File size: 3,403 Bytes
3af6d41 | 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 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 | """Measure per-region SSIM for every declared desktop visual checkpoint.
Reads the visual spec (scope/desktop-visual-comparison-current.json), crops
source and candidate rasters to each declared region bbox, and prints a
region-by-region SSIM table plus the checkpoint average. Diagnostic-only.
Usage:
.venv/bin/python materials/33/clone/measure_visual_regions.py [--json OUT]
"""
from __future__ import annotations
import argparse
import json
import sys
from pathlib import Path
import numpy as np
SITE_ROOT = Path(__file__).resolve().parents[1]
SPEC_PATH = SITE_ROOT / "scope" / "desktop-visual-comparison-current.json"
def _load_rgb(path: Path) -> np.ndarray:
from PIL import Image
with Image.open(path) as image:
return np.asarray(image.convert("RGB"), dtype=np.uint8)
def _ssim(a: np.ndarray, b: np.ndarray) -> float:
from skimage.metrics import structural_similarity as ssim_fn
return round(float(ssim_fn(a, b, channel_axis=2, data_range=255)), 4)
def main() -> int:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--json", dest="json_out", help="write JSON summary to this path")
args = parser.parse_args()
spec = json.loads(SPEC_PATH.read_text(encoding="utf-8"))
summary: dict[str, object] = {"checkpoints": []}
all_regions: list[float] = []
for checkpoint in spec["checkpoints"]:
checkpoint_id = checkpoint["id"]
source_path = (SPEC_PATH.parent / checkpoint["source"]["path"]).resolve()
candidate_path = (SPEC_PATH.parent / checkpoint["candidate"]["path"]).resolve()
source = _load_rgb(source_path)
candidate = _load_rgb(candidate_path)
if source.shape != candidate.shape:
print(
f"!! {checkpoint_id}: size mismatch "
f"{source.shape} vs {candidate.shape}",
file=sys.stderr,
)
continue
rows: list[dict[str, object]] = []
region_scores: list[float] = []
for region in checkpoint["regions"]:
x, y = region["x"], region["y"]
w, h = region["width"], region["height"]
score = _ssim(source[y : y + h, x : x + w], candidate[y : y + h, x : x + w])
rows.append(
{
"checkpoint": checkpoint_id,
"region": region["id"],
"bbox": [x, y, w, h],
"ssim": score,
}
)
region_scores.append(score)
all_regions.append(score)
average = round(float(np.mean(region_scores)), 4) if region_scores else None
print(f"{checkpoint_id}: avg={average}")
for row in rows:
print(f" {row['region']:<20} {row['ssim']}")
summary["checkpoints"].append(
{
"id": checkpoint_id,
"regions": rows,
"average_ssim": average,
}
)
summary["overall_region_average"] = round(float(np.mean(all_regions)), 4)
print(f"overall region average: {summary['overall_region_average']}")
if args.json_out:
out = Path(args.json_out)
out.parent.mkdir(parents=True, exist_ok=True)
out.write_text(json.dumps(summary, indent=2) + "\n", encoding="utf-8")
print(f"wrote {out}")
return 0
if __name__ == "__main__":
sys.exit(main())
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