putting the ncc in the metric calculation itself for clarity

mlcommons · Dec 19, 2024 · 8b9a797 · 8b9a797
1 parent 08dc42a
commit 8b9a797
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Showing 2 changed files with 6 additions and 6 deletions.
diff --git a/GANDLF/cli/generate_metrics.py b/GANDLF/cli/generate_metrics.py
@@ -375,7 +375,7 @@ def __percentile_clip(
             if compute_ncc:
                 calculated_ncc_metrics = ncc_metrics(output_infill, gt_image_infill)
                 for key, value in calculated_ncc_metrics.items():
-                    overall_stats_dict[current_subject_id][f"ncc_{key}"] = value.item()
+                    overall_stats_dict[current_subject_id][key] = value.item()
 
             # only voxels that are to be inferred (-> flat array)
             # these are required for mse, psnr, etc.

diff --git a/GANDLF/metrics/synthesis.py b/GANDLF/metrics/synthesis.py
@@ -195,9 +195,9 @@ def ncc_metrics(prediction: torch.Tensor, target: torch.Tensor) -> dict:
     onesImage = corr_image == corr_image
     stats_filter.Execute(corr_image, onesImage)
     return {
-        "mean": stats_filter.GetMean(1),
-        "std": stats_filter.GetSigma(1),
-        "max": stats_filter.GetMaximum(1),
-        "min": stats_filter.GetMinimum(1),
-        "median": stats_filter.GetMedian(1),
+        "ncc_mean": stats_filter.GetMean(1),
+        "ncc_std": stats_filter.GetSigma(1),
+        "ncc_max": stats_filter.GetMaximum(1),
+        "ncc_min": stats_filter.GetMinimum(1),
+        "ncc_median": stats_filter.GetMedian(1),
     }