def to_bbox(self):
'''
The function to_bbox create Rectangle class object from current Bitmap class object
:return: Rectangle class object
'''
return Rectangle.from_array(self._data).translate(
drow=self._origin.row, dcol=self._origin.col)
def crop(img: np.ndarray, rect: Rectangle) -> np.ndarray:
'''
The function crop cut out part of the image with rectangle size. If rectangle for crop is out of image area it
generates exception error(ValueError).
:param img: image(numpy matrix) to be cropped
:param rect: class object Rectangle of a certain size
:return: cropped image
'''
img_rect = Rectangle.from_array(img)
if not img_rect.contains(rect):
raise ValueError('Rectangle for crop out of image area!')
return rect.get_cropped_numpy_slice(img)
def crop_with_padding(img: np.ndarray, rect: Rectangle) -> np.ndarray:
'''
The function crop cut out part of the image with rectangle size. If rectangle for crop is out of image area it
generates additional padding.
:param img: image(numpy matrix) to be cropped
:param rect: class object Rectangle of a certain size
:return: cropped image
'''
img_rect = Rectangle.from_array(img)
if not img_rect.contains(rect):
row, col = img.shape[:2]
new_img = cv2.copyMakeBorder(img,
top=rect.height,
bottom=rect.height,
left=rect.width,
right=rect.width,
borderType=cv2.BORDER_CONSTANT)
new_rect = rect.translate(drow=rect.height, dcol=rect.width)
return new_rect.get_cropped_numpy_slice(new_img)
else:
return rect.get_cropped_numpy_slice(img)
def to_bbox(self):
return Rectangle.from_array(self._data).translate(
drow=self._origin.row, dcol=self._origin.col)
def crop(img: np.ndarray, rect: Rectangle) -> np.ndarray:
img_rect = Rectangle.from_array(img)
if not img_rect.contains(rect):
raise ValueError('Rectangle for crop out of image area!')
return rect.get_cropped_numpy_slice(img)
