Integrated Facial Software to Database and Main Program.

This commit is contained in:
Batuhan Berk Başoğlu 2021-01-24 10:55:36 -05:00
parent 9f7adf2762
commit e1f6e307fa
6 changed files with 117 additions and 110 deletions

View file

@ -9,6 +9,7 @@ try:
except ImportError:
import _pickle as cPickle # Python3.
def enroll_face_dataset():
pwd = sys.path[0]
PREDICTOR_PATH = pwd + '/Facial_models/shape_predictor_68_face_landmarks.dat'
@ -18,7 +19,6 @@ def enroll_face_dataset():
shapePredictor = dlib.shape_predictor(PREDICTOR_PATH)
faceRecognizer = dlib.face_recognition_model_v1(FACE_RECOGNITION_MODEL_PATH)
faceDatasetFolder = pwd + '/Facial_images/face_rec/train/'
subfolders = []
@ -27,7 +27,6 @@ def enroll_face_dataset():
if os.path.isdir(xpath):
subfolders.append(xpath)
nameLabelMap = {}
labels = []
imagePaths = []
@ -58,12 +57,10 @@ def enroll_face_dataset():
faceDescriptor = faceRecognizer.compute_face_descriptor(img, shape)
faceDescriptorList = [x for x in faceDescriptor]
faceDescriptorNdarray = np.asarray(faceDescriptorList, dtype=np.float64)
faceDescriptorNdarray = faceDescriptorNdarray[np.newaxis, :]
if faceDescriptors is None:
faceDescriptors = faceDescriptorNdarray
else:

View file

@ -2,13 +2,13 @@ import os,sys,time
import dlib
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'
@ -23,13 +23,14 @@ faceRecognizer = dlib.face_recognition_model_v1(FACE_RECOGNITION_MODEL_PATH)
index = np.load(pwd + '/Facial_models/index.pkl', allow_pickle=True)
faceDescriptorsEnrolled = np.load(pwd + '/Facial_models/descriptors.npy')
cam = cv2.VideoCapture(1)
cam = cv2.VideoCapture(0)
count = 0
x1 = x2 = y1 = y2 = 0
while True:
cond = False
while DBHelper.get_power() == "on":
t = time.time()
success, im = cam.read()
@ -37,7 +38,6 @@ while True:
print('cannot capture input from camera')
break
if (count % SKIP_FRAMES) == 0:
img = cv2.cvtColor(im, cv2.COLOR_BGR2RGB)
@ -67,15 +67,15 @@ while True:
argmin = np.argmin(distances) # index
minDistance = distances[argmin] # minimum distance
if minDistance <= THRESHOLD:
label = index[argmin]
label = DBHelper.get_firstname(index[argmin]) + "_" + DBHelper.get_lastname(index[argmin])
cond = True
else:
label = 'unknown'
cond = False
# print("time taken = {:.3f} seconds".format(time.time() - t))
cv2.rectangle(im, (x1, y1), (x2, y2), (0, 255, 0), 2)
font_face = cv2.FONT_HERSHEY_SIMPLEX
font_scale = 0.8
@ -83,7 +83,6 @@ while True:
printLabel = '{} {:0.4f}'.format(label, minDistance)
cv2.putText(im, printLabel, (int(x1), int(y1)), font_face, font_scale, text_color, thickness=2)
cv2.imshow('img', im)
k = cv2.waitKey(1) & 0xff
@ -91,4 +90,13 @@ while True:
break
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()

View file

@ -4,6 +4,7 @@ import math
import cv2
import Facial_Recognition_Enrollment
def register_your_face(label):
num_cap = 50

View file

@ -1,5 +1,6 @@
import DBHelper
import Facial_Recognition_Registration
import Facial_Recognition_Enrollment
def upload_your_face(firstname, lastname, email, phone):
@ -13,6 +14,7 @@ def upload_your_face(firstname, lastname, email, phone):
count += 1
DBHelper.upload_data("User_" + str(count), firstname, lastname, email, phone)
Facial_Recognition_Registration.register_your_face("User_" + str(count))
Facial_Recognition_Enrollment.enroll_face_dataset()
for i in range(20):
DBHelper.upload_user_photo("User_" + str(count) + "/" + str(i) + ".jpg")
except:

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@ -1,6 +1,6 @@
import os
import DBHelper
import Facial_Recognition_Wrapper
import Facial_Recognition_Inference
def start():
@ -32,8 +32,7 @@ def start():
print("Success.")
except:
print("No Thieves are registered.")
Facial_Recognition_Wrapper.training_recognizer("LBPH")
Facial_Recognition_Wrapper.face_recognition_inference("LBPH")
Facial_Recognition_Inference
if __name__ == "__main__":