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#!/usr/bin/python
# The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt
#
# This example program shows how to find frontal human faces in an image. In
# particular, it shows how you can take a list of images from the command
# line and display each on the screen with red boxes overlaid on each human
# face.
#
# The examples/faces folder contains some jpg images of people. You can run
# this program on them and see the detections by executing the following command:
# ./face_detector.py ../examples/faces/*.jpg
#
# This face detector is made using the now classic Histogram of Oriented
# Gradients (HOG) feature combined with a linear classifier, an image
# pyramid, and sliding window detection scheme. This type of object detector
# is fairly general and capable of detecting many types of semi-rigid objects
# in addition to human faces. Therefore, if you are interested in making
# your own object detectors then read the train_object_detector.py example
# program.
#
#
# COMPILING THE DLIB PYTHON INTERFACE
# Dlib comes with a compiled python interface for python 2.7 on MS Windows. If
# you are using another python version or operating system then you need to
# compile the dlib python interface before you can use this file. To do this,
# run compile_dlib_python_module.bat. This should work on any operating system
# so long as you have CMake and boost-python installed. On Ubuntu, this can be
# done easily by running the command: sudo apt-get install libboost-python-dev cmake
import dlib, sys
from skimage import io
detector = dlib.get_frontal_face_detector()
win = dlib.image_window()
for f in sys.argv[1:]:
print "processing file: ", f
img = io.imread(f)
# 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: ", len(dets)
for d in dets:
print " detection position left,top,right,bottom:", d.left(), d.top(), d.right(), d.bottom()
win.clear_overlay()
win.set_image(img)
win.add_overlay(dets)
raw_input("Hit enter to continue")