import sys, numpy as np
from PIL import Image
root = r"artifacts/vm0"
def load(n): return np.asarray(Image.open(f"{root}/{n}/screenshots/world-offline.png").convert("RGB")).astype(np.int16)
def cmp(a, b, name, maskTop=0):
    A, B = load(a), load(b)
    assert A.shape == B.shape, (A.shape, B.shape)
    d = np.abs(A - B).max(axis=2)
    H, W = d.shape
    region = d[maskTop:, :]
    diff = region > 0
    n = int(diff.sum()); tot = region.size
    rows = np.where(diff.any(axis=1))[0]
    print(f"{name}: {n} / {tot} px differ ({100.0*n/tot:.5f}%)"
          + (f"  rows {rows.min()+maskTop}-{rows.max()+maskTop}, max|d|={int(region.max())}, mean|d| over differing={region[diff].mean():.2f}" if n else "  IDENTICAL"))
    if n:
        hist = np.bincount(region[diff].astype(np.int64), minlength=8)
        print(f"   |d| histogram 1..7+: {hist[1:8].tolist()} ...>=8: {int((region[diff]>=8).sum())}")
        vis = np.zeros((H, W, 3), np.uint8)
        vis[..., 0] = np.clip(d * 16, 0, 255).astype(np.uint8)  # red = difference amplified x16
        base = (A.astype(np.float32) * 0.25).astype(np.uint8)
        vis = np.maximum(vis, base)
        Image.fromarray(vis).save(f"{root}/diff-{name}.png")
    return n
print("== whole frame, exact ==")
cmp("base", "base-normals", "A2-normals-only")
cmp("base-normals", "head-off", "HEAD-off_vs_base+normals")
cmp("head-off", "head-on", "detail-on_vs_off")
cmp("base", "head-off", "HEAD-off_vs_base")
print("== top-280 sky band masked (the tool's documented self-noise band) ==")
cmp("base-normals", "head-off", "HEAD-off_vs_base+normals_masked", 280)