File size: 2,559 Bytes
352cafd |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 |
import numpy as np
import cv2
def get_disk_kernel(radius):
return cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (radius*2+1, radius*2+1))
def compute_boundary_acc(gt, seg, mask):
gt = gt.astype(np.uint8)
seg = seg.astype(np.uint8)
mask = mask.astype(np.uint8)
h, w = gt.shape
min_radius = 1
max_radius = (w+h)/300
num_steps = 5
seg_acc = [None] * num_steps
mask_acc = [None] * num_steps
for i in range(num_steps):
curr_radius = min_radius + int((max_radius-min_radius)/num_steps*i)
kernel = get_disk_kernel(curr_radius)
boundary_region = cv2.morphologyEx(gt, cv2.MORPH_GRADIENT, kernel) > 0
gt_in_bound = gt[boundary_region]
seg_in_bound = seg[boundary_region]
mask_in_bound = mask[boundary_region]
num_edge_pixels = (boundary_region).sum()
num_seg_gd_pix = ((gt_in_bound) * (seg_in_bound) + (1-gt_in_bound) * (1-seg_in_bound)).sum()
num_mask_gd_pix = ((gt_in_bound) * (mask_in_bound) + (1-gt_in_bound) * (1-mask_in_bound)).sum()
seg_acc[i] = num_seg_gd_pix / num_edge_pixels
mask_acc[i] = num_mask_gd_pix / num_edge_pixels
return sum(seg_acc)/num_steps, sum(mask_acc)/num_steps
def compute_boundary_acc_multi_class(gt, seg, mask):
h, w = gt.shape
min_radius = 1
max_radius = (w+h)/300
num_steps = 5
seg_acc = [None] * num_steps
mask_acc = [None] * num_steps
classes = np.unique(gt)
for i in range(num_steps):
curr_radius = min_radius + int((max_radius-min_radius)/num_steps*i)
kernel = get_disk_kernel(curr_radius)
boundary_region = np.zeros_like(gt)
for c in classes:
# Skip void
if c == 0:
continue
gt_class = (gt == c).astype(np.uint8)
class_bound = cv2.morphologyEx(gt_class, cv2.MORPH_GRADIENT, kernel)
boundary_region += class_bound
boundary_region = boundary_region > 0
gt_in_bound = gt[boundary_region]
seg_in_bound = seg[boundary_region]
mask_in_bound = mask[boundary_region]
void_count = (gt_in_bound == 0).sum()
num_edge_pixels = (boundary_region).sum()
num_seg_gd_pix = (gt_in_bound == seg_in_bound).sum()
num_mask_gd_pix = (gt_in_bound == mask_in_bound).sum()
seg_acc[i] = (num_seg_gd_pix-void_count) / (num_edge_pixels-void_count)
mask_acc[i] = (num_mask_gd_pix-void_count) / (num_edge_pixels-void_count)
return sum(seg_acc)/num_steps, sum(mask_acc)/num_steps |