Commit e236cac6 authored by Olegs NIKISINS's avatar Olegs NIKISINS
Browse files

Added underscore to preproc configs to resolve warning when running baselines

parent f45b8e3d
......@@ -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
......
......@@ -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
......
......@@ -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,
_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,
_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)
......@@ -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
......
......@@ -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
......
......@@ -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
......
......@@ -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
......
......@@ -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
......
......@@ -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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