def hw_to_center(a):
"""Convert (top left, width, height) bounding box to (center, width, height) bounding box.
Args:
param1 (arr): [xmin, ymin, width, height] where (xmin, ymin)
represents the top left of the bounding box
Returns:
arr: [center_x, center_y, width, height]
"""
bbs = util.partition(a, 4)
bbs = [[a[0] + a[2] / 2, a[1] + a[3] / 2, a[2], a[3]] for a in bbs]
return np.concatenate(bbs)
def corners_to_center(a):
"""Convert (top left, bottom right) bounding box to (center, width, height) bounding box.
Args:
param1 (arr): [xmin, ymin, xmax, ymax] where (xmin, ymin)
and (xmax, ymax) represent the top left and bottom
right corners of the bounding box
Returns:
arr: [center_x, center_y, width, height]
"""
bbs = util.partition(a, 4)
bbs = [[(a[0] + a[2]) / 2, (a[1] + a[3]) / 2,
int(a[2] - a[0]),
int(a[3] - a[1])] for a in bbs]
return np.concatenate(bbs)
def center_to_hw(a):
"""Convert (center, width, height) bounding box to (top left, width, height) bounding box.
Args:
param1 (arr): [center_x, center_y, width, height] where (center_x, center_y)
represents the center of the bounding box
Returns:
arr: [xmin, ymin, width, height]
"""
bbs = util.partition(a, 4)
bbs = [[int(a[0] - a[2] / 2),
int(a[1] - a[3] / 2),
int(a[2]),
int(a[3])] for a in bbs]
return np.concatenate(bbs)
def transform_y(self, y, x):
if not isinstance(y, md.StructuredLabel):
return y
for i, label in enumerate(y):
data, data_type, name = label
if (data_type == md.LabelType.CATEGORY):
y[i] = (np.array(data), data_type, name)
if (data_type == md.LabelType.BOUNDING_BOX):
r, c, *_ = x.shape
boxes = util.partition(
data, 4) # Partition into array of bounding boxes
masks = [center_to_mask(bb, x)
for bb in boxes] # Create masks from bounding boxes
trfms = [self.transform_x(mask)
for mask in masks] # Transform masks
y[i] = (
np.concatenate([mask_to_center(t)
for t in trfms]), data_type, name
) # Convert masks back into bounding boxes, save result
return y