hotfix(dataset): fix eval_mask in dataset.

* we only evaluated points on non-ground point.
* no need print ssf_metrics since our train range is out of evaluation.

Author: Kin-Zhang

src/dataset.py

@@ -366,7 +366,14 @@ def __getitem__(self, index_):
 
             if self.eval_index:
                 # looks like v2 not follow the same rule as v1 with eval_mask provided
-                data_dict['eval_mask'] = np.ones_like(data_dict['pc0'][:, 0], dtype=np.bool_) if 'eval_mask' not in f[key] else f[key]['eval_mask'][:]
+                # data_dict['eval_mask'] = np.ones_like(data_dict['pc0'][:, 0], dtype=np.bool_) if 'eval_mask' not in f[key] else f[key]['eval_mask'][:]
+                if 'eval_mask' in f[key]:
+                    data_dict['eval_mask'] = f[key]['eval_mask'][:]
+                elif 'ground_mask' in f[key]:
+                    data_dict['eval_mask'] = ~f[key]['ground_mask'][:]
+                else:
+                    data_dict['eval_mask'] = np.ones_like(data_dict['pc0'][:, 0], dtype=np.bool_)
+                    
         if self.transform:
             data_dict = self.transform(data_dict)
         return data_dict

src/utils/eval_metric.py

@@ -342,7 +342,7 @@ def normalize(self):
 
             self.epe_ssf['Mean'][motion] = np.nanmean(avg_epes)
 
-    def print(self):
+    def print(self, ssf_metrics: bool = False):
         if not self.norm_flag:
             self.normalize()
         printed_data = []
@@ -357,8 +357,9 @@ def print(self):
         print("Version 2 Metric on Normalized Category-based:")
         print(tabulate(printed_data, headers=["Class", "Static", "Dynamic"], tablefmt='orgtbl'), "\n")
 
-        printed_data = []
-        for key in self.epe_ssf:
-            printed_data.append([key, np.around(self.epe_ssf[key]['Static'],4), np.around(self.epe_ssf[key]['Dynamic'],4), self.epe_ssf[key]["#Static"], self.epe_ssf[key]["#Dynamic"]])
-        print("Version 3 Metric on EPE Distance-based:")
-        print(tabulate(printed_data, headers=["Distance", "Static", "Dynamic", "#Static", "#Dynamic"], tablefmt='orgtbl'), "\n")
+        if ssf_metrics:
+            printed_data = []
+            for key in self.epe_ssf:
+                printed_data.append([key, np.around(self.epe_ssf[key]['Static'],4), np.around(self.epe_ssf[key]['Dynamic'],4), self.epe_ssf[key]["#Static"], self.epe_ssf[key]["#Dynamic"]])
+            print("Version 3 Metric on EPE Distance-based:")
+            print(tabulate(printed_data, headers=["Distance", "Static", "Dynamic", "#Static", "#Dynamic"], tablefmt='orgtbl'), "\n")