fix compare_util

tests/compare_util.py

@@ -51,10 +51,7 @@ def cosine(gt: np.ndarray, pred: np.ndarray, *args):
 
     result = (gt @ pred) / (np.linalg.norm(gt, 2) * np.linalg.norm(pred, 2))
 
-    if not (isinstance(gt, bool) or isinstance(pred, bool)):
-        return -1 if math.isnan(result) or mse(gt, pred) >= 0.01 else result
-    else:
-        return -1 if math.isnan(result) else result
+    return -1 if math.isnan(result) else result
 
 
 def compare_arrays(gt: np.ndarray, pred: np.ndarray):
@@ -65,8 +62,16 @@ def euclidean(gt: np.ndarray, pred: np.ndarray, *args):
     return np.linalg.norm(gt.reshape(-1) - pred.reshape(-1))
 
 
-def mse(gt: np.ndarray, pred: np.ndarray, *args):
-    return np.mean((gt - pred) ** 2)
+# def mse(gt: np.ndarray, pred: np.ndarray, *args):
+#     return np.mean((gt - pred) ** 2)
+
+def divide(gt: np.ndarray, pred: np.ndarray):
+    result = np.divide(gt, pred)
+    return result
+
+
+def mean(gt: np.ndarray):
+    return np.mean(gt)
 
 
 def allclose(gt: np.ndarray, pred: np.ndarray, thresh: float):
@@ -128,6 +133,8 @@ def compare_binfile(result_path: Tuple[str, str],
         compare_op = gt
     if compare_op(similarity, threshold):
         return False, similarity_info
+    if (mean(divide(gt_arr, pred_arr)) > 1.5 or mean(divide(gt_arr, pred_arr)) < 0.6):
+        return False, similarity_info , f"\nmaybe a case of multiples"
     return True, similarity_info