change class names

tools/data_converter/scannet_converter.py

@@ -2,7 +2,7 @@ import os
 import pickle
 from pathlib import Path
 
-from tools.data_converter.scannet_data_utils import ScannetObject
+from tools.data_converter.scannet_data_utils import ScanNetData
 
 
 def create_scannet_info_file(data_path, pkl_prefix='scannet', save_path=None):
@@ -14,8 +14,8 @@ def create_scannet_info_file(data_path, pkl_prefix='scannet', save_path=None):
     assert os.path.exists(save_path)
     train_filename = save_path / f'{pkl_prefix}_infos_train.pkl'
     val_filename = save_path / f'{pkl_prefix}_infos_val.pkl'
-    train_dataset = ScannetObject(root_path=data_path, split='train')
-    val_dataset = ScannetObject(root_path=data_path, split='val')
+    train_dataset = ScanNetData(root_path=data_path, split='train')
+    val_dataset = ScanNetData(root_path=data_path, split='val')
     scannet_infos_train = train_dataset.get_scannet_infos(has_label=True)
     with open(train_filename, 'wb') as f:
         pickle.dump(scannet_infos_train, f)

tools/data_converter/scannet_data_utils.py

@@ -3,7 +3,7 @@ import os
 import numpy as np
 
 
-class ScannetObject(object):
+class ScanNetData(object):
     ''' Load and parse object data '''
 
     def __init__(self, root_path, split='train'):
@@ -79,7 +79,4 @@ class ScannetObject(object):
             else self.sample_id_list
         with futures.ThreadPoolExecutor(num_workers) as executor:
             infos = executor.map(process_single_scene, sample_id_list)
-        # infos = list()
-        # for sample in sample_id_list:
-        #     infos.append(process_single_scene(sample))
         return list(infos)

tools/data_converter/sunrgbd_converter.py

@@ -2,7 +2,7 @@ import os
 import pickle
 from pathlib import Path
 
-from tools.data_converter.sunrgbd_data_utils import SUNRGBDObject
+from tools.data_converter.sunrgbd_data_utils import SUNRGBDData
 
 
 def create_sunrgbd_info_file(data_path,
@@ -17,10 +17,9 @@ def create_sunrgbd_info_file(data_path,
     assert os.path.exists(save_path)
     train_filename = save_path / f'{pkl_prefix}_infos_train.pkl'
     val_filename = save_path / f'{pkl_prefix}_infos_val.pkl'
-    train_dataset = SUNRGBDObject(
+    train_dataset = SUNRGBDData(
         root_path=data_path, split='train', use_v1=use_v1)
-    val_dataset = SUNRGBDObject(
-        root_path=data_path, split='val', use_v1=use_v1)
+    val_dataset = SUNRGBDData(root_path=data_path, split='val', use_v1=use_v1)
     sunrgbd_infos_train = train_dataset.get_sunrgbd_infos(has_label=True)
     with open(train_filename, 'wb') as f:
         pickle.dump(sunrgbd_infos_train, f)

tools/data_converter/sunrgbd_data_utils.py

@@ -17,7 +17,7 @@ def random_sampling(pc, num_sample, replace=None, return_choices=False):
         return pc[choices]
 
 
-class SUNObject3d(object):
+class SUNRGBDInstance(object):
 
     def __init__(self, line):
         data = line.split(' ')
@@ -43,7 +43,7 @@ class SUNObject3d(object):
         ])
 
 
-class SUNRGBDObject(object):
+class SUNRGBDData(object):
     ''' Load and parse object data '''
 
     def __init__(self, root_path, split='train', use_v1=False):
@@ -57,7 +57,7 @@ class SUNRGBDObject(object):
         self.cat2label = {cat: self.classes.index(cat) for cat in self.classes}
         self.label2cat = {
             label: self.classes[label]
-            for label in len(self.classes)
+            for label in range(len(self.classes))
         }
         assert split in ['train', 'val', 'test']
         split_dir = os.path.join(self.root_dir, '%s_data_idx.txt' % split)
@@ -100,7 +100,7 @@ class SUNRGBDObject(object):
     def get_label_objects(self, idx):
         label_filename = os.path.join(self.label_dir, '%06d.txt' % (idx))
         lines = [line.rstrip() for line in open(label_filename)]
-        objects = [SUNObject3d(line) for line in lines]
+        objects = [SUNRGBDInstance(line) for line in lines]
         return objects
 
     def get_sunrgbd_infos(self,