[Refactor] rename `CLASSES` and `PALETTE` to `classes` and `palette` in dataset metainfo (#1932)

* rame CLASS and PALETTE to class and palette

* change mmcv-full to mmcv

* fix comments

tests/test_datasets/test_scannet_dataset.py

@@ -136,7 +136,7 @@ class TestScanNetDataset(unittest.TestCase):
             ann_file,
             data_prefix=data_prefix,
             pipeline=pipeline,
-            metainfo=dict(CLASSES=classes),
+            metainfo=dict(classes=classes),
             modality=modality)
 
         scannet_dataset.prepare_data(0)
@@ -163,7 +163,7 @@ class TestScanNetDataset(unittest.TestCase):
                               torch.tensor([107.7353]))
 
         no_class_scannet_dataset = ScanNetDataset(
-            data_root, ann_file, metainfo=dict(CLASSES=['cabinet']))
+            data_root, ann_file, metainfo=dict(classes=['cabinet']))
 
         input_dict = no_class_scannet_dataset.get_data_info(0)
         ann_info = no_class_scannet_dataset.parse_ann_info(input_dict)
@@ -175,7 +175,7 @@ class TestScanNetDataset(unittest.TestCase):
         self.assertEqual(ann_info['gt_labels_3d'].dtype, np.int64)
         # all instance have been filtered by classes
         self.assertEqual(len(ann_info['gt_labels_3d']), 27)
-        self.assertEqual(len(no_class_scannet_dataset.metainfo['CLASSES']), 1)
+        self.assertEqual(len(no_class_scannet_dataset.metainfo['classes']), 1)
 
     def test_scannet_seg(self):
         data_root, ann_file, classes, palette, scene_idxs, data_prefix, \
@@ -186,7 +186,7 @@ class TestScanNetDataset(unittest.TestCase):
         scannet_seg_dataset = ScanNetSegDataset(
             data_root,
             ann_file,
-            metainfo=dict(CLASSES=classes, PALETTE=palette),
+            metainfo=dict(classes=classes, palette=palette),
             data_prefix=data_prefix,
             pipeline=pipeline,
             modality=modality,

tests/test_datasets/test_semantickitti_dataset.py

@@ -72,7 +72,7 @@ class TestSemanticKITTIDataset(unittest.TestCase):
         semantickitti_dataset = SemanticKITTIDataset(
             data_root,
             ann_file,
-            metainfo=dict(CLASSES=classes, PALETTE=palette),
+            metainfo=dict(classes=classes, palette=palette),
             data_prefix=data_prefix,
             pipeline=pipeline,
             modality=modality)

tests/test_datasets/test_sunrgbd_dataset.py

@@ -48,7 +48,7 @@ class TestScanNetDataset(unittest.TestCase):
             ann_file,
             data_prefix=data_prefix,
             pipeline=pipeline,
-            metainfo=dict(CLASSES=classes),
+            metainfo=dict(classes=classes),
             modality=modality)
 
         scannet_dataset.prepare_data(0)
@@ -81,7 +81,7 @@ class TestScanNetDataset(unittest.TestCase):
             ann_file,
             data_prefix=data_prefix,
             pipeline=pipeline,
-            metainfo=dict(CLASSES=classes),
+            metainfo=dict(classes=classes),
             modality=modality)
 
         input_dict = bed_scannet_dataset.get_data_info(0)
@@ -94,4 +94,4 @@ class TestScanNetDataset(unittest.TestCase):
         assert ann_info['gt_labels_3d'].dtype == np.int64
         # all instance have been filtered by classes
         self.assertEqual(len(ann_info['gt_labels_3d']), 3)
-        self.assertEqual(len(bed_scannet_dataset.metainfo['CLASSES']), 1)
+        self.assertEqual(len(bed_scannet_dataset.metainfo['classes']), 1)

tests/test_evaluation/test_metrics/test_indoor_metric.py

@@ -49,7 +49,7 @@ class TestIndoorMetric(unittest.TestCase):
         pred_dict['eval_ann_info'] = eval_ann_info
 
         indoor_metric.dataset_meta = {
-            'CLASSES': ('cabinet', 'bed', 'chair', 'sofa', 'table', 'door',
+            'classes': ('cabinet', 'bed', 'chair', 'sofa', 'table', 'door',
                         'window', 'bookshelf', 'picture', 'counter', 'desk',
                         'curtain', 'refrigerator', 'showercurtrain', 'toilet',
                         'sink', 'bathtub', 'garbagebin'),

tests/test_evaluation/test_metrics/test_instance_seg_metric.py

@@ -67,7 +67,7 @@ class TestInstanceSegMetric(unittest.TestCase):
                         'curtain', 'refrigerator', 'showercurtrain', 'toilet',
                         'sink', 'bathtub', 'garbagebin')
         dataset_meta = dict(
-            seg_valid_class_ids=seg_valid_class_ids, CLASSES=class_labels)
+            seg_valid_class_ids=seg_valid_class_ids, classes=class_labels)
         instance_seg_metric = InstanceSegMetric()
         instance_seg_metric.dataset_meta = dataset_meta
         instance_seg_metric.process(data_batch, predictions)

tests/test_evaluation/test_metrics/test_kitti_metric.py

@@ -53,7 +53,7 @@ def test_multi_modal_kitti_metric():
         pytest.skip('test requires GPU and torch+cuda')
     kittimetric = KittiMetric(
         data_root + '/kitti_infos_train.pkl', metric=['mAP'])
-    kittimetric.dataset_meta = dict(CLASSES=['Pedestrian', 'Cyclist', 'Car'])
+    kittimetric.dataset_meta = dict(classes=['Pedestrian', 'Cyclist', 'Car'])
     data_batch, predictions = _init_multi_modal_evaluate_input()
     kittimetric.process(data_batch, predictions)
     ap_dict = kittimetric.compute_metrics(kittimetric.results)
@@ -76,7 +76,7 @@ def test_kitti_metric_mAP():
         pytest.skip('test requires GPU and torch+cuda')
     kittimetric = KittiMetric(
         data_root + '/kitti_infos_train.pkl', metric=['mAP'])
-    kittimetric.dataset_meta = dict(CLASSES=['Pedestrian', 'Cyclist', 'Car'])
+    kittimetric.dataset_meta = dict(classes=['Pedestrian', 'Cyclist', 'Car'])
     data_batch, predictions = _init_evaluate_input()
     kittimetric.process(data_batch, predictions)
     ap_dict = kittimetric.compute_metrics(kittimetric.results)

tools/dataset_converters/create_gt_database.py

@@ -243,7 +243,7 @@ def create_groundtruth_database(dataset_class_name,
         image_idx = example['sample_idx']
         points = example['points'].tensor.numpy()
         gt_boxes_3d = annos['gt_bboxes_3d'].tensor.numpy()
-        names = [dataset.metainfo['CLASSES'][i] for i in annos['gt_labels_3d']]
+        names = [dataset.metainfo['classes'][i] for i in annos['gt_labels_3d']]
         group_dict = dict()
         if 'group_ids' in annos:
             group_ids = annos['group_ids']
@@ -409,7 +409,7 @@ class GTDatabaseCreater:
         points = example['points'].tensor.numpy()
         gt_boxes_3d = annos['gt_bboxes_3d'].tensor.numpy()
         names = [
-            self.dataset.metainfo['CLASSES'][i] for i in annos['gt_labels_3d']
+            self.dataset.metainfo['classes'][i] for i in annos['gt_labels_3d']
         ]
         group_dict = dict()
         if 'group_ids' in annos:

tools/dataset_converters/update_infos_to_v2.py

@@ -261,7 +261,7 @@ def update_nuscenes_infos(pkl_path, out_dir):
     print(f'Reading from input file: {pkl_path}.')
     data_list = mmengine.load(pkl_path)
     METAINFO = {
-        'CLASSES':
+        'classes':
         ('car', 'truck', 'trailer', 'bus', 'construction_vehicle', 'bicycle',
          'motorcycle', 'pedestrian', 'traffic_cone', 'barrier'),
     }
@@ -340,8 +340,8 @@ def update_nuscenes_infos(pkl_path, out_dir):
             empty_instance = get_empty_instance()
             empty_instance['bbox_3d'] = ori_info_dict['gt_boxes'][
                 i, :].tolist()
-            if ori_info_dict['gt_names'][i] in METAINFO['CLASSES']:
-                empty_instance['bbox_label'] = METAINFO['CLASSES'].index(
+            if ori_info_dict['gt_names'][i] in METAINFO['classes']:
+                empty_instance['bbox_label'] = METAINFO['classes'].index(
                     ori_info_dict['gt_names'][i])
             else:
                 ignore_class_name.add(ori_info_dict['gt_names'][i])
@@ -386,7 +386,7 @@ def update_kitti_infos(pkl_path, out_dir):
     # TODO update to full label
     # TODO discuss how to process 'Van', 'DontCare'
     METAINFO = {
-        'CLASSES': ('Pedestrian', 'Cyclist', 'Car', 'Van', 'Truck',
+        'classes': ('Pedestrian', 'Cyclist', 'Car', 'Van', 'Truck',
                     'Person_sitting', 'Tram', 'Misc'),
     }
     print(f'Reading from input file: {pkl_path}.')
@@ -451,8 +451,8 @@ def update_kitti_infos(pkl_path, out_dir):
             empty_instance = get_empty_instance()
             empty_instance['bbox'] = anns['bbox'][instance_id].tolist()
 
-            if anns['name'][instance_id] in METAINFO['CLASSES']:
-                empty_instance['bbox_label'] = METAINFO['CLASSES'].index(
+            if anns['name'][instance_id] in METAINFO['classes']:
+                empty_instance['bbox_label'] = METAINFO['classes'].index(
                     anns['name'][instance_id])
             else:
                 ignore_class_name.add(anns['name'][instance_id])
@@ -522,7 +522,7 @@ def update_s3dis_infos(pkl_path, out_dir):
         print(f'Warning, you may overwriting '
               f'the original data {pkl_path}.')
         time.sleep(5)
-    METAINFO = {'CLASSES': ('table', 'chair', 'sofa', 'bookcase', 'board')}
+    METAINFO = {'classes': ('table', 'chair', 'sofa', 'bookcase', 'board')}
     print(f'Reading from input file: {pkl_path}.')
     data_list = mmengine.load(pkl_path)
     print('Start updating:')
@@ -554,12 +554,12 @@ def update_s3dis_infos(pkl_path, out_dir):
                     empty_instance['bbox_3d'] = anns['gt_boxes_upright_depth'][
                         instance_id].tolist()
 
-                    if anns['class'][instance_id] < len(METAINFO['CLASSES']):
+                    if anns['class'][instance_id] < len(METAINFO['classes']):
                         empty_instance['bbox_label_3d'] = anns['class'][
                             instance_id]
                     else:
                         ignore_class_name.add(
-                            METAINFO['CLASSES'][anns['class'][instance_id]])
+                            METAINFO['classes'][anns['class'][instance_id]])
                         empty_instance['bbox_label_3d'] = -1
 
                     empty_instance = clear_instance_unused_keys(empty_instance)
@@ -593,7 +593,7 @@ def update_scannet_infos(pkl_path, out_dir):
               f'the original data {pkl_path}.')
         time.sleep(5)
     METAINFO = {
-        'CLASSES':
+        'classes':
         ('cabinet', 'bed', 'chair', 'sofa', 'table', 'door', 'window',
          'bookshelf', 'picture', 'counter', 'desk', 'curtain', 'refrigerator',
          'showercurtrain', 'toilet', 'sink', 'bathtub', 'garbagebin')
@@ -629,9 +629,9 @@ def update_scannet_infos(pkl_path, out_dir):
                 empty_instance['bbox_3d'] = anns['gt_boxes_upright_depth'][
                     instance_id].tolist()
 
-                if anns['name'][instance_id] in METAINFO['CLASSES']:
+                if anns['name'][instance_id] in METAINFO['classes']:
                     empty_instance['bbox_label_3d'] = METAINFO[
-                        'CLASSES'].index(anns['name'][instance_id])
+                        'classes'].index(anns['name'][instance_id])
                 else:
                     ignore_class_name.add(anns['name'][instance_id])
                     empty_instance['bbox_label_3d'] = -1
@@ -667,7 +667,7 @@ def update_sunrgbd_infos(pkl_path, out_dir):
               f'the original data {pkl_path}.')
         time.sleep(5)
     METAINFO = {
-        'CLASSES': ('bed', 'table', 'sofa', 'chair', 'toilet', 'desk',
+        'classes': ('bed', 'table', 'sofa', 'chair', 'toilet', 'desk',
                     'dresser', 'night_stand', 'bookshelf', 'bathtub')
     }
     print(f'Reading from input file: {pkl_path}.')
@@ -705,9 +705,9 @@ def update_sunrgbd_infos(pkl_path, out_dir):
                 empty_instance['bbox_3d'] = anns['gt_boxes_upright_depth'][
                     instance_id].tolist()
                 empty_instance['bbox'] = anns['bbox'][instance_id].tolist()
-                if anns['name'][instance_id] in METAINFO['CLASSES']:
+                if anns['name'][instance_id] in METAINFO['classes']:
                     empty_instance['bbox_label_3d'] = METAINFO[
-                        'CLASSES'].index(anns['name'][instance_id])
+                        'classes'].index(anns['name'][instance_id])
                     empty_instance['bbox_label'] = empty_instance[
                         'bbox_label_3d']
                 else:
@@ -746,7 +746,7 @@ def update_lyft_infos(pkl_path, out_dir):
     print(f'Reading from input file: {pkl_path}.')
     data_list = mmengine.load(pkl_path)
     METAINFO = {
-        'CLASSES':
+        'classes':
         ('car', 'truck', 'bus', 'emergency_vehicle', 'other_vehicle',
          'motorcycle', 'bicycle', 'pedestrian', 'animal'),
     }
@@ -817,8 +817,8 @@ def update_lyft_infos(pkl_path, out_dir):
             empty_instance = get_empty_instance()
             empty_instance['bbox_3d'] = ori_info_dict['gt_boxes'][
                 i, :].tolist()
-            if ori_info_dict['gt_names'][i] in METAINFO['CLASSES']:
-                empty_instance['bbox_label'] = METAINFO['CLASSES'].index(
+            if ori_info_dict['gt_names'][i] in METAINFO['classes']:
+                empty_instance['bbox_label'] = METAINFO['classes'].index(
                     ori_info_dict['gt_names'][i])
             else:
                 ignore_class_name.add(ori_info_dict['gt_names'][i])
@@ -865,7 +865,7 @@ def update_waymo_infos(pkl_path, out_dir):
     # TODO update to full label
     # TODO discuss how to process 'Van', 'DontCare'
     METAINFO = {
-        'CLASSES': ('Car', 'Pedestrian', 'Cyclist', 'Sign'),
+        'classes': ('Car', 'Pedestrian', 'Cyclist', 'Sign'),
     }
     print(f'Reading from input file: {pkl_path}.')
     data_list = mmengine.load(pkl_path)
@@ -955,8 +955,8 @@ def update_waymo_infos(pkl_path, out_dir):
             empty_instance = get_empty_instance()
             empty_instance['bbox'] = anns['bbox'][instance_id].tolist()
 
-            if anns['name'][instance_id] in METAINFO['CLASSES']:
-                empty_instance['bbox_label'] = METAINFO['CLASSES'].index(
+            if anns['name'][instance_id] in METAINFO['classes']:
+                empty_instance['bbox_label'] = METAINFO['classes'].index(
                     anns['name'][instance_id])
             else:
                 ignore_class_name.add(anns['name'][instance_id])
@@ -999,8 +999,8 @@ def update_waymo_infos(pkl_path, out_dir):
             empty_instance = get_empty_instance()
             empty_instance['bbox'] = anns['bbox'][instance_id].tolist()
 
-            if anns['name'][instance_id] in METAINFO['CLASSES']:
-                empty_instance['bbox_label'] = METAINFO['CLASSES'].index(
+            if anns['name'][instance_id] in METAINFO['classes']:
+                empty_instance['bbox_label'] = METAINFO['classes'].index(
                     anns['name'][instance_id])
             else:
                 ignore_class_name.add(anns['name'][instance_id])