From e236cac643e458b1b871ec84328dcaab12a44edc Mon Sep 17 00:00:00 2001
From: Olegs NIKISINS <onikisins@italix03.idiap.ch>
Date: Mon, 5 Mar 2018 15:54:54 +0100
Subject: [PATCH] Added underscore to preproc configs to resolve warning when
running baselines
---
bob/pad/face/config/lbp_svm.py | 4 +--
bob/pad/face/config/lbp_svm_aggregated_db.py | 4 +--
.../config/preprocessor/video_face_crop.py | 28 +++++++++----------
bob/pad/face/config/qm_lr.py | 4 +--
bob/pad/face/config/qm_one_class_gmm.py | 4 +--
.../config/qm_one_class_svm_aggregated_db.py | 4 +--
.../qm_one_class_svm_cascade_aggregated_db.py | 4 +--
bob/pad/face/config/qm_svm.py | 4 +--
bob/pad/face/config/qm_svm_aggregated_db.py | 4 +--
9 files changed, 30 insertions(+), 30 deletions(-)
diff --git a/bob/pad/face/config/lbp_svm.py b/bob/pad/face/config/lbp_svm.py
index f5eba528..c57ed630 100644
--- a/bob/pad/face/config/lbp_svm.py
+++ b/bob/pad/face/config/lbp_svm.py
@@ -31,14 +31,14 @@ MAX_IMAGE_SIZE = None # no limiting here
FACE_DETECTION_METHOD = None # use annotations
MIN_FACE_SIZE = 50 # skip small faces
-image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
+_image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
rgb_output_flag = RGB_OUTPUT_FLAG,
use_face_alignment = USE_FACE_ALIGNMENT,
max_image_size = MAX_IMAGE_SIZE,
face_detection_method = FACE_DETECTION_METHOD,
min_face_size = MIN_FACE_SIZE)
-preprocessor = Wrapper(image_preprocessor)
+preprocessor = Wrapper(_image_preprocessor)
"""
In the preprocessing stage the face is cropped in each frame of the input video given facial annotations.
The size of the face is normalized to ``FACE_SIZE`` dimensions. The faces with the size
diff --git a/bob/pad/face/config/lbp_svm_aggregated_db.py b/bob/pad/face/config/lbp_svm_aggregated_db.py
index fb84bd47..812bf4a9 100644
--- a/bob/pad/face/config/lbp_svm_aggregated_db.py
+++ b/bob/pad/face/config/lbp_svm_aggregated_db.py
@@ -33,14 +33,14 @@ MAX_IMAGE_SIZE = None # no limiting here
FACE_DETECTION_METHOD = None # use annotations
MIN_FACE_SIZE = 50 # skip small faces
-image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
+_image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
rgb_output_flag = RGB_OUTPUT_FLAG,
use_face_alignment = USE_FACE_ALIGNMENT,
max_image_size = MAX_IMAGE_SIZE,
face_detection_method = FACE_DETECTION_METHOD,
min_face_size = MIN_FACE_SIZE)
-preprocessor = Wrapper(image_preprocessor)
+preprocessor = Wrapper(_image_preprocessor)
"""
In the preprocessing stage the face is cropped in each frame of the input video given facial annotations.
The size of the face is normalized to ``FACE_SIZE`` dimensions. The faces with the size
diff --git a/bob/pad/face/config/preprocessor/video_face_crop.py b/bob/pad/face/config/preprocessor/video_face_crop.py
index 57bb5901..e8aa571b 100644
--- a/bob/pad/face/config/preprocessor/video_face_crop.py
+++ b/bob/pad/face/config/preprocessor/video_face_crop.py
@@ -16,23 +16,23 @@ MAX_IMAGE_SIZE = None # no limiting here
FACE_DETECTION_METHOD = "dlib" # use dlib face detection
MIN_FACE_SIZE = 50 # skip small faces
-image_preprocessor = FaceCropAlign(face_size=FACE_SIZE,
- rgb_output_flag=RGB_OUTPUT_FLAG,
- use_face_alignment=USE_FACE_ALIGNMENT,
- max_image_size=MAX_IMAGE_SIZE,
- face_detection_method=FACE_DETECTION_METHOD,
- min_face_size=MIN_FACE_SIZE)
+_image_preprocessor = FaceCropAlign(face_size=FACE_SIZE,
+ rgb_output_flag=RGB_OUTPUT_FLAG,
+ use_face_alignment=USE_FACE_ALIGNMENT,
+ max_image_size=MAX_IMAGE_SIZE,
+ face_detection_method=FACE_DETECTION_METHOD,
+ min_face_size=MIN_FACE_SIZE)
-rgb_face_detector_dlib = Wrapper(image_preprocessor)
+rgb_face_detector_dlib = Wrapper(_image_preprocessor)
# =======================================================================================
FACE_DETECTION_METHOD = "mtcnn" # use mtcnn face detection
-image_preprocessor = FaceCropAlign(face_size=FACE_SIZE,
- rgb_output_flag=RGB_OUTPUT_FLAG,
- use_face_alignment=USE_FACE_ALIGNMENT,
- max_image_size=MAX_IMAGE_SIZE,
- face_detection_method=FACE_DETECTION_METHOD,
- min_face_size=MIN_FACE_SIZE)
+_image_preprocessor = FaceCropAlign(face_size=FACE_SIZE,
+ rgb_output_flag=RGB_OUTPUT_FLAG,
+ use_face_alignment=USE_FACE_ALIGNMENT,
+ max_image_size=MAX_IMAGE_SIZE,
+ face_detection_method=FACE_DETECTION_METHOD,
+ min_face_size=MIN_FACE_SIZE)
-rgb_face_detector_mtcnn = Wrapper(image_preprocessor)
+rgb_face_detector_mtcnn = Wrapper(_image_preprocessor)
diff --git a/bob/pad/face/config/qm_lr.py b/bob/pad/face/config/qm_lr.py
index 1e7522c0..0ae7eb31 100644
--- a/bob/pad/face/config/qm_lr.py
+++ b/bob/pad/face/config/qm_lr.py
@@ -30,14 +30,14 @@ MAX_IMAGE_SIZE = None # no limiting here
FACE_DETECTION_METHOD = None # use annotations
MIN_FACE_SIZE = 50 # skip small faces
-image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
+_image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
rgb_output_flag = RGB_OUTPUT_FLAG,
use_face_alignment = USE_FACE_ALIGNMENT,
max_image_size = MAX_IMAGE_SIZE,
face_detection_method = FACE_DETECTION_METHOD,
min_face_size = MIN_FACE_SIZE)
-preprocessor = Wrapper(image_preprocessor)
+preprocessor = Wrapper(_image_preprocessor)
"""
In the preprocessing stage the face is cropped in each frame of the input video given facial annotations.
The size of the face is normalized to ``FACE_SIZE`` dimensions. The faces of the size
diff --git a/bob/pad/face/config/qm_one_class_gmm.py b/bob/pad/face/config/qm_one_class_gmm.py
index 52d99739..15582c19 100644
--- a/bob/pad/face/config/qm_one_class_gmm.py
+++ b/bob/pad/face/config/qm_one_class_gmm.py
@@ -30,14 +30,14 @@ MAX_IMAGE_SIZE = None # no limiting here
FACE_DETECTION_METHOD = None # use annotations
MIN_FACE_SIZE = 50 # skip small faces
-image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
+_image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
rgb_output_flag = RGB_OUTPUT_FLAG,
use_face_alignment = USE_FACE_ALIGNMENT,
max_image_size = MAX_IMAGE_SIZE,
face_detection_method = FACE_DETECTION_METHOD,
min_face_size = MIN_FACE_SIZE)
-preprocessor = Wrapper(image_preprocessor)
+preprocessor = Wrapper(_image_preprocessor)
"""
In the preprocessing stage the face is cropped in each frame of the input video given facial annotations.
The size of the face is normalized to ``FACE_SIZE`` dimensions. The faces of the size
diff --git a/bob/pad/face/config/qm_one_class_svm_aggregated_db.py b/bob/pad/face/config/qm_one_class_svm_aggregated_db.py
index 1951849d..e30161c1 100644
--- a/bob/pad/face/config/qm_one_class_svm_aggregated_db.py
+++ b/bob/pad/face/config/qm_one_class_svm_aggregated_db.py
@@ -32,14 +32,14 @@ MAX_IMAGE_SIZE = None # no limiting here
FACE_DETECTION_METHOD = None # use annotations
MIN_FACE_SIZE = 50 # skip small faces
-image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
+_image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
rgb_output_flag = RGB_OUTPUT_FLAG,
use_face_alignment = USE_FACE_ALIGNMENT,
max_image_size = MAX_IMAGE_SIZE,
face_detection_method = FACE_DETECTION_METHOD,
min_face_size = MIN_FACE_SIZE)
-preprocessor = Wrapper(image_preprocessor)
+preprocessor = Wrapper(_image_preprocessor)
"""
In the preprocessing stage the face is cropped in each frame of the input video given facial annotations.
The size of the face is normalized to ``FACE_SIZE`` dimensions. The faces of the size
diff --git a/bob/pad/face/config/qm_one_class_svm_cascade_aggregated_db.py b/bob/pad/face/config/qm_one_class_svm_cascade_aggregated_db.py
index 01679f83..4c43a6e6 100644
--- a/bob/pad/face/config/qm_one_class_svm_cascade_aggregated_db.py
+++ b/bob/pad/face/config/qm_one_class_svm_cascade_aggregated_db.py
@@ -32,14 +32,14 @@ MAX_IMAGE_SIZE = None # no limiting here
FACE_DETECTION_METHOD = None # use annotations
MIN_FACE_SIZE = 50 # skip small faces
-image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
+_image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
rgb_output_flag = RGB_OUTPUT_FLAG,
use_face_alignment = USE_FACE_ALIGNMENT,
max_image_size = MAX_IMAGE_SIZE,
face_detection_method = FACE_DETECTION_METHOD,
min_face_size = MIN_FACE_SIZE)
-preprocessor = Wrapper(image_preprocessor)
+preprocessor = Wrapper(_image_preprocessor)
"""
In the preprocessing stage the face is cropped in each frame of the input video given facial annotations.
The size of the face is normalized to ``FACE_SIZE`` dimensions. The faces of the size
diff --git a/bob/pad/face/config/qm_svm.py b/bob/pad/face/config/qm_svm.py
index 8e742ff2..422115b2 100644
--- a/bob/pad/face/config/qm_svm.py
+++ b/bob/pad/face/config/qm_svm.py
@@ -30,14 +30,14 @@ MAX_IMAGE_SIZE = None # no limiting here
FACE_DETECTION_METHOD = None # use annotations
MIN_FACE_SIZE = 50 # skip small faces
-image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
+_image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
rgb_output_flag = RGB_OUTPUT_FLAG,
use_face_alignment = USE_FACE_ALIGNMENT,
max_image_size = MAX_IMAGE_SIZE,
face_detection_method = FACE_DETECTION_METHOD,
min_face_size = MIN_FACE_SIZE)
-preprocessor = Wrapper(image_preprocessor)
+preprocessor = Wrapper(_image_preprocessor)
"""
In the preprocessing stage the face is cropped in each frame of the input video given facial annotations.
The size of the face is normalized to ``FACE_SIZE`` dimensions. The faces of the size
diff --git a/bob/pad/face/config/qm_svm_aggregated_db.py b/bob/pad/face/config/qm_svm_aggregated_db.py
index 1acd37d9..3506a03b 100644
--- a/bob/pad/face/config/qm_svm_aggregated_db.py
+++ b/bob/pad/face/config/qm_svm_aggregated_db.py
@@ -32,14 +32,14 @@ MAX_IMAGE_SIZE = None # no limiting here
FACE_DETECTION_METHOD = None # use annotations
MIN_FACE_SIZE = 50 # skip small faces
-image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
+_image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
rgb_output_flag = RGB_OUTPUT_FLAG,
use_face_alignment = USE_FACE_ALIGNMENT,
max_image_size = MAX_IMAGE_SIZE,
face_detection_method = FACE_DETECTION_METHOD,
min_face_size = MIN_FACE_SIZE)
-preprocessor = Wrapper(image_preprocessor)
+preprocessor = Wrapper(_image_preprocessor)
"""
In the preprocessing stage the face is cropped in each frame of the input video given facial annotations.
The size of the face is normalized to ``FACE_SIZE`` dimensions. The faces of the size
--
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