From 205b26f8313327e975652804246357763657feb9 Mon Sep 17 00:00:00 2001 From: Davis King Date: Sun, 10 Sep 2017 22:16:54 -0400 Subject: [PATCH] Improved citations --- python_examples/face_landmark_detection.py | 16 ++++++++++++---- 1 file changed, 12 insertions(+), 4 deletions(-) diff --git a/python_examples/face_landmark_detection.py b/python_examples/face_landmark_detection.py index e9957b647..c04005cdd 100755 --- a/python_examples/face_landmark_detection.py +++ b/python_examples/face_landmark_detection.py @@ -6,19 +6,27 @@ # points on the face such as the corners of the mouth, along the eyebrows, on # 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, # and sliding window detection scheme. The pose estimator was created by # using dlib's implementation of the paper: # One Millisecond Face Alignment with an Ensemble of Regression Trees by # 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 # 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 # You can install dlib using the command: