def apply(self, img, **params):
w, h = img.shape[:2]
crop_w, crop_h = self.width, self.height
if self.crop_pos == 0:
return F.crop(img, 0, 0, crop_w, crop_h)
elif self.crop_pos == 1:
return F.crop(img, w - crop_w, 0, w, crop_h)
elif self.crop_pos == 2:
return F.crop(img, 0, h - crop_h, crop_w, h)
elif self.crop_pos == 3:
return F.crop(img, w - crop_w, h - crop_h, w, h)
else:
return F.center_crop(img, crop_h, crop_w)
def apply(self, img, offset=(0, 0, 0, 0), **params):
x_min = offset[0]
y_min = offset[1]
x_max = params['cols'] - offset[2]
y_max = params['rows'] - offset[3]
return F.crop(img, x_min=x_min, y_min=y_min, x_max=x_max, y_max=y_max)
def five_crop(
img: numpy.ndarray, size: List[int]
) -> Tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray, numpy.ndarray,
numpy.ndarray]:
"""Crop the given image into four corners and the central crop.
Args:
img (numpy.ndarray): Image to be cropped.
size (sequence or int): Desired output size of the crop. If size is an
int instead of sequence like (h, w), a square crop (size, size) is
made. If provided a sequence of length 1, it will be interpreted
as (size[0], size[0]).
Returns:
tuple: tuple (tl, tr, bl, br, center)
Corresponding top left, top right, bottom left, bottom right and center crop.
"""
image_height, image_width = img.shape[:2]
crop_height, crop_width = size
if crop_width > image_width or crop_height > image_height:
msg = "Requested crop size {} is bigger than input size {}"
raise ValueError(msg.format(size, (image_height, image_width)))
tl = F.crop(img, 0, 0, crop_width, crop_height)
tr = F.crop(img, image_width - crop_width, 0, image_width, crop_height)
bl = F.crop(img, 0, image_height - crop_height, crop_width, image_height)
br = F.crop(
img,
image_width - crop_width,
image_height - crop_height,
image_width,
image_height,
)
center = F.center_crop(img, crop_height, crop_width)
return tl, tr, bl, br, center
def apply(self, img, x_min=0, x_max=0, y_min=0, y_max=0, **params):
cropped = crop(img, x_min, y_min, x_max, y_max)
return cropped
def resized_crop(image, height, width, x_min, y_min, x_max, y_max):
image = F.crop(image, x_min, y_min, x_max, y_max)
image = cv2.resize(image, (width, height))
return image
def apply(self, img, **params):
return [F.crop(img, **crop) for crop in self.get_crops(img.shape)]