Update README.md

README.md

@@ -81,13 +81,9 @@ with torch.no_grad():
  
 iqa_score = np.mean(scores)
 
-# maps the predicted score from the model's range [min_pred, max_pred] 
-# to the actual range [min_score, max_score] using min-max scaling.
-
+# maps the predicted score to [0,1] range
 min_pred = -6.52
 max_pred = 3.11
-max_score = 4.32
-min_score = 1
 
-normalized_score = ((iqa_score - min_pred) / (max_pred - min_pred)) * (max_score - min_score) + min_score
+normalized_score = ((iqa_score - min_pred) / (max_pred - min_pred))
 print(f"Predicted quality Score: {normalized_score:.4f}")