From 45c1e69668f7d46d24bd7d873372ca95f90a5d9f Mon Sep 17 00:00:00 2001
From: Amir Mohammadi <183.amir@gmail.com>
Date: Mon, 26 Dec 2016 13:23:58 +0100
Subject: [PATCH] [doc] improve example using bob.ip.facedetect
---
doc/guide.rst | 9 ++++++---
doc/plot/show_lena.py | 19 +++++++++++++------
2 files changed, 19 insertions(+), 9 deletions(-)
diff --git a/doc/guide.rst b/doc/guide.rst
index 950d43b..ac88b86 100644
--- a/doc/guide.rst
+++ b/doc/guide.rst
@@ -9,9 +9,9 @@
from pkg_resources import resource_filename
return resource_filename('bob.ip.flandmark', join('data', f))
-=============
- Users Guide
-=============
+==============================================
+ Face Landmark Detection Using Python and Bob
+==============================================
:py:class:`bob.ip.flandmark` detects 8 coordinates of important keypoints in **frontal** human faces.
To properly work, the keypoint localizer requires the input of an image (of type ``uint8``, gray-scaled) and of a bounding box describing a rectangle where the face is supposed to be located in the image (see :py:meth:`bob.ip.flandmark.Flandmark.locate`).
@@ -64,8 +64,11 @@ The code below shall detect most frontal faces in a provided image:
>>> import bob.ip.facedetect
>>> lena = bob.io.base.load(get_file('lena.jpg'))
>>> bounding_box, quality = bob.ip.facedetect.detect_single_face(lena)
+ >>> # scale the bounding box to cover more of the face
+ >>> bounding_box = bounding_box.scale(1.2, True)
>>> y, x = bounding_box.topleft
>>> height, width = bounding_box.size
+ >>> width = height # make it square
>>> print((y, x, height, width))
(...)
diff --git a/doc/plot/show_lena.py b/doc/plot/show_lena.py
index eae7670..a34ca56 100644
--- a/doc/plot/show_lena.py
+++ b/doc/plot/show_lena.py
@@ -1,24 +1,31 @@
-from matplotlib import pyplot
from bob.ip.flandmark import Flandmark
from bob.ip.draw import box, cross
from bob.ip.color import rgb_to_gray
+from bob.ip.facedetect import detect_single_face
+import bob.io.image
+
def get_data(f):
from os.path import join
from pkg_resources import resource_filename
from bob.io.base import load
- import bob.io.image
return load(resource_filename('bob.ip.flandmark', join('data', f)))
+
lena = get_data('lena.jpg')
lena_gray = rgb_to_gray(lena)
-x, y, width, height = [214, 202, 183, 183] #or from bob.ip.facedetect
+bounding_box, quality = detect_single_face(lena)
+bounding_box = bounding_box.scale(1.2, True)
+y, x = bounding_box.topleft
+height, width = bounding_box.size
+width = height
+# x, y, width, height = [214, 202, 183, 183] # Manual annotations
localizer = Flandmark()
keypoints = localizer.locate(lena_gray, y, x, height, width)
# draw the keypoints and bounding box
-box(lena, (y, x), (height, width), (255, 0, 0)) # red bounding box
+box(lena, (y, x), (height, width), (255, 0, 0)) # red bounding box
for k in keypoints:
- cross(lena, k.astype(int), 5, (255, 255, 0)) # yellow key points
+ cross(lena, k.astype(int), 5, (255, 255, 0)) # yellow key points
-pyplot.imshow(lena.transpose(1, 2, 0))
+bob.io.image.imshow(lena)
--
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