reduc test data

tests/data/sunrgbd/sunrgbd_trainval/val_data_idx.txt

-3
-4
+2

tests/test_indoor_loading.py

@@ -4,97 +4,39 @@ from mmdet3d.datasets.pipelines.indoor_loading import IndoorLoadData
 
 
 def test_indoor_load_data():
-    sunrgbd_train_info = mmcv.load(
-        './tests/data/sunrgbd/sunrgbd_infos_train.pkl')
-    sunrgbd_load_train_data = IndoorLoadData('sunrgbd', False, True,
-                                             [0.5, 0.5, 0.5])
-    sunrgbd_train_results = dict()
-    sunrgbd_train_results[
-        'data_path'] = './tests/data/sunrgbd/sunrgbd_trainval'
-    sunrgbd_train_results['info'] = sunrgbd_train_info[0]
-    sunrgbd_train_results = sunrgbd_load_train_data(sunrgbd_train_results)
-    sunrgbd_train_point_cloud = sunrgbd_train_results.get('point_cloud', None)
-    sunrgbd_train_gt_boxes = sunrgbd_train_results.get('gt_boxes', None)
-    sunrgbd_train_gt_classes = sunrgbd_train_results.get('gt_classes', None)
-    sunrgbd_train_gt_boxes_mask = sunrgbd_train_results.get(
-        'gt_boxes_mask', None)
-    assert sunrgbd_train_point_cloud.shape == (50000, 4)
-    assert sunrgbd_train_gt_boxes.shape == (3, 7)
-    assert sunrgbd_train_gt_classes.shape == (3, 1)
-    assert sunrgbd_train_gt_boxes_mask.shape == (3, 1)
+    sunrgbd_info = mmcv.load('./tests/data/sunrgbd/sunrgbd_infos_train.pkl')
+    sunrgbd_load_data = IndoorLoadData('sunrgbd', False, True, [0.5, 0.5, 0.5])
+    sunrgbd_results = dict()
+    sunrgbd_results['data_path'] = './tests/data/sunrgbd/sunrgbd_trainval'
+    sunrgbd_results['info'] = sunrgbd_info[0]
+    sunrgbd_results = sunrgbd_load_data(sunrgbd_results)
+    sunrgbd_point_cloud = sunrgbd_results.get('point_cloud', None)
+    sunrgbd_gt_boxes = sunrgbd_results.get('gt_boxes', None)
+    sunrgbd_gt_classes = sunrgbd_results.get('gt_classes', None)
+    sunrgbd_gt_boxes_mask = sunrgbd_results.get('gt_boxes_mask', None)
+    assert sunrgbd_point_cloud.shape == (1000, 4)
+    assert sunrgbd_gt_boxes.shape == (3, 7)
+    assert sunrgbd_gt_classes.shape == (3, 1)
+    assert sunrgbd_gt_boxes_mask.shape == (3, 1)
 
-    scannet_val_info = mmcv.load('./tests/data/sunrgbd/sunrgbd_infos_val.pkl')
-    scannet_load_val_data = IndoorLoadData('sunrgbd', False, True,
-                                           [0.5, 0.5, 0.5])
-    scannet_val_results = dict()
-    scannet_val_results['data_path'] = './tests/data/sunrgbd/sunrgbd_trainval'
-    scannet_val_results['info'] = scannet_val_info[0]
-    scannet_val_results = scannet_load_val_data(scannet_val_results)
-    scannet_val_point_cloud = scannet_val_results.get('point_cloud', None)
-    scannet_val_gt_boxes = scannet_val_results.get('gt_boxes', None)
-    scannet_val_gt_classes = scannet_val_results.get('gt_classes', None)
-    scannet_val_gt_boxes_mask = scannet_val_results.get('gt_boxes_mask', None)
-    assert scannet_val_point_cloud.shape == (50000, 4)
-    assert scannet_val_gt_boxes.shape == (3, 7)
-    assert scannet_val_gt_classes.shape == (3, 1)
-    assert scannet_val_gt_boxes_mask.shape == (3, 1)
-
-    sunrgbd_train_info = mmcv.load(
-        './tests/data/sunrgbd/sunrgbd_infos_train.pkl')
-    sunrgbd_load_train_data = IndoorLoadData('sunrgbd', False, True,
-                                             [0.5, 0.5, 0.5])
-    sunrgbd_train_results = dict()
-    sunrgbd_train_results[
-        'data_path'] = './tests/data/sunrgbd/sunrgbd_trainval'
-    sunrgbd_train_results['info'] = sunrgbd_train_info[0]
-    sunrgbd_train_results = sunrgbd_load_train_data(sunrgbd_train_results)
-    sunrgbd_train_point_cloud = sunrgbd_train_results.get('point_cloud', None)
-    sunrgbd_train_gt_boxes = sunrgbd_train_results.get('gt_boxes', None)
-    sunrgbd_train_gt_classes = sunrgbd_train_results.get('gt_classes', None)
-    sunrgbd_train_gt_boxes_mask = sunrgbd_train_results.get(
-        'gt_boxes_mask', None)
-    assert sunrgbd_train_point_cloud.shape == (50000, 4)
-    assert sunrgbd_train_gt_boxes.shape == (3, 7)
-    assert sunrgbd_train_gt_classes.shape == (3, 1)
-    assert sunrgbd_train_gt_boxes_mask.shape == (3, 1)
-
-    scannet_val_info = mmcv.load(
-        './tests/data/scannet/scannet_infos_train.pkl')
-    scannet_load_val_data = IndoorLoadData('scannet', False, True,
-                                           [0.5, 0.5, 0.5])
-    scannet_val_results = dict()
-    scannet_val_results[
-        'data_path'] = './tests/data/scannet/scannet_train_instance_data'
-    scannet_val_results['info'] = scannet_val_info[0]
-    scannet_val_results = scannet_load_val_data(scannet_val_results)
-    scannet_val_point_cloud = scannet_val_results.get('point_cloud', None)
-    scannet_val_gt_boxes = scannet_val_results.get('gt_boxes', None)
-    scannet_val_gt_classes = scannet_val_results.get('gt_classes', None)
-    scannet_val_gt_boxes_mask = scannet_val_results.get('gt_boxes_mask', None)
-    scannet_pcl_color = scannet_val_results.get('pcl_color', None)
-    scannet_instance_labels = scannet_val_results.get('instance_labels', None)
-    scannet_semantic_labels = scannet_val_results.get('semantic_labels', None)
-    assert scannet_val_point_cloud.shape == (50000, 4)
-    assert scannet_val_gt_boxes.shape == (27, 6)
-    assert scannet_val_gt_classes.shape == (27, 1)
-    assert scannet_val_gt_boxes_mask.shape == (27, 1)
-    assert scannet_pcl_color.shape == (50000, 3)
-    assert scannet_instance_labels.shape == (50000, )
-    assert scannet_semantic_labels.shape == (50000, )
-
-    scannet_val_info = mmcv.load('./tests/data/scannet/scannet_infos_val.pkl')
-    scannet_load_val_data = IndoorLoadData('scannet', False, True,
-                                           [0.5, 0.5, 0.5])
-    scannet_val_results = dict()
-    scannet_val_results[
+    scannet_info = mmcv.load('./tests/data/scannet/scannet_infos_train.pkl')
+    scannet_load_data = IndoorLoadData('scannet', False, True, [0.5, 0.5, 0.5])
+    scannet_results = dict()
+    scannet_results[
         'data_path'] = './tests/data/scannet/scannet_train_instance_data'
-    scannet_val_results['info'] = scannet_val_info[0]
-    scannet_val_results = scannet_load_val_data(scannet_val_results)
-    scannet_val_point_cloud = scannet_val_results.get('point_cloud', None)
-    scannet_val_gt_boxes = scannet_val_results.get('gt_boxes', None)
-    scannet_val_gt_classes = scannet_val_results.get('gt_classes', None)
-    scannet_val_gt_boxes_mask = scannet_val_results.get('gt_boxes_mask', None)
-    assert scannet_val_point_cloud.shape == (50000, 4)
-    assert scannet_val_gt_boxes.shape == (28, 6)
-    assert scannet_val_gt_classes.shape == (28, 1)
-    assert scannet_val_gt_boxes_mask.shape == (28, 1)
+    scannet_results['info'] = scannet_info[0]
+    scannet_results = scannet_load_data(scannet_results)
+    scannet_point_cloud = scannet_results.get('point_cloud', None)
+    scannet_gt_boxes = scannet_results.get('gt_boxes', None)
+    scannet_gt_classes = scannet_results.get('gt_classes', None)
+    scannet_gt_boxes_mask = scannet_results.get('gt_boxes_mask', None)
+    scannet_pcl_color = scannet_results.get('pcl_color', None)
+    scannet_instance_labels = scannet_results.get('instance_labels', None)
+    scannet_semantic_labels = scannet_results.get('semantic_labels', None)
+    assert scannet_point_cloud.shape == (1000, 4)
+    assert scannet_gt_boxes.shape == (27, 6)
+    assert scannet_gt_classes.shape == (27, 1)
+    assert scannet_gt_boxes_mask.shape == (27, 1)
+    assert scannet_pcl_color.shape == (1000, 3)
+    assert scannet_instance_labels.shape == (1000, )
+    assert scannet_semantic_labels.shape == (1000, )

tools/data_converter/sunrgbd_data_utils.py

@@ -112,7 +112,7 @@ class SUNRGBDData(object):
         def process_single_scene(sample_idx):
             print('%s sample_idx: %s' % (self.split, sample_idx))
             # convert depth to points
-            SAMPLE_NUM = 50000
+            SAMPLE_NUM = 1000
             pc_upright_depth = self.get_depth(sample_idx)
             # TODO : sample points in loading process and test
             pc_upright_depth_subsampled = random_sampling(