>B2dhBaSAZAUg_)t?2vJbpq<{Ng2v8*=hDZz*VK zYH8oSci-rtv5Dy;Gjlt801)Kh=;ZF<>E-R?>lYLpf(Q*mzIgTeO?1rL*tpcR_vsm# zAF{Fw3X6(MO3TVCYU}E;4YX{|fB?j%!-zM zL?yQmbCd~}KckpSUE3EDb(DtR>JXvMtdR~v6-u;clZC!#C+h6|U=rFH=={d#ME+U^T!`^8-nXDHK+6LVfi^R?Pe}Pn^G|AV-Ni+lyE_Aq8p~$!Qgwc0rS@L zUVh<@waxXqb+#JepmkI;#!lS~YiPQKMv1fhE|ZvgW?~i&WH@nO=#O%(jtux5uwq{* 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