File size: 1,135 Bytes
f698f1c | 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 | import numpy as np
import cv2
from skimage.morphology import skeletonize
def crack_metrics(mask: np.ndarray):
# mask: [H,W] 0/1
area_px = int(mask.sum())
# largest connected component
num_labels, labels, stats, _ = cv2.connectedComponentsWithStats(mask.astype(np.uint8), connectivity=8)
largest_cc = 0
if num_labels > 1:
# ignore background label 0
largest_cc = int(stats[1:, cv2.CC_STAT_AREA].max())
# length estimate via skeletonization
skel = skeletonize(mask.astype(bool))
length_px = int(skel.sum())
return {
"area_px": area_px,
"length_px": length_px,
"largest_component_px": largest_cc,
}
def severity_from_metrics(m):
# Tune these thresholds on your validation set
area = m["area_px"]
length = m["length_px"]
largest = m["largest_component_px"]
score = 0
if area > 1500: score += 1
if area > 6000: score += 1
if length > 600: score += 1
if length > 2000: score += 1
if largest > 2500: score += 1
if score >= 4:
return "High"
if score >= 2:
return "Medium"
return "Low" |