Integrate face registration and enrollment
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parent
2d1ee72eb7
commit
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5 changed files with 54 additions and 51 deletions
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@ -9,28 +9,29 @@ try:
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except ImportError:
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except ImportError:
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import _pickle as cPickle # Python3.
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import _pickle as cPickle # Python3.
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pwd = sys.path[0]
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def enroll_face_dataset():
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PREDICTOR_PATH = pwd + '/Facial_models/shape_predictor_68_face_landmarks.dat'
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pwd = sys.path[0]
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FACE_RECOGNITION_MODEL_PATH = pwd + '/Facial_models/dlib_face_recognition_resnet_model_v1.dat'
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PREDICTOR_PATH = pwd + '/Facial_models/shape_predictor_68_face_landmarks.dat'
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FACE_RECOGNITION_MODEL_PATH = pwd + '/Facial_models/dlib_face_recognition_resnet_model_v1.dat'
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faceDetector = dlib.get_frontal_face_detector()
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faceDetector = dlib.get_frontal_face_detector()
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shapePredictor = dlib.shape_predictor(PREDICTOR_PATH)
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shapePredictor = dlib.shape_predictor(PREDICTOR_PATH)
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faceRecognizer = dlib.face_recognition_model_v1(FACE_RECOGNITION_MODEL_PATH)
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faceRecognizer = dlib.face_recognition_model_v1(FACE_RECOGNITION_MODEL_PATH)
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faceDatasetFolder = pwd + '/Facial_images/face_rec/train/'
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faceDatasetFolder = pwd + '/Facial_images/face_rec/train/'
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subfolders = []
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subfolders = []
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for x in os.listdir(faceDatasetFolder):
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for x in os.listdir(faceDatasetFolder):
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xpath = os.path.join(faceDatasetFolder, x)
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xpath = os.path.join(faceDatasetFolder, x)
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if os.path.isdir(xpath):
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if os.path.isdir(xpath):
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subfolders.append(xpath)
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subfolders.append(xpath)
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nameLabelMap = {}
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nameLabelMap = {}
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labels = []
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labels = []
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imagePaths = []
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imagePaths = []
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for i, subfolder in enumerate(subfolders):
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for i, subfolder in enumerate(subfolders):
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for x in os.listdir(subfolder):
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for x in os.listdir(subfolder):
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xpath = os.path.join(subfolder, x)
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xpath = os.path.join(subfolder, x)
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if x.endswith('jpg'):
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if x.endswith('jpg'):
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@ -38,10 +39,10 @@ for i, subfolder in enumerate(subfolders):
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labels.append(i)
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labels.append(i)
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nameLabelMap[xpath] = subfolder.split('/')[-1]
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nameLabelMap[xpath] = subfolder.split('/')[-1]
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index = {}
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index = {}
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i = 0
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i = 0
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faceDescriptors = None
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faceDescriptors = None
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for imagePath in imagePaths:
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for imagePath in imagePaths:
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print("processing: {}".format(imagePath))
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print("processing: {}".format(imagePath))
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img = cv2.imread(imagePath)
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img = cv2.imread(imagePath)
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@ -71,7 +72,7 @@ for imagePath in imagePaths:
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index[i] = nameLabelMap[imagePath]
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index[i] = nameLabelMap[imagePath]
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i += 1
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i += 1
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# Write descriors and index to disk
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# Write descriors and index to disk
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np.save(pwd+'/Facial_models/descriptors.npy', faceDescriptors)
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np.save(pwd+'/Facial_models/descriptors.npy', faceDescriptors)
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with open(pwd+'/Facial_models/index.pkl', 'wb') as f:
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with open(pwd+'/Facial_models/index.pkl', 'wb') as f:
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cPickle.dump(index, f)
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cPickle.dump(index, f)
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@ -2,10 +2,11 @@ import sys
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import os
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import os
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import math
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import math
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import cv2
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import cv2
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import Facial_Recognition_Enrollment
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def register_your_face(label):
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def register_your_face(label):
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num_cap = 60
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num_cap = 50
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path = sys.path[0] + '/Facial_images/face_rec/train/' + label
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path = sys.path[0] + '/Facial_images/face_rec/train/' + label
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@ -14,7 +15,7 @@ def register_your_face(label):
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if not folder:
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if not folder:
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os.makedirs(path)
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os.makedirs(path)
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cap = cv2.VideoCapture(0)
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cap = cv2.VideoCapture(1)
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c = 0
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c = 0
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while c < num_cap:
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while c < num_cap:
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ret, frame = cap.read()
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ret, frame = cap.read()
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@ -31,5 +32,6 @@ def register_your_face(label):
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if __name__ == "__main__":
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if __name__ == "__main__":
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label = input('Enter a label:')
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label = input('Enter a label: ')
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register_your_face(label)
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register_your_face(label)
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Facial_Recognition_Enrollment.enroll_face_dataset()
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__pycache__/Facial_Recognition_Enrollment.cpython-38.pyc
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__pycache__/Facial_Recognition_Enrollment.cpython-38.pyc
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