Metrics
Metrics utilities for LVAE training and evaluation.
RunningPSNR
Track the running PSNR over validation batches.
get()
Return the current PSNR.
reset()
Reset accumulated statistics.
update(rec, tar)
Update statistics with a batch of reconstructed and target images.
PSNR(gt, pred, range_=None)
Compute PSNR for tensors shaped as (batch, H, W).
RangeInvariantPsnr(gt, pred)
Compute range-invariant PSNR for grayscale images.
avg_psnr(target, prediction)
Compute mean and standard error of PSNR.
avg_range_inv_psnr(target, prediction)
Compute mean and standard error of range-invariant PSNR.
avg_ssim(target, prediction)
Compute mean and standard deviation of SSIM.
compute_SE(arr)
Compute the standard error of the mean.
compute_custom_ssim(gt_, pred_, ssim_obj_dict)
Compute SSIM using custom per-channel scorers.
compute_masked_psnr(mask, tar1, tar2, pred1, pred2)
Compute PSNR on masked regions for two target/prediction pairs.
compute_multiscale_ssim(gt_, pred_, range_invariant=True)
Compute channel-wise multiscale SSIM.
compute_stats(highres_data, pred_unnorm, verbose=True)
Compute PSNR- and SSIM-based metrics on high-SNR data.
fix(gt, x)
Zero-mean tensors and match prediction range to the ground truth.
fix_range(gt, x)
Rescale a tensor to match the range of the ground truth.
range_invariant_multiscale_ssim(gt_, pred_)
Compute range-invariant multiscale SSIM for one channel.
zero_mean(x)
Return a zero-mean tensor along the channel dimension.