diff --git a/bob/pad/face/test/test.py b/bob/pad/face/test/test.py
index 799d8efb2b6a0506776dfd07e4b10516b6fd8c83..10043dfa44fa0d9f4a6af5c6fc76edfc88852ace 100644
--- a/bob/pad/face/test/test.py
+++ b/bob/pad/face/test/test.py
@@ -41,11 +41,41 @@ import random
-def test_detect_face_landmarks_in_image():
+def test_detect_face_landmarks_in_image_mtcnn():
+
+ img = load(datafile('testimage.jpg', 'bob.bio.face.test'))
+ assert len(img) == 3
+ annotations = face_detection_utils.detect_face_landmarks_in_image(img, method = 'mtcnn')
+ assert len(annotations['landmarks']) == 68
+ assert len(annotations['left_eye']) == 2
+ assert len(annotations['right_eye']) == 2
+ assert len(annotations['topleft']) == 2
+ assert len(annotations['bottomright']) == 2
+
+ #assert len(annotations['left_eye']) == (176, 220)
+
+
+
+def test_detect_face_landmarks_in_video_mtcnn():
+
+ img = load(datafile('testimage.jpg', 'bob.bio.face.test'))
+ assert len(img) == 3
+ frame_container= bob.bio.video.FrameContainer()
+ frame_container.add(1,img)
+ frame_container.add(2,img)
+
+ annotations = face_detection_utils.detect_face_landmarks_in_video(frame_container, method = 'mtcnn')
+ assert len(annotations) == 2
+ assert len(annotations['1']['landmarks']) == 68
+
+
+
+
+def test_detect_face_landmarks_in_image_dlib():
img = load(datafile('testimage.jpg', 'bob.bio.face.test'))
assert len(img) == 3
- annotations = face_detection_utils.detect_face_landmarks_in_image(img)
+ annotations = face_detection_utils.detect_face_landmarks_in_image(img, method = 'dlib')
assert len(annotations['landmarks']) == 68
assert len(annotations['left_eye']) == 2
assert len(annotations['right_eye']) == 2
@@ -56,7 +86,7 @@ def test_detect_face_landmarks_in_image():
-def test_detect_face_landmarks_in_video():
+def test_detect_face_landmarks_in_video_dlib():
img = load(datafile('testimage.jpg', 'bob.bio.face.test'))
assert len(img) == 3
@@ -64,7 +94,7 @@ def test_detect_face_landmarks_in_video():
frame_container.add(1,img)
frame_container.add(2,img)
- annotations = face_detection_utils.detect_face_landmarks_in_video(frame_container)
+ annotations = face_detection_utils.detect_face_landmarks_in_video(frame_container, method = 'dlib')
assert len(annotations) == 2
assert len(annotations['1']['landmarks']) == 68
diff --git a/bob/pad/face/utils/face_detection_utils.py b/bob/pad/face/utils/face_detection_utils.py
index 0ba1f2308344618aaba65a889722d90acc2731ed..7b01c4c26a3d767f4554655c9c092521e7102450 100644
--- a/bob/pad/face/utils/face_detection_utils.py
+++ b/bob/pad/face/utils/face_detection_utils.py
@@ -11,6 +11,43 @@ import importlib
import numpy as np
+
+def getEyePos(lm):
+
+ """
+ This function returns the locations of left and right eyes
+
+ **Parameters:**
+
+ ``lm`` : :py:class:`array`
+ A numpy array containing the coordinates of facial landmarks, (68X2)
+
+
+ **Returns:**
+
+ ``right_eye``
+ A tuple containing the location of right eye,
+
+ ``left_eye``
+ A tuple containing the location of left eye
+
+ """
+
+ # Mean position of eye corners as eye centers , casted to int()
+
+ left_eye_t = (lm[36,:] + lm[39,:])/2.0
+ right_eye_t = (lm[42,:] + lm[45,:])/2.0
+
+ right_eye = (int(left_eye_t[1]),int(left_eye_t[0]))
+ left_eye = (int(right_eye_t[1]),int(right_eye_t[0]))
+
+ return right_eye,left_eye
+
+
+
+
+
+
#==============================================================================
def detect_face_in_image(image, method = "dlib"):
"""
@@ -99,100 +136,113 @@ def detect_faces_in_video(frame_container, method = "dlib"):
return annotations
-def getEyePos(lm):
+
+def detect_face_landmarks_in_image(image, method = "dlib"):
"""
- This function returns the locations of left and right eyes
+ This function detects a face in the input image. Two oprions for face detector , but landmark detector is always the same
**Parameters:**
- ``lm`` : :py:class:`array`
- A numpy array containing the coordinates of facial landmarks, (68X2)
+ ``image`` : 3D :py:class:`numpy.ndarray`
+ A color image to detect the face in.
+ ``method`` : :py:class:`str`
+ A package to be used for face detection. Options supported by this
+ package: "dlib" (dlib is a dependency of this package). If bob.ip.mtcnn
+ is installed in your system you can use it as-well (bob.ip.mtcnn is NOT
+ a dependency of this package).
**Returns:**
- ``right_eye``
- A tuple containing the location of right eye,
+ ``annotations`` : :py:class:`dict`
+ A dictionary containing annotations of the face bounding box, eye locations and facial landmarks.
+ Dictionary must be as follows ``{'topleft': (row, col), 'bottomright': (row, col), 'left_eye': (row, col), 'right_eye': (row, col), 'landmarks': [(col1,row1), (col2,row2), ...]}``.
+ If no annotations found an empty dictionary is returned.
+ Where (rowK,colK) is the location of Kth facial landmark (K=0,...,67).
+ """
- ``left_eye``
- A tuple containing the location of left eye
+ ### Face detector
- """
+ try:
+ face_detection_module = importlib.import_module("bob.ip."+ method)
- # Mean position of eye corners as eye centers , casted to int()
+ except ImportError:
- left_eye_t = (lm[36,:] + lm[39,:])/2.0
- right_eye_t = (lm[42,:] + lm[45,:])/2.0
+ print("No module named bob.ip." + method + " trying to use default method!")
- right_eye = (int(left_eye_t[1]),int(left_eye_t[0]))
- left_eye = (int(right_eye_t[1]),int(right_eye_t[0]))
+ try:
+ face_detection_module = importlib.import_module("bob.ip.dlib")
+ method = "dlib"
+ except ImportError:
+ raise ImportError("No module named bob.ip.dlib")
+
+
+ if not hasattr(face_detection_module, 'FaceDetector'):
+ raise AttributeError("bob.ip." + method + " module has no attribute FaceDetector!")
+
+
+ #### Landmark detector
+
+ try:
+ landmark_detection_module = importlib.import_module("bob.ip.facelandmarks")
+ except ImportError:
+ raise ImportError("No module named bob.ip.facelandmarks!!")
+
+ if not hasattr(landmark_detection_module, 'detect_landmarks_on_boundingbox'):
+ raise AttributeError("bob.ip.facelandmarksmodule has no attribute detect_landmarks_on_boundingbox!")
+
+
+ face_detector = face_detection_module.FaceDetector()
- return right_eye,left_eye
+ data = face_detector.detect_single_face(image)
-def detect_face_landmarks_in_image(image, method = "dlib"):
- """
- This function detects a face and facial landmarks in the input image.
+ annotations = {}
- **Parameters:**
+ if ( data is not None ) and ( not all([x is None for x in data]) ):
- ``image`` : 3D :py:class:`numpy.ndarray`
- A color image to detect the face in.
+ bounding_box = data[0]
- ``method`` : :py:class:`str`
- A package to be used for face detection. Options supported by this
- package: "dlib" (dlib is a dependency of this package).
+ #bounding_box = bounding_box.scale(0.9, True)
- **Returns:**
+ lm=landmark_detection_module.detect_landmarks_on_boundingbox(image, bounding_box)
- ``annotations`` : :py:class:`dict`
- A dictionary containing the annotations for an image.
- Dictionary must be as follows ``{'topleft': (row, col), 'bottomright': (row, col), 'left_eye': (row, col), 'right_eye': (row, col), 'landmarks': [(row1,col1), (row2,col2), ...]}``
- Where (rowK,colK) is the location of Kth facial landmark (K=0,...,67).
- If no annotations found an empty dictionary is returned.
- """
+ if lm is not None:
- try:
- face_landmark_detection_module = importlib.import_module("bob.ip.facelandmarks");
- except ImportError:
- raise ImportError("No module named bob.ip.facelandmarks")
+ lm=np.array(lm)
- if not hasattr(face_landmark_detection_module, 'detect_landmarks'):
- raise AttributeError("bob.ip.facelandmarks module has no attribute detect_landmarks")
+ lm=np.vstack((lm[:,1],lm[:,0])).T
- key_points = face_landmark_detection_module.detect_landmarks(image, 1);
+ #print("LM",lm)
- annotations = {}
+ right_eye,left_eye = getEyePos(lm)
- try:
- kp = key_points[0]
- except:
- kp = None
- if kp is not None:
+ points = []
+
+ for i in range(lm.shape[0]):
+
+ points.append((int(lm[i,0]),int(lm[i,1])))
- lm = np.vstack((kp.landmarks[:,1],kp.landmarks[:,0])).T
+ annotations['topleft'] = bounding_box.topleft
- right_eye,left_eye = getEyePos(lm)
+ annotations['bottomright'] = bounding_box.bottomright
- points = []
+ annotations['landmarks'] = points
- for i in range(lm.shape[0]):
- points.append((int(lm[i,0]),int(lm[i,1])))
+ annotations['left_eye'] = left_eye
- annotations['topleft'] = kp.bounding_box.topleft
- annotations['bottomright'] = kp.bounding_box.bottomright
- annotations['landmarks'] = points # list of landmarks
- annotations['left_eye'] = left_eye
- annotations['right_eye'] = right_eye
+ annotations['right_eye'] = right_eye
return annotations
+
+
def detect_face_landmarks_in_video(frame_container, method = "dlib"):
"""
This function detects a face and face landmarks in each farme of the input video.
@@ -204,16 +254,17 @@ def detect_face_landmarks_in_video(frame_container, method = "dlib"):
``method`` : :py:class:`str`
A package to be used for face detection. Options supported by this
- package: "dlib" (dlib is a dependency of this package).
+ package: "dlib" (dlib is a dependency of this package) and "mtcnn".
+ If its found it will be used else defaults to "dlib"
**Returns:**
``annotations`` : :py:class:`dict`
A dictionary containing the annotations for each frame in the video.
Dictionary structure: ``annotations = {'1': frame1_dict, '2': frame1_dict, ...}``.
- Where ``frameN_dict = {'topleft': (row, col), 'bottomright': (row, col), 'left_eye': (row, col), 'right_eye': (row, col), 'landmarks': [(row1,col1), (row2,col2), ...]}``
+ Where ``frameN_dict = {'topleft': (row, col), 'bottomright': (row, col), 'left_eye': (row, col), 'right_eye': (row, col), 'landmarks': [(col1,row1), (col2,row2), ...]}``
is the dictionary defining the coordinates of the face bounding box in frame N.
- Where (rowK,colK) is the location of Kth facial landmark (K=0,...,67).
+ Where (colK,rowK) is the location of Kth facial landmark (K=0,...,67).
If no annotations found an empty dictionary is returned.
"""