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