From 8740b92fc3dd343feb879c7533549c32bcfd19c1 Mon Sep 17 00:00:00 2001
From: Manuel Gunther <siebenkopf@googlemail.com>
Date: Fri, 5 Feb 2016 12:51:23 -0700
Subject: [PATCH] Fixed FaceDetector to also accept color images
---
bob/bio/face/preprocessor/FaceDetect.py | 16 ++++++++++------
doc/implementation.rst | 2 +-
2 files changed, 11 insertions(+), 7 deletions(-)
diff --git a/bob/bio/face/preprocessor/FaceDetect.py b/bob/bio/face/preprocessor/FaceDetect.py
index 3e8422cb..a97cd3ec 100644
--- a/bob/bio/face/preprocessor/FaceDetect.py
+++ b/bob/bio/face/preprocessor/FaceDetect.py
@@ -107,7 +107,7 @@ class FaceDetect (Base):
# get the landmarks in the face
if self.flandmark is not None:
# use the flandmark detector
- uint8_image = image.astype(numpy.uint8)
+
# make the bounding box square shape by extending the horizontal position by 2 pixels times width/20
bb = bob.ip.facedetect.BoundingBox(topleft = (bounding_box.top_f, bounding_box.left_f - bounding_box.size[1] / 10.), size = bounding_box.size)
@@ -115,7 +115,7 @@ class FaceDetect (Base):
left = max(bb.left, 0)
bottom = min(bb.bottom, image.shape[0])
right = min(bb.right, image.shape[1])
- landmarks = self.flandmark.locate(uint8_image, top, left, bottom-top, right-left)
+ landmarks = self.flandmark.locate(image, top, left, bottom-top, right-left)
if landmarks is not None and len(landmarks):
return {
@@ -136,7 +136,7 @@ class FaceDetect (Base):
**Parameters:**
- image : 2D :py:class:`numpy.ndarray`
+ image : 2D or 3D :py:class:`numpy.ndarray`
The face image to be processed.
annotations : any
@@ -144,14 +144,18 @@ class FaceDetect (Base):
**Returns:**
- face : 2D :py:class:`numpy.ndarray` (float)
+ face : 2D or 3D :py:class:`numpy.ndarray` (float)
The detected and cropped face.
"""
+ uint8_image = image.astype(numpy.uint8)
+ if uint8_image.ndim == 3:
+ uint8_image = bob.ip.color.rgb_to_gray(uint8_image)
+
# detect the face
- bounding_box, self.quality = bob.ip.facedetect.detect_single_face(image, self.cascade, self.sampler, self.detection_overlap)
+ bounding_box, self.quality = bob.ip.facedetect.detect_single_face(uint8_image, self.cascade, self.sampler, self.detection_overlap)
# get the eye landmarks
- annotations = self._landmarks(image, bounding_box)
+ annotations = self._landmarks(uint8_image, bounding_box)
# apply face cropping
return self.cropper.crop_face(image, annotations)
diff --git a/doc/implementation.rst b/doc/implementation.rst
index aad0c60f..91d6d4da 100644
--- a/doc/implementation.rst
+++ b/doc/implementation.rst
@@ -81,7 +81,7 @@ Or simply (using the face detector :ref:`Resource <bob.bio.face.preprocessors>`)
.. code-block:: py
- preprocessor = bob.bio.face.preprocessor.TanTriggs(face_cropper = 'face-crop-eyes')
+ preprocessor = bob.bio.face.preprocessor.TanTriggs(face_cropper = 'landmark-detect')
.. _bob.bio.face.resources:
--
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