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Davis King 2017-09-10 22:16:54 -04:00
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python_examples/face_landmark_detection.py
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# points on the face such as the corners of the mouth, along the eyebrows, on # points on the face such as the corners of the mouth, along the eyebrows, on
# the eyes, and so forth. # the eyes, and so forth.
# #
# This face detector is made using the classic Histogram of Oriented # The face detector we use is made using the classic Histogram of Oriented
# Gradients (HOG) feature combined with a linear classifier, an image pyramid, # Gradients (HOG) feature combined with a linear classifier, an image pyramid,
# and sliding window detection scheme. The pose estimator was created by # and sliding window detection scheme. The pose estimator was created by
# using dlib's implementation of the paper: # using dlib's implementation of the paper:
# One Millisecond Face Alignment with an Ensemble of Regression Trees by # One Millisecond Face Alignment with an Ensemble of Regression Trees by
# Vahid Kazemi and Josephine Sullivan, CVPR 2014 # Vahid Kazemi and Josephine Sullivan, CVPR 2014
# and was trained on the iBUG 300-W face landmark dataset. # and was trained on the iBUG 300-W face landmark dataset (see
# https://ibug.doc.ic.ac.uk/resources/facial-point-annotations/):
# C. Sagonas, E. Antonakos, G, Tzimiropoulos, S. Zafeiriou, M. Pantic.
# 300 faces In-the-wild challenge: Database and results.
# Image and Vision Computing (IMAVIS), Special Issue on Facial Landmark Localisation "In-The-Wild". 2016.
# You can get the trained model file from:
# http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2.
# Note that the license for the iBUG 300-W dataset excludes commercial use.
# So you should contact Imperial College London to find out if it's OK for
# you use use this model in a commercial product.
#
# #
# Also, note that you can train your own models using dlib's machine learning # Also, note that you can train your own models using dlib's machine learning
# tools. See train_shape_predictor.py to see an example. # tools. See train_shape_predictor.py to see an example.
# #
# You can get the shape_predictor_68_face_landmarks.dat file from:
# http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2
# #
# COMPILING/INSTALLING THE DLIB PYTHON INTERFACE # COMPILING/INSTALLING THE DLIB PYTHON INTERFACE
# You can install dlib using the command: # You can install dlib using the command: