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import numpy as np
import scipy.linalg
from . import metric_utils
import math
import cv2
def compute_psnr(opts, max_real):
# stats: numpy, [N, 3]
stats = metric_utils.compute_image_stats_for_generator(opts=opts, capture_all=True, max_items=max_real).get_all()
if opts.rank != 0:
return float('nan'), float('nan'), float('nan')
print('Number of samples: %d' % stats.shape[0])
avg_psnr = stats[:, 0].sum() / stats.shape[0]
avg_ssim = stats[:, 1].sum() / stats.shape[0]
avg_l1 = stats[:, 2].sum() / stats.shape[0]
return avg_psnr, avg_ssim, avg_l1