From 47c73ab74471418f42562edcbbd9060aad3e2ec1 Mon Sep 17 00:00:00 2001
From: Andre Anjos <andre.anjos@idiap.ch>
Date: Fri, 21 Sep 2012 10:40:00 +0200
Subject: [PATCH] Better package standardization
---
MANIFEST.in | 2 +
README.rst | 70 +++++++++++++++++++++++++++++++++
flandmark/__init__.py | 91 ++++++++++++++++++++++++++++++++++++++++++-
flandmark/ext/ext.cpp | 2 +-
flandmark/test.py | 5 +--
setup.py | 37 +++++++++++++++++-
6 files changed, 200 insertions(+), 7 deletions(-)
create mode 100644 MANIFEST.in
create mode 100644 README.rst
diff --git a/MANIFEST.in b/MANIFEST.in
new file mode 100644
index 0000000..d361b96
--- /dev/null
+++ b/MANIFEST.in
@@ -0,0 +1,2 @@
+include README.rst *.cfg bootstrap.py
+recursive-include flandmark *.sql3 *.cpp *.h *.xml *.dat
diff --git a/README.rst b/README.rst
new file mode 100644
index 0000000..37720e0
--- /dev/null
+++ b/README.rst
@@ -0,0 +1,70 @@
+==============================
+ Python Bindings to flandmark
+==============================
+
+This package is a simple Boost.Python wrapper to the (rather quick) open-source
+facial landmark detector `flandmark
+<http://cmp.felk.cvut.cz/~uricamic/flandmark/index.php>`_. If you use this
+package, the author asks you to cite the following paper::
+
+ @InProceedings{Uricar-Franc-Hlavac-VISAPP-2012,
+ author = {U{\\v{r}}i{\\v{c}}{\\'{a}}{\\v{r}}, Michal and Franc, Vojt{\\v{e}}ch and Hlav{\\'{a}}{\\v{c}}, V{\\'{a}}clav},
+ title = {Detector of Facial Landmarks Learned by the Structured Output {SVM}},
+ year = {2012},
+ pages = {547-556},
+ booktitle = {VISAPP '12: Proceedings of the 7th International Conference on Computer Vision Theory and Applications},
+ editor = {Csurka, Gabriela and Braz, Jos{\'{e}}},
+ publisher = {SciTePress --- Science and Technology Publications},
+ address = {Portugal},
+ volume = {1},
+ isbn = {978-989-8565-03-7},
+ book_pages = {747},
+ month = {February},
+ day = {24-26},
+ venue = {Rome, Italy},
+ keywords = {Facial Landmark Detection, Structured Output Classification, Support Vector Machines, Deformable Part Models},
+ prestige = {important},
+ authorship = {50-40-10},
+ status = {published},
+ project = {FP7-ICT-247525 HUMAVIPS, PERG04-GA-2008-239455 SEMISOL,
+ Czech Ministry of Education project 1M0567},
+ www = {http://www.visapp.visigrapp.org},
+ }
+
+Installation
+------------
+
+To install these bindings, you will need the open-source library `Bob
+<http://www.idiap.ch/software/bob/>`_ installed somewhere. At least version 1.1
+of Bob is required. If you have compiled Bob yourself and installed it on a
+non-standard location, you will need to note down the path leading to the root
+of that installation.
+
+Just type::
+
+ $ python bootstrap.py
+ $ ./bin/buildout
+
+If Bob is installed in a non-standard location, remember to use the **same
+python interpreter** that was used to compile Bob (replace ``<bob-root>`` with
+the root of your local installation of Bob)::
+
+ $ <bob-root>/bin/python bootstrap.py
+ $ PKG_CONFIG_PATH=<bob-root>/lib/pkgconfig ./bin/buildout
+
+The `PKG_CONFIG_PATH` variable will help ``buildout`` find the correct include
+and link paths to your non-stock Bob installation.
+
+Usage
+-----
+
+Pretty simple, just do something like::
+
+ import bob
+ import flandmark
+
+ video = bob.io.VideoReader('myvideo.avi')
+ localize = flandmark.Localizer()
+
+ for i, frame in enumerate(video):
+ print localize(frame)
diff --git a/flandmark/__init__.py b/flandmark/__init__.py
index 6766446..3ad5d7b 100644
--- a/flandmark/__init__.py
+++ b/flandmark/__init__.py
@@ -1 +1,90 @@
-from ._flandmark import *
+from . import _flandmark
+
+from pkg_resources import resource_filename
+
+def __filename__(f):
+ """Returns the test file on the "data" subdirectory"""
+ return resource_filename(__name__, f)
+
+class Localizer(_flandmark.Localizer):
+ """A fast and effective facial landmark localization framework based on
+ flandmark
+
+ Consult http://cmp.felk.cvut.cz/~uricamic/flandmark/index.php for more
+ information.
+ """
+
+ def __init__(self, detection_model=resource_filename(__name__,
+ 'haarcascade_frontalface_alt.xml'),
+ localization_model=resource_filename(__name__,
+ 'flandmark_model.dat')):
+ """Builds a new facial localization model.
+
+ Raises RuntimeError's if the models either don't exist or can't be loaded.
+
+ Keyword parameters:
+
+ detection_model
+ An OpenCV (xml) detection model file for a CvHaarClassifierCascade. If not
+ specified, use a default installed with the package.
+
+ localization_model
+ A flandmark localization model file. If not specified, use a default
+ installed with the package. The default model provides the following
+ keypoints, in this order:
+
+ [0]
+ Face center
+
+ [1]
+ Canthus-rl (inner corner of the right eye). Note: The "right eye" means
+ the right eye at face w.r.t. itself - that is the left eye in the image.
+
+ [2]
+ Canthus-lr (inner corder of the left eye)
+
+ [3]
+ Mouth-corner-r (right corner of the mouth)
+
+ [4]
+ Mouth-corner-l (left corner of the mouth)
+
+ [5]
+ Canthus-rr (outer corner of the right eye)
+
+ [6]
+ Canthus-ll (outer corner of the left eye)
+
+ [7]
+ Nose
+ """
+ super(Localizer, self).__init__(detection_model, localization_model)
+
+ def __call__(self, image):
+ """Localizes facial keypoints on all faces detected at the input image.
+
+ Keyword parameters:
+
+ image
+ Either a gray-scale or colored image where to run the detection and
+ localization.
+
+ Returns a tuple composed of dictionaries. Each dictionary in the list has
+ two entries: ``bbox`` and ``landmark``. The ``bbox`` entry corresponds to
+ the OpenCV cascade face detected, whereas the ``landmark`` contains a list
+ of tuples (representing x,y coordinates) with the landmarks.
+
+ If no faces are detected on the input image, than the returned tuple is
+ empty.
+ """
+
+ if image.ndim == 3:
+ from bob.ip import rgb_to_gray
+ gray = rgb_to_gray(image)
+ return super(Localizer, self).__call__(gray)
+
+ elif image.ndim == 2:
+ return super(Localizer, self).__call__(gray)
+
+ else:
+ raise TypeError, "Localizer accepts images as numpy.ndarray objects with either 2 or 3 dimensions"
diff --git a/flandmark/ext/ext.cpp b/flandmark/ext/ext.cpp
index 2c14351..a768e26 100644
--- a/flandmark/ext/ext.cpp
+++ b/flandmark/ext/ext.cpp
@@ -106,7 +106,7 @@ class Localizer {
// The first point represents the center of the bounding box used by
// the flandmark library.
- for (int i = 2; i < (2*m_flandmark->data.options.M); i += 2) {
+ for (int i = 0; i < (2*m_flandmark->data.options.M); i += 2) {
lmlist.append(make_tuple(m_landmarks[i], m_landmarks[i+1]));
}
det["landmark"] = lmlist;
diff --git a/flandmark/test.py b/flandmark/test.py
index 501958d..81f7840 100644
--- a/flandmark/test.py
+++ b/flandmark/test.py
@@ -30,8 +30,8 @@ class FlandmarkTest(unittest.TestCase):
v = bob.io.VideoReader(INPUT_VIDEO)
- for i, f in enumerate(v):
- self.assertTrue(op(bob.ip.rgb_to_gray(f)))
+ for f in v:
+ self.assertTrue(op(f))
def xtest02_broken(self):
@@ -39,6 +39,5 @@ class FlandmarkTest(unittest.TestCase):
"flandmark/flandmark_model.dat")
for i, f in enumerate(bob.io.VideoReader(INPUT_VIDEO)):
- v = bob.ip.rgb_to_gray(f)
print v
self.assertTrue(op(v))
diff --git a/setup.py b/setup.py
index 55da9ad..c7f9cb9 100644
--- a/setup.py
+++ b/setup.py
@@ -8,7 +8,7 @@
import sys
import subprocess
-from distutils.core import setup
+from setuptools import setup, find_packages
from distutils.extension import Extension
def pkgconfig(package):
@@ -82,8 +82,30 @@ def setup_bob_extension(ext_name, sources):
)
setup(
+
name="flandmark",
version="1.0.6",
+ description="",
+ license="GPLv3",
+ author='Andre Anjos',
+ author_email='andre.anjos@idiap.ch',
+ long_description=open('README.rst').read(),
+
+ packages=find_packages(),
+ include_package_data=True,
+ zip_safe=False,
+
+ install_requires=[
+ 'setuptools',
+ 'bob',
+ ],
+
+ entry_points = {
+ 'console_scripts': [
+ 'annotate.py = flandmark.script.annotate:main',
+ ],
+ },
+
ext_modules=[
setup_bob_extension("flandmark._flandmark",
[
@@ -91,4 +113,15 @@ setup(
"flandmark/ext/liblbp.cpp",
"flandmark/ext/ext.cpp",
])
- ])
+ ],
+
+ classifiers = [
+ 'Development Status :: 4 - Beta',
+ 'Intended Audience :: Developers',
+ 'License :: OSI Approved :: GNU General Public License v3 (GPLv3)',
+ 'Natural Language :: English',
+ 'Programming Language :: Python',
+ 'Topic :: Scientific/Engineering :: Artificial Intelligence',
+ ],
+
+ )
--
GitLab