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#!/usr/bin/env python3
"""P78（夜晚氛围与场景细节）基准截图抽帧分析。
读 `LV_P78_SHOT=1` 的真实 xvfb 1280x720 帧（同日同时刻机位先拍正午、再拍 22 时）与日志，
在像素层给出可测断言，避免只靠 vision 手判：
1. 夜帧水面逐格微光斑：光斑格条带亮度 - 相邻非光斑水格亮度 >= 10；非光斑水格 std <= 12
（暗部平整、光斑不是噪声）。
2. 暗部层次：夜帧水面 bbox std >= 白天水面 bbox std，且夜帧无实心 24x24 近黑块、
近黑占比 <= 0.02（不是「铁板一块」）。
3. 炊烟：夜帧炊烟区亮度 - 白天炊烟区亮度 >= 20（夜帧更醒目）；日志 smoke_alpha(夜) > 80。
4. 桥头灯柱窄光晕：灯柱环带亮度 - 外圈亮度 夜帧 >= 8，白天 < 8（夜帧才加、窄）。
5. 白天零回归：日志 lantern=0.00；白天/夜帧 pairwise diff > 0。
Usage: python3 scripts/analyze-p78.py <record-dir> <out-txt>
Exit 0 pass / 1 fail / 2 usage.
"""
import re
import sys
from pathlib import Path
import numpy as np
from PIL import Image
from numpy.lib.stride_tricks import sliding_window_view
REGIONS_RE = re.compile(
r"^p78-regions (day|night) glint_src=(-?\d+),(-?\d+) glint_ctl=(-?\d+),(-?\d+) bridge_src=(-?\d+),(-?\d+)",
re.MULTILINE,
)
NIGHT_RE = re.compile(
r"^p78-shot=night .*smoke_src=(-?\d+),(-?\d+) smoke_alpha=(\d+)",
re.MULTILINE,
)
DAY_RE = re.compile(r"^p78-shot=day .*lantern=([\d.]+)", re.MULTILINE)
TILE = 32
BLOCK = 24
NEAR_BLACK = 24
WATER_BBOX_Y = (280, 376)
def luma(a):
return 0.299 * a[:, :, 0] + 0.587 * a[:, :, 1] + 0.114 * a[:, :, 2]
def last_regions(text, tag):
hits = [m for m in REGIONS_RE.finditer(text) if m.group(1) == tag]
if not hits:
return None
m = hits[-1]
return {
"glint": (int(m.group(2)), int(m.group(3))),
"ctl": (int(m.group(4)), int(m.group(5))),
"bridge": (int(m.group(6)), int(m.group(7))),
}
def ring_mean(a, cx, cy, r0, r1):
y, x = np.ogrid[: a.shape[0], : a.shape[1]]
d = np.sqrt((x - cx) ** 2 + (y - cy) ** 2)
m = (d >= r0) & (d < r1)
return float(luma(a)[m].mean())
def main():
if len(sys.argv) != 3:
print(__doc__)
return 2
rec = Path(sys.argv[1])
out = Path(sys.argv[2])
log = (rec / "log.txt").read_text(encoding="utf-8", errors="replace")
failures = []
lines = [
"P78（夜晚氛围与场景细节）证据分析 — 真实 Desktop xvfb 1280x720，同日同机位 正午 vs 22 时",
"近黑阈值 24；实心块 = 24x24 全近黑。",
"",
]
day_img = rec / "p78-day.png"
night_img = rec / "p78-night.png"
if not day_img.exists() or not night_img.exists():
out.write_text("missing p78-day.png / p78-night.png\nverdict=FAIL\n", encoding="utf-8")
print("missing frames")
return 1
day = np.asarray(Image.open(day_img).convert("RGB"), dtype=np.int16)
night = np.asarray(Image.open(night_img).convert("RGB"), dtype=np.int16)
day_regions = last_regions(log, "day")
night_regions = last_regions(log, "night")
if not day_regions or not night_regions:
failures.append("missing p78-regions day/night")
if "p78-shot=day" not in log or "p78-shot=night" not in log:
failures.append("missing p78-shot day/night lines")
day_lantern = DAY_RE.search(log)
if day_lantern and float(day_lantern.group(1)) != 0.0:
failures.append(f"白天 lantern={day_lantern.group(1)} 应为 0.00（白天零回归）")
lines.append(f"day lantern={day_lantern.group(1) if day_lantern else '?'}（须 0.00）")
# 1. 夜帧水面微光斑对比。
if night_regions:
gx, gy = night_regions["glint"]
cx, cy = night_regions["ctl"]
if gx < 0 or cx < 0:
failures.append("夜帧未定位到可见光斑/对照水格")
else:
g_tile = luma(night)[gy : gy + TILE, gx : gx + TILE]
c_tile = luma(night)[cy : cy + TILE, cx : cx + TILE]
stripe = g_tile[12:16, 6:26].mean()
ctl_mean = c_tile.mean()
ctl_std = c_tile.std()
delta = stripe - ctl_mean
lines.append(
f"night glint stripe={stripe:.1f} ctl_mean={ctl_mean:.1f} ctl_std={ctl_std:.1f} delta={delta:.1f}"
)
if delta < 10:
failures.append(f"夜帧光斑对比不足 delta={delta:.1f} < 10")
if ctl_std > 12:
failures.append(f"夜帧非光斑水面不够平整 std={ctl_std:.1f} > 12")
# 2. 暗部层次 + 无铁板一块。
day_water = luma(day)[WATER_BBOX_Y[0] : WATER_BBOX_Y[1], :]
night_water = luma(night)[WATER_BBOX_Y[0] : WATER_BBOX_Y[1], :]
lines.append(
f"water bbox std: day={day_water.std():.1f} night={night_water.std():.1f}"
)
if night_water.std() < day_water.std():
failures.append("夜帧水面层次低于白天（暗部被压平）")
mask = (night[:, :, 0] <= NEAR_BLACK) & (night[:, :, 1] <= NEAR_BLACK) & (night[:, :, 2] <= NEAR_BLACK)
frac = float(mask.mean())
block = int(sliding_window_view(mask.astype(np.int64), (BLOCK, BLOCK)).sum(axis=(2, 3)).max())
lines.append(f"night near-black frac={frac:.3f} max24blk={block}")
if frac > 0.02:
failures.append(f"夜帧近黑占比 {frac:.3f} > 0.02（铁板一块）")
if block >= BLOCK * BLOCK:
failures.append("夜帧存在实心 24x24 近黑块")
# 3. 炊烟夜帧更醒目。
night_meta = NIGHT_RE.search(log)
if not night_meta:
failures.append("missing p78-shot=night smoke metadata")
else:
sx, sy, smoke_alpha = int(night_meta.group(1)), int(night_meta.group(2)), int(night_meta.group(3))
day_smoke = luma(day)[320:400, 620:720].mean()
night_smoke = luma(night)[320:400, 620:720].mean()
lines.append(
f"smoke region mean: day={day_smoke:.1f} night={night_smoke:.1f} delta={night_smoke - day_smoke:.1f} smoke_alpha={smoke_alpha}"
)
if night_smoke - day_smoke < 20:
failures.append(f"夜帧炊烟不够醒目 delta={night_smoke - day_smoke:.1f} < 20")
if smoke_alpha <= 80:
failures.append(f"夜帧炊烟 alpha {smoke_alpha} 应 > 80")
# 4. 桥头灯柱窄光晕。
if day_regions and night_regions and night_regions["bridge"][0] >= 0:
bx, by = night_regions["bridge"]
ccx, ccy = bx + TILE // 2, by + TILE // 2
day_ring = ring_mean(day, ccx, ccy, 8, 30) - ring_mean(day, ccx, ccy, 40, 64)
night_ring = ring_mean(night, ccx, ccy, 8, 30) - ring_mean(night, ccx, ccy, 40, 64)
lines.append(f"bridge ring diff: day={day_ring:.1f} night={night_ring:.1f}")
if night_ring < 8:
failures.append(f"夜帧桥头窄光晕不足 diff={night_ring:.1f} < 8")
if day_ring >= 8:
failures.append(f"白天桥头不应有夜光晕 diff={day_ring:.1f}")
# 5. 白天/夜帧差异。
diff = int((np.abs(day.astype(np.int64) - night.astype(np.int64)).sum(axis=2) > 0).sum())
lines.append(f"day vs night differing_pixels={diff}")
if diff == 0:
failures.append("白天与夜帧完全相同")
lines.append("")
if failures:
lines.append("verdict=FAIL")
for f in failures:
lines.append(" - " + f)
else:
lines.append("verdict=PASS")
lines.append(" 夜帧光斑对比/非光斑平整、水面层次不低于白天、无铁板一块；")
lines.append(" 炊烟夜帧更醒目、桥头窄光晕仅夜帧出现；白天 lantern=0 且两帧有差异。")
out.parent.mkdir(parents=True, exist_ok=True)
out.write_text("\n".join(lines) + "\n", encoding="utf-8")
print(f"wrote {out} verdict={'FAIL' if failures else 'PASS'}")
return 1 if failures else 0
if __name__ == "__main__":
sys.exit(main())
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