Facial Landmark Detector

Dlib is a popular library. It can be used for face detection or face recognition. In this article I will use it for facial landmark detection. Facial landmarks are fecial features like nose, eyes, mouth or jaw.


Start with installing Dlib library. Dlib requires Lib Boost.

sudo apt-get install libboost-all-dev

Now we can install Dlib.

sudo pip install dlib

Following example uses PIL and numpy packages. Instead of Pillow it is possible to use skimage package.

pip install Pillow
pip install numpy

Note that in order to detect facial landmarks, a previously trained model file is needed. You can download one from Dlib site.

Download model file from this link : http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2

After download is completed, extract the archive and make sure its location is correctly referenced in the source file.

	"""You can download a trained facial shape predictor from:
	http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2)"""
	import dlib
	from PIL import Image
	from PIL import ImageDraw
	import numpy as np
	import os
	predictor_path = "shape_predictor_68_face_landmarks.dat"
	faces_image_path = "iamages/00000005.png"
	def detect_landmarks(image):
	# obtain detector and predictor
	detector = dlib.get_frontal_face_detector()
	predictor = dlib.shape_predictor(predictor_path)
	# convert image to numpy array
	img = np.asanyarray(image)
	img.flags.writeable =True
	#output list
	face_landmark_tuples=[]
	# Ask the detector to find the bounding boxes of each face. The 1 in the
	# second argument indicates that we should upsample the image 1 time. This
	# will make everything bigger and allow us to detect more faces.
	dets = detector(img, 1)
	print("Number of faces detected: {}".format(len(dets)))
	for k, rect in enumerate(dets):
	print("Detection {}: Left: {} Top: {} Right: {} Bottom: {}"
	.format(k, rect.left(), rect.top(), rect.right(), rect.bottom()))
	# Get the landmarks/parts for the face in box rect.
	shape = predictor(img, rect)
	face_landmark_tuples.append((k,rect,shape))
	return face_landmark_tuples
	def draw_landmarks(image,shape):
	parts = []
	radius=1
	# copy original image, do not touch it
	out_image=image.copy()
	# extract parts to list
	for i in xrange(0, shape.num_parts, 1):
	print("Part {}".format(shape.part(i)))
	parts.append(shape.part(i))
	# for each part, draw a circle
	draw = ImageDraw.Draw(out_image)
	for part in parts:
	x = part.x
	y = part.y
	draw.ellipse((x - radius, y - radius, x + radius, y + radius), fill=(255, 0, 0, 255))
	return out_image
	def draw_glasses(image,shape):
	# obtain image dimensions and calculate offsets
	width,height=image.size
	offset_vertical=height/50
	offset_horizontal=width/50
	# add left and right glass points
	parts_left=obtain_left_glass(offset_horizontal, offset_vertical, shape)
	parts_right=obtain_right_glass(offset_horizontal, offset_vertical, shape)
	# copy original image, do not touch at
	out_image=image.copy()
	# draw lines
	draw = ImageDraw.Draw(out_image)
	draw.line(parts_left, fill=(0, 0, 0), width=10)
	draw.line(parts_right, fill=(0, 0, 0), width=10)
	return out_image
	def obtain_right_glass(offset_horizontal, offset_vertical, shape):
	parts_right=[]
	# add tip of nose
	part = shape.part(28)
	_x = part.x + 2 * offset_horizontal
	_y = part.y
	parts_right.append((_x, _y))
	# add eyebrow
	for i in xrange(22, 27, 1):
	_x = shape.part(i).x
	_y = shape.part(i).y - offset_vertical
	parts_right.append((_x, _y))
	# right top of face
	part = shape.part(16)
	_x = part.x
	_y = part.y - offset_vertical
	parts_right.append((_x, _y))
	# right nostril
	part = shape.part(35)
	_x = part.x + 4 * offset_horizontal
	_y = part.y - 4 * offset_vertical
	parts_right.append((_x, _y))
	# add tip of nose again to close loop
	part = shape.part(28)
	_x = part.x + 2 * offset_horizontal
	_y = part.y
	parts_right.append((_x, _y))
	return parts_right
	def obtain_left_glass(offset_horizontal, offset_vertical, shape):
	parts_left = []
	# left top of face
	part = shape.part(0)
	_x = part.x
	_y = part.y + offset_vertical
	parts_left.append((_x, _y))
	# add eyebrow
	for i in xrange(17, 22, 1):
	_x = shape.part(i).x
	_y = shape.part(i).y - offset_vertical
	parts_left.append((_x, _y))
	# add tip of nose
	part = shape.part(28)
	_x = part.x - 2 * offset_horizontal
	_y = part.y
	parts_left.append((_x, _y))
	# left nostril
	part = shape.part(31)
	_x = part.x - 4 * offset_horizontal
	_y = part.y - 4 * offset_vertical
	parts_left.append((_x, _y))
	# left top of face to close the loop
	part = shape.part(0)
	_x = part.x
	_y = part.y + offset_vertical
	parts_left.append((_x, _y))
	return parts_left
	def main():
	# read image and convert to np array
	image=Image.open(faces_image_path)
	# detect faces and landmarks
	face_landmark_tuples = detect_landmarks(image=image)
	for k,rect,shape in face_landmark_tuples:
	# draw landmarks to image
	out_image=draw_landmarks(image,shape=shape)
	# determine file name and save new image
	path_name=os.path.dirname(faces_image_path)
	output_file=os.path.join(path_name,str(k)+os.path.basename(faces_image_path))
	out_image.save(output_file)
	if __name__ =='__main__':main()

view raw facial_landmark_generator.py hosted with ❤ by GitHub

The application first tries to detect faces in the given image. After that for each face it tries to detect landmarks. For each face an image file is created and landmarks are drawn to that file.

Landmarks are returned in a shape object. Shape object contains part objects which are two dimensional points each of which corresponds to a landmark point. To understand which point corresponds to which landmark point look at the following image. It is taken from dlib link https://sourceforge.net/p/dclib/discussion/442518/thread/c038d05f/

Given application also contains sample methods to add circles around eyes to simulate glasses.