def from_dlib_rect(cls, dlib_rect: dlib.rectangle):
return cls.from_values(
top_left_x=round(dlib_rect.left()),
top_left_y=round(dlib_rect.top()),
bottom_right_x=round(dlib_rect.right()),
bottom_right_y=round(dlib_rect.bottom()),
)
def show_face_block(image: numpy.ndarray, face_block: dlib.rectangle):
img_temp = image.copy()
cv2.rectangle(img_temp, (face_block.left(), face_block.top()),
(face_block.right(), face_block.bottom()), (255, 0, 255),
2)
cv2.imshow('', img_temp)
cv2.waitKey(0)
def dlibrect_to_BoundingBox_onepoint(
rect: dlib_rectangle) -> BoundingBox_onepoint:
# take a bounding box and convert it
# to the format (left, top, width, height)
x = rect.left()
y = rect.top()
w = rect.right() - x
h = rect.bottom() - y
# return a tuple of (left, top, w, h)
return BoundingBox_onepoint(x, y, w, h)
def _crop(image: np.ndarray, rect: dlib.rectangle) -> np.ndarray:
"""
Crop an image to the given rectangle.
The input is not modified.
Args:
image: input image to be cropped.
rect: rectangle to extract.
Returns:
the cropped image.
"""
top = rect.top()
bottom = rect.bottom()
left = rect.left()
right = rect.right()
return image[top:bottom, left:right]
def get_cropped_face(img, face_block: dlib.rectangle, margin='default'):
if margin == 'default':
margin = BboxCropper.MARGIN
else:
margin = margin
lt_x, lt_y, rb_x, rb_y, w, h = face_block.left(), face_block.top(), \
face_block.right() + 1, face_block.bottom() + 1, \
face_block.width(), face_block.height()
lt_ext_x = int(lt_x - margin * w)
lt_ext_y = int(lt_y - margin * h)
rb_ext_x = int(rb_x + margin * w)
rb_ext_y = int(rb_y + margin * h)
return BboxCropper.crop_image_to_dimensions(img, lt_ext_x, lt_ext_y,
rb_ext_x, rb_ext_y)
def get_bottom_right(box: dlib.rectangle, img: numpy.ndarray) -> tuple:
"""
Extract coordinates of bounding box's bottom right corner making
sure that corresponding pixel lies within specified image.
:param box: dlib.rectangle - Bounding box.
:param img: numpy.ndarray - Pixel matrix of image.
:return: tuple - x and y coordinates of bottom right corner.
Raises ValueError in case of an invalid pixel matrix or bounding box.
"""
# Check bounding box.
if box is None:
raise ValueError
# Check pixel matrix.
if not is_valid_pixel_matrix(img):
raise ValueError
# Coordinate values should not be negative.
x = max(0, box.right())
y = max(0, box.bottom())
# Coordinate values should not
# exceed the image's width / height.
return _adjust_coordinates(x, y, img)
def dlib_rect_to_box(rect: rectangle) -> BoundingBox:
x = rect.left()
y = rect.top()
w = rect.right() - x
h = rect.bottom() - y
return x, y, w, h
def draw_location(image: np.ndarray,
location: dlib.rectangle,
color=(0, 255, 0),
thickness=1) -> None:
cv2.rectangle(image, (location.left(), location.top()),
(location.right(), location.bottom()), color, thickness)
def rect_to_bbox(self, rect: dlib.rectangle):
x = rect.left()
y = rect.top()
w = rect.right() - x
h = rect.bottom() - y
return np.array([x, y, w, h])
def dlib_rect_to_boxes(rect: dlib.rectangle) -> tuple:
return rect.top(), rect.right(), rect.bottom(), rect.left()
def crate_from_dlib_rectangle(cls,
dlib_rect: dlib.rectangle) -> 'Rectangle':
return Rectangle(left_top=Point(x=dlib_rect.left(), y=dlib_rect.top()),
right_bottom=Point(x=dlib_rect.right(),
y=dlib_rect.bottom()))
def dlibrect_to_BoundingBox_twopoint(
rect: dlib_rectangle) -> BoundingBox_twopoint:
return BoundingBox_twopoint(rect.left(), rect.top(), rect.right(),
rect.bottom())
def rect_to_bb(self, rect: dlib.rectangle) -> tuple:
x = rect.left()
y = rect.top()
w = rect.right() - x
h = rect.bottom() - y
return (x, y, w, h)