Update metrics.py

using sklearn to calculate confusion matrix

Author: xyl576807077

ptsemseg/metrics.py

@@ -2,23 +2,15 @@
 # https://github.com/wkentaro/pytorch-fcn/blob/master/torchfcn/utils.py
 
 import numpy as np
-
+from sklearn.metrics import confusion_matrix
 
 class runningScore(object):
     def __init__(self, n_classes):
         self.n_classes = n_classes
         self.confusion_matrix = np.zeros((n_classes, n_classes))
 
-    def _fast_hist(self, label_true, label_pred, n_class):
-        mask = (label_true >= 0) & (label_true < n_class)
-        hist = np.bincount(
-            n_class * label_true[mask].astype(int) + label_pred[mask], minlength=n_class ** 2
-        ).reshape(n_class, n_class)
-        return hist
-
     def update(self, label_trues, label_preds):
-        for lt, lp in zip(label_trues, label_preds):
-            self.confusion_matrix += self._fast_hist(lt.flatten(), lp.flatten(), self.n_classes)
+        self.confusion_matrix += confusion_matrix(label_trues.flatten(), label_preds.flatten(), list(range(self.n_classes)))
 
     def get_scores(self):
         """Returns accuracy score evaluation result.