|
|
|
|
|
import os
|
|
|
import argparse
|
|
|
import json
|
|
|
from datetime import datetime
|
|
|
import cv2
|
|
|
import numpy as np
|
|
|
from skimage.metrics import peak_signal_noise_ratio as psnr
|
|
|
from PIL import Image, UnidentifiedImageError
|
|
|
|
|
|
def verify_image(path, exts=('.png', '.jpg', '.jpeg', '.webp')):
|
|
|
"""Verify file exists, is non-empty, has valid extension, and can be opened by PIL."""
|
|
|
if not os.path.isfile(path):
|
|
|
return False, f'File not found: {path}'
|
|
|
if os.path.getsize(path) == 0:
|
|
|
return False, f'File is empty: {path}'
|
|
|
if not path.lower().endswith(exts):
|
|
|
return False, f'Unsupported format: {path}'
|
|
|
try:
|
|
|
img = Image.open(path)
|
|
|
img.verify()
|
|
|
except (UnidentifiedImageError, Exception) as e:
|
|
|
return False, f'Cannot read image: {path} ({e})'
|
|
|
return True, ''
|
|
|
|
|
|
def evaluate_psnr(input_img_path, output_img_path):
|
|
|
"""Read images and calculate PSNR"""
|
|
|
img1 = cv2.imread(input_img_path)
|
|
|
img2 = cv2.imread(output_img_path)
|
|
|
img1 = cv2.cvtColor(img1, cv2.COLOR_BGR2RGB)
|
|
|
img2 = cv2.cvtColor(img2, cv2.COLOR_BGR2RGB)
|
|
|
|
|
|
if img1.shape != img2.shape:
|
|
|
img2 = cv2.resize(img2, (img1.shape[1], img1.shape[0]))
|
|
|
|
|
|
return psnr(img1, img2)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
|
parser = argparse.ArgumentParser(description="PSNR image quality evaluation")
|
|
|
parser.add_argument('--groundtruth', required=True, help='Original image path')
|
|
|
parser.add_argument('--output', required=True, help='Reconstructed image path')
|
|
|
parser.add_argument('--result', required=True, help='Path to save results as JSONL')
|
|
|
args = parser.parse_args()
|
|
|
|
|
|
process = True
|
|
|
comments = []
|
|
|
|
|
|
|
|
|
for tag, path in [('input', args.groundtruth), ('output', args.output)]:
|
|
|
ok, msg = verify_image(path)
|
|
|
if not ok:
|
|
|
process = False
|
|
|
comments.append(f'[{tag}] {msg}')
|
|
|
|
|
|
|
|
|
psnr_val = None
|
|
|
if process:
|
|
|
try:
|
|
|
psnr_val = evaluate_psnr(args.groundtruth, args.output)
|
|
|
result_flag = psnr_val > 10
|
|
|
comments.append(f'PSNR={psnr_val:.2f} (>10 → {"PASS" if result_flag else "FAIL"})')
|
|
|
except Exception as e:
|
|
|
process = False
|
|
|
result_flag = False
|
|
|
comments.append(f'PSNR calculation error: {e}')
|
|
|
else:
|
|
|
result_flag = False
|
|
|
|
|
|
|
|
|
entry = {
|
|
|
"Process": process,
|
|
|
"Result": result_flag,
|
|
|
"TimePoint": datetime.now().isoformat(sep='T', timespec='seconds'),
|
|
|
"comments": "; ".join(comments)
|
|
|
}
|
|
|
print(entry["comments"])
|
|
|
os.makedirs(os.path.dirname(args.result) or '.', exist_ok=True)
|
|
|
with open(args.result, 'a', encoding='utf-8') as f:
|
|
|
f.write(json.dumps(entry, ensure_ascii=False, default=str) + "\n")
|
|
|
|
|
|
|
|
|
print("\nTest complete - Final status: " + ("PASS" if result_flag else "FAIL")) |
