import numpy as np, glob, sys
from PIL import Image
d=sys.argv[1]
f=sorted(glob.glob(f"{d}/f*.png"))
a=[np.asarray(Image.open(x).convert("RGB"),dtype=np.int16) for x in f]
# noise-tolerant per-pair change: % of pixels differing by more than 8 levels
p=np.array([100.0*np.count_nonzero(np.abs(a[i]-a[i-1]).max(axis=2)>8)/(a[0].shape[0]*a[0].shape[1]) for i in range(1,len(a))])
print(f"  pairs={len(p)}  mean={p.mean():.2f}%  median={np.median(p):.2f}%  p90={np.percentile(p,90):.2f}%  max={p.max():.2f}%")
ev,od=p[0::2],p[1::2]
print(f"  even-idx pairs mean={ev.mean():.2f}%   odd-idx pairs mean={od.mean():.2f}%   ratio={max(ev.mean(),od.mean())/max(min(ev.mean(),od.mean()),1e-9):.1f}x")
print(f"  first 16 pairs: {np.round(p[:16],2)}")