Integrate face registration and enrollment

This commit is contained in:
Feier Zhang 2021-01-19 17:08:55 -05:00
parent 2d1ee72eb7
commit 4d0d442ab6
5 changed files with 54 additions and 51 deletions

View file

@ -9,28 +9,29 @@ try:
except ImportError: except ImportError:
import _pickle as cPickle # Python3. import _pickle as cPickle # Python3.
pwd = sys.path[0] def enroll_face_dataset():
PREDICTOR_PATH = pwd + '/Facial_models/shape_predictor_68_face_landmarks.dat' pwd = sys.path[0]
FACE_RECOGNITION_MODEL_PATH = pwd + '/Facial_models/dlib_face_recognition_resnet_model_v1.dat' 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() faceDetector = dlib.get_frontal_face_detector()
shapePredictor = dlib.shape_predictor(PREDICTOR_PATH) shapePredictor = dlib.shape_predictor(PREDICTOR_PATH)
faceRecognizer = dlib.face_recognition_model_v1(FACE_RECOGNITION_MODEL_PATH) faceRecognizer = dlib.face_recognition_model_v1(FACE_RECOGNITION_MODEL_PATH)
faceDatasetFolder = pwd + '/Facial_images/face_rec/train/' faceDatasetFolder = pwd + '/Facial_images/face_rec/train/'
subfolders = [] subfolders = []
for x in os.listdir(faceDatasetFolder): for x in os.listdir(faceDatasetFolder):
xpath = os.path.join(faceDatasetFolder, x) xpath = os.path.join(faceDatasetFolder, x)
if os.path.isdir(xpath): if os.path.isdir(xpath):
subfolders.append(xpath) subfolders.append(xpath)
nameLabelMap = {} nameLabelMap = {}
labels = [] labels = []
imagePaths = [] imagePaths = []
for i, subfolder in enumerate(subfolders): for i, subfolder in enumerate(subfolders):
for x in os.listdir(subfolder): for x in os.listdir(subfolder):
xpath = os.path.join(subfolder, x) xpath = os.path.join(subfolder, x)
if x.endswith('jpg'): if x.endswith('jpg'):
@ -38,10 +39,10 @@ for i, subfolder in enumerate(subfolders):
labels.append(i) labels.append(i)
nameLabelMap[xpath] = subfolder.split('/')[-1] nameLabelMap[xpath] = subfolder.split('/')[-1]
index = {} index = {}
i = 0 i = 0
faceDescriptors = None faceDescriptors = None
for imagePath in imagePaths: for imagePath in imagePaths:
print("processing: {}".format(imagePath)) print("processing: {}".format(imagePath))
img = cv2.imread(imagePath) img = cv2.imread(imagePath)
@ -71,7 +72,7 @@ for imagePath in imagePaths:
index[i] = nameLabelMap[imagePath] index[i] = nameLabelMap[imagePath]
i += 1 i += 1
# Write descriors and index to disk # Write descriors and index to disk
np.save(pwd+'/Facial_models/descriptors.npy', faceDescriptors) np.save(pwd+'/Facial_models/descriptors.npy', faceDescriptors)
with open(pwd+'/Facial_models/index.pkl', 'wb') as f: with open(pwd+'/Facial_models/index.pkl', 'wb') as f:
cPickle.dump(index, f) cPickle.dump(index, f)

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@ -2,10 +2,11 @@ import sys
import os import os
import math import math
import cv2 import cv2
import Facial_Recognition_Enrollment
def register_your_face(label): def register_your_face(label):
num_cap = 60 num_cap = 50
path = sys.path[0] + '/Facial_images/face_rec/train/' + label path = sys.path[0] + '/Facial_images/face_rec/train/' + label
@ -14,7 +15,7 @@ def register_your_face(label):
if not folder: if not folder:
os.makedirs(path) os.makedirs(path)
cap = cv2.VideoCapture(0) cap = cv2.VideoCapture(1)
c = 0 c = 0
while c < num_cap: while c < num_cap:
ret, frame = cap.read() ret, frame = cap.read()
@ -31,5 +32,6 @@ def register_your_face(label):
if __name__ == "__main__": if __name__ == "__main__":
label = input('Enter a label:') label = input('Enter a label: ')
register_your_face(label) register_your_face(label)
Facial_Recognition_Enrollment.enroll_face_dataset()

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