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import numpy as np
def get_dims_with_exclusion(dim, exclude=None):
dims = list(range(dim))
if exclude is not None:
dims.remove(exclude)
return dims
def get_unique_labels(mask):
return np.nonzero(np.bincount(mask.flatten() + 1))[0] - 1
def get_bbox_from_mask(mask):
rows = np.any(mask, axis=1)
cols = np.any(mask, axis=0)
rmin, rmax = np.where(rows)[0][[0, -1]]
cmin, cmax = np.where(cols)[0][[0, -1]]
return rmin, rmax, cmin, cmax
def expand_bbox(bbox, expand_ratio, min_crop_size=None):
rmin, rmax, cmin, cmax = bbox
rcenter = 0.5 * (rmin + rmax)
ccenter = 0.5 * (cmin + cmax)
height = expand_ratio * (rmax - rmin + 1)
width = expand_ratio * (cmax - cmin + 1)
if min_crop_size is not None:
height = max(height, min_crop_size)
width = max(width, min_crop_size)
rmin = int(round(rcenter - 0.5 * height))
rmax = int(round(rcenter + 0.5 * height))
cmin = int(round(ccenter - 0.5 * width))
cmax = int(round(ccenter + 0.5 * width))
return rmin, rmax, cmin, cmax
def clamp_bbox(bbox, rmin, rmax, cmin, cmax):
return (max(rmin, bbox[0]), min(rmax, bbox[1]),
max(cmin, bbox[2]), min(cmax, bbox[3]))
def get_bbox_iou(b1, b2):
h_iou = get_segments_iou(b1[:2], b2[:2])
w_iou = get_segments_iou(b1[2:4], b2[2:4])
return h_iou * w_iou
def get_segments_iou(s1, s2):
a, b = s1
c, d = s2
intersection = max(0, min(b, d) - max(a, c) + 1)
union = max(1e-6, max(b, d) - min(a, c) + 1)
return intersection / union
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