diff --git a/bob/pad/face/config/grid.py b/bob/pad/face/config/grid.py
index 12d4c4059b0ced23327c5c6cbaa7a36cb06d13eb..8d3061f5af05847dcc2bddaedf21fac4a6298810 100644
--- a/bob/pad/face/config/grid.py
+++ b/bob/pad/face/config/grid.py
@@ -5,22 +5,22 @@ from bob.bio.base.grid import Grid
# Configuration to run on computation cluster:
idiap = Grid(
- training_queue='32G',
+ training_queue='8G-io-big',
number_of_preprocessing_jobs=32,
preprocessing_queue='4G-io-big',
number_of_extraction_jobs=32,
- extraction_queue='8G-io-big',
+ extraction_queue='4G-io-big',
number_of_projection_jobs=32,
- projection_queue='8G-io-big',
+ projection_queue='4G-io-big',
number_of_enrollment_jobs=32,
- enrollment_queue='8G-io-big',
+ enrollment_queue='4G-io-big',
number_of_scoring_jobs=1,
- scoring_queue='8G-io-big',
+ scoring_queue='4G-io-big',
)
# Configuration to run on user machines:
diff --git a/bob/pad/face/config/preprocessor/video_face_crop.py b/bob/pad/face/config/preprocessor/video_face_crop.py
index ad7f963b0fdb8f92319c02ad8210c899a44dbccc..72156454a24fed51f8bce0102511f49d5e3f2175 100644
--- a/bob/pad/face/config/preprocessor/video_face_crop.py
+++ b/bob/pad/face/config/preprocessor/video_face_crop.py
@@ -17,15 +17,50 @@ MIN_FACE_SIZE = 50
USE_LOCAL_CROPPER_FLAG = True # Use the local face cropping class (identical to Ivana's paper)
RGB_OUTPUT_FLAG = True # Return RGB cropped face using local cropper
DETECT_FACES_FLAG = True # find annotations locally replacing the database annotations
+FACE_DETECTION_METHOD = "dlib"
+
+rgb_face_detector_dlib = VideoFaceCrop(cropped_image_size = CROPPED_IMAGE_SIZE,
+ cropped_positions = CROPPED_POSITIONS,
+ fixed_positions = FIXED_POSITIONS,
+ mask_sigma = MASK_SIGMA,
+ mask_neighbors = MASK_NEIGHBORS,
+ mask_seed = None,
+ check_face_size_flag = CHECK_FACE_SIZE_FLAG,
+ min_face_size = MIN_FACE_SIZE,
+ use_local_cropper_flag = USE_LOCAL_CROPPER_FLAG,
+ rgb_output_flag = RGB_OUTPUT_FLAG,
+ detect_faces_flag = DETECT_FACES_FLAG,
+ face_detection_method = FACE_DETECTION_METHOD)
+
+
+CROPPED_IMAGE_SIZE = (64, 64) # The size of the resulting face
+CROPPED_POSITIONS = {'topleft' : (0,0) , 'bottomright' : CROPPED_IMAGE_SIZE}
+FIXED_POSITIONS = None
+MASK_SIGMA = None # The sigma for random values areas outside image
+MASK_NEIGHBORS = 5 # The number of neighbors to consider while extrapolating
+MASK_SEED = None # The seed for generating random values during extrapolation
+CHECK_FACE_SIZE_FLAG = True # Check the size of the face
+MIN_FACE_SIZE = 50
+USE_LOCAL_CROPPER_FLAG = True # Use the local face cropping class (identical to Ivana's paper)
+RGB_OUTPUT_FLAG = True # Return RGB cropped face using local cropper
+DETECT_FACES_FLAG = True # find annotations locally replacing the database annotations
+FACE_DETECTION_METHOD = "mtcnn"
+
+rgb_face_detector_mtcnn = VideoFaceCrop(cropped_image_size = CROPPED_IMAGE_SIZE,
+ cropped_positions = CROPPED_POSITIONS,
+ fixed_positions = FIXED_POSITIONS,
+ mask_sigma = MASK_SIGMA,
+ mask_neighbors = MASK_NEIGHBORS,
+ mask_seed = None,
+ check_face_size_flag = CHECK_FACE_SIZE_FLAG,
+ min_face_size = MIN_FACE_SIZE,
+ use_local_cropper_flag = USE_LOCAL_CROPPER_FLAG,
+ rgb_output_flag = RGB_OUTPUT_FLAG,
+ detect_faces_flag = DETECT_FACES_FLAG,
+ face_detection_method = FACE_DETECTION_METHOD)
+
+
+
+
+
-preprocessor_rgb_face_detect = VideoFaceCrop(cropped_image_size = CROPPED_IMAGE_SIZE,
- cropped_positions = CROPPED_POSITIONS,
- fixed_positions = FIXED_POSITIONS,
- mask_sigma = MASK_SIGMA,
- mask_neighbors = MASK_NEIGHBORS,
- mask_seed = None,
- check_face_size_flag = CHECK_FACE_SIZE_FLAG,
- min_face_size = MIN_FACE_SIZE,
- use_local_cropper_flag = USE_LOCAL_CROPPER_FLAG,
- rgb_output_flag = RGB_OUTPUT_FLAG,
- detect_faces_flag = DETECT_FACES_FLAG)
diff --git a/bob/pad/face/preprocessor/VideoFaceCrop.py b/bob/pad/face/preprocessor/VideoFaceCrop.py
index 97024f8daa0b7f282206025b4e7643020f24bdb1..a335fc1cbff908a815dd311f95f557a2655ed7a9 100644
--- a/bob/pad/face/preprocessor/VideoFaceCrop.py
+++ b/bob/pad/face/preprocessor/VideoFaceCrop.py
@@ -84,6 +84,12 @@ class VideoFaceCrop(Preprocessor, object):
cropping.
Default: ``False``.
+ ``face_detection_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).
+
``kwargs``
Remaining keyword parameters passed to the Base constructor, such as ``color_channel`` or ``dtype``.
"""
@@ -101,6 +107,7 @@ class VideoFaceCrop(Preprocessor, object):
use_local_cropper_flag = False,
rgb_output_flag = False,
detect_faces_flag = False,
+ face_detection_method = "dlib",
**kwargs):
super(VideoFaceCrop, self).__init__(cropped_image_size = cropped_image_size,
@@ -114,6 +121,7 @@ class VideoFaceCrop(Preprocessor, object):
use_local_cropper_flag = use_local_cropper_flag,
rgb_output_flag = rgb_output_flag,
detect_faces_flag = detect_faces_flag,
+ face_detection_method = face_detection_method,
**kwargs)
self.cropped_image_size = cropped_image_size
@@ -127,6 +135,7 @@ class VideoFaceCrop(Preprocessor, object):
self.use_local_cropper_flag = use_local_cropper_flag
self.rgb_output_flag = rgb_output_flag
self.detect_faces_flag = detect_faces_flag
+ self.face_detection_method = face_detection_method
# Save also the data stored in the kwargs:
for (k, v) in kwargs.items():
@@ -276,7 +285,7 @@ class VideoFaceCrop(Preprocessor, object):
if self.detect_faces_flag:
- annotations = detect_faces_in_video(frames)
+ annotations = detect_faces_in_video(frames, self.face_detection_method)
if len(frames) != len(annotations): # if some annotations are missing
@@ -307,7 +316,9 @@ class VideoFaceCrop(Preprocessor, object):
name of the file.
"""
- self.video_preprocessor.write_data(frames, file_name)
+ if frames: # save file if FrameContainer is not empty, otherwise do nothing.
+
+ self.video_preprocessor.write_data(frames, file_name)
#==========================================================================
diff --git a/bob/pad/face/test/test.py b/bob/pad/face/test/test.py
index f97f8218565a25ccbb9771a426cf60f8f26381a0..ac1078e42c5fb5509af2a2ea0d7a124bb6a3afeb 100644
--- a/bob/pad/face/test/test.py
+++ b/bob/pad/face/test/test.py
@@ -167,6 +167,7 @@ def test_video_face_crop():
USE_LOCAL_CROPPER_FLAG = True # Use the local face cropping class (identical to Ivana's paper)
RGB_OUTPUT_FLAG = True # Return RGB cropped face using local cropper
DETECT_FACES_FLAG = True # find annotations locally replacing the database annotations
+ FACE_DETECTION_METHOD = "dlib"
preprocessor = VideoFaceCrop(cropped_image_size = CROPPED_IMAGE_SIZE,
cropped_positions = CROPPED_POSITIONS,
@@ -178,7 +179,8 @@ def test_video_face_crop():
min_face_size = MIN_FACE_SIZE,
use_local_cropper_flag = USE_LOCAL_CROPPER_FLAG,
rgb_output_flag = RGB_OUTPUT_FLAG,
- detect_faces_flag = DETECT_FACES_FLAG)
+ detect_faces_flag = DETECT_FACES_FLAG,
+ face_detection_method = FACE_DETECTION_METHOD)
video, _ = convert_image_to_video_data(image, annotations, 3)
diff --git a/bob/pad/face/utils/face_detection_utils.py b/bob/pad/face/utils/face_detection_utils.py
index 2214958d80a15c7730517b5a82b49d52ab4a0abe..66b16de7dbdf996f5b26a6addb3da08667894f44 100644
--- a/bob/pad/face/utils/face_detection_utils.py
+++ b/bob/pad/face/utils/face_detection_utils.py
@@ -7,11 +7,11 @@ This file contains face detection utils.
#==============================================================================
# Import here:
-import bob.ip.dlib # for face detection functionality
+import importlib
#==============================================================================
-def detect_face_in_image(image):
+def detect_face_in_image(image, method = "dlib"):
"""
This function detects a face in the input image.
@@ -20,34 +20,45 @@ def detect_face_in_image(image):
``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:**
``annotations`` : :py:class:`dict`
A dictionary containing annotations of the face bounding box.
Dictionary must be as follows ``{'topleft': (row, col), 'bottomright': (row, col)}``.
+ If no annotations found an empty dictionary is returned.
"""
- bounding_box, _ = bob.ip.dlib.FaceDetector().detect_single_face(image)
+ try:
+ face_detection_module = importlib.import_module("bob.ip." + method)
+ except ImportError:
+ raise ImportError("No module named bob.ip." + method)
- annotations = {}
+ if not hasattr(face_detection_module, 'FaceDetector'):
+ raise AttributeError("bob.ip." + method + " module has no attribute FaceDetector")
- if bounding_box is not None:
+ data = face_detection_module.FaceDetector().detect_single_face(image)
- annotations['topleft'] = bounding_box.topleft
+ annotations = {}
- annotations['bottomright'] = bounding_box.bottomright
+ if ( data is not None ) and ( not all([x is None for x in data]) ):
- else:
+ bounding_box = data[0]
- annotations['topleft'] = (0, 0)
+ annotations['topleft'] = bounding_box.topleft
- annotations['bottomright'] = (0, 0)
+ annotations['bottomright'] = bounding_box.bottomright
return annotations
#==============================================================================
-def detect_faces_in_video(frame_container):
+def detect_faces_in_video(frame_container, method = "dlib"):
"""
This function detects a face in each farme of the input video.
@@ -56,6 +67,12 @@ def detect_faces_in_video(frame_container):
``frame_container`` : FrameContainer
FrameContainer containing the frames data.
+ ``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:**
``annotations`` : :py:class:`dict`
@@ -63,6 +80,7 @@ def detect_faces_in_video(frame_container):
Dictionary structure: ``annotations = {'1': frame1_dict, '2': frame1_dict, ...}``.
Where ``frameN_dict = {'topleft': (row, col), 'bottomright': (row, col)}``
is the dictionary defining the coordinates of the face bounding box in frame N.
+ If no annotations found an empty dictionary is returned.
"""
annotations = {}
@@ -71,9 +89,11 @@ def detect_faces_in_video(frame_container):
image = frame[1]
- frame_annotations = detect_face_in_image(image)
+ frame_annotations = detect_face_in_image(image, method)
+
+ if frame_annotations:
- annotations[str(idx)] = frame_annotations
+ annotations[str(idx)] = frame_annotations
return annotations
diff --git a/develop.cfg b/develop.cfg
index f8617f19c93663008158d1b270e9c09b0cdd219a..ddc5fe3db1435ffa3c41f4c9b1d35bda929ac6ff 100644
--- a/develop.cfg
+++ b/develop.cfg
@@ -22,6 +22,7 @@ eggs = bob.pad.face
bob.learn.activation
bob.ip.flandmark
bob.ip.facedetect
+ bob.ip.dlib
bob.ip.qualitymeasure
bob.learn.linear
bob.db.base
@@ -56,6 +57,7 @@ develop = src/bob.extension
src/bob.learn.activation
src/bob.ip.flandmark
src/bob.ip.facedetect
+ src/bob.ip.dlib
src/bob.ip.qualitymeasure
src/bob.learn.linear
src/bob.db.base
@@ -92,6 +94,7 @@ bob.io.matlab = git git@gitlab.idiap.ch:bob/bob.io.matlab
bob.learn.activation = git git@gitlab.idiap.ch:bob/bob.learn.activation
bob.ip.flandmark = git git@gitlab.idiap.ch:bob/bob.ip.flandmark
bob.ip.facedetect = git git@gitlab.idiap.ch:bob/bob.ip.facedetect
+bob.ip.dlib = git git@gitlab.idiap.ch:bob/bob.ip.dlib
bob.ip.qualitymeasure = git git@gitlab.idiap.ch:bob/bob.ip.qualitymeasure
bob.learn.linear = git git@gitlab.idiap.ch:bob/bob.learn.linear
bob.db.base = git git@gitlab.idiap.ch:bob/bob.db.base
diff --git a/setup.py b/setup.py
index 0a0578e9d4355fcdc12bd181768fb43c0c237ffe..5994338a00da26f58f9e9dc5cafaca19978ba57e 100644
--- a/setup.py
+++ b/setup.py
@@ -103,7 +103,8 @@ setup(
# registered preprocessors:
'bob.pad.preprocessor': [
'empty-preprocessor = bob.pad.face.config.preprocessor.filename:empty_preprocessor', # no preprocessing
- 'preprocessor-rgb-face-detect = bob.pad.face.config.preprocessor.video_face_crop:preprocessor_rgb_face_detect', # detect faces locally replacing database annotations
+ 'rgb-face-detect-dlib = bob.pad.face.config.preprocessor.video_face_crop:rgb_face_detector_dlib', # detect faces locally replacing database annotations
+ 'rgb-face-detect-mtcnn = bob.pad.face.config.preprocessor.video_face_crop:rgb_face_detector_mtcnn', # detect faces locally replacing database annotations
],
# registered extractors: