Smit Shilu smitshilu

Reproduce

# clone this repo
git clone https://github.com/smitshilu/AISecurityCamera.git
cd AISecurityCamera

# Start the Camera feed using following commnad
python start.py

# If you want to save a new face encoding

Reproduce

# clone this repo
git clone https://github.com/smitshilu/AISecurityCamera.git
cd AISecurityCamera

# Start the Camera feed using following commnad
python start.py

# If you want to save a new face encoding

How to install dlib v19.9 or newer (w/ python bindings) from github on macOS and Ubuntu

Pre-reqs:

Have Python 3 installed. On macOS, this could be installed from homebrew or even via standard Python 3.6 downloaded installer from https://www.python.org/download. On Linux, just use your package manager.
On macOS:
- Install XCode from the Mac App Store (or install the XCode command line utils).
- Have homebrew installed
On Linux:

Tensorflow

System information

OS - High Sierra 10.13
Tensorflow - 1.4
Xcode command line tools - 8.2 (Download from here: Xcode - Support - Apple Developer & Switch to different clang version: sudo xcode-select --switch/Library/Developer/CommandLineTools & check version: clang -v)
Cmake - 3.7
Bazel - 0.7.0

	# load the required model for 68 points detection
	predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")
	face_rec = dlib.face_recognition_model_v1('dlib_face_recognition_resnet_model_v1.dat')

	# iterate through all the detected faces
	if (len(face_locations) > 0):
	for face_location in face_locations:
	# get 68 points landmark
	face_encoding = predictor(frame, face_location)
	face_descriptor = face_rec.compute_face_descriptor(frame, face_encoding, 1)

	# Initialize video_capture to get camera feed
	video_capture = cv2.VideoCapture(0)
	video_capture.set(3, 320)
	video_capture.set(4, 240)

	# Grab a single frame from WebCam
	ret, frame = video_capture.read()

	# Initialize haar cascade
	detect_faces = cv2.CascadeClassifier('haarcascade_frontalface_alt2.xml')