finish indoor load test unit

tests/data/sunrgbd/sunrgbd_trainval/label_v1/000004.txt

+bed 125 98 416 333 -0.248717 3.078656 -0.411026 0.906626 0.995895 0.788974 0.179270 -0.983800
+night_stand 61 204 119 105 -1.700247 3.645455 -0.707344 0.382063 0.203700 0.340909 0.138196 -0.990405
+lamp 80 86 79 124 -1.677273 3.627273 0.022727 0.234005 0.176469 0.409091 0.227884 -0.973688
+ottoman 151 331 486 199 0.127273 1.600000 -0.806818 0.734650 0.309392 0.393182 0.176299 -0.984337

tests/data/sunrgbd/sunrgbd_trainval/train_data_idx.txt

+1
+2

tests/data/sunrgbd/sunrgbd_trainval/val_data_idx.txt

+3
+4

tests/test_indoor_augment.py

 import numpy as np
 
 from mmdet3d.datasets.pipelines.indoor_augment import (IndoorFlipData,
-                                                       IndoorRotateData,
-                                                       PointShuffle)
+                                                       IndoorRotateData)
 
 
 def test_indoor_flip_data():
     sunrgbd_flip_data = IndoorFlipData('sunrgbd')
     sunrgbd_results = dict()
-    sunrgbd_results['points'] = np.array(
+    sunrgbd_results['point_cloud'] = np.array(
         [[1.02828765e+00, 3.65790772e+00, 1.97294697e-01, 1.61959505e+00],
          [-3.95979017e-01, 1.05465031e+00, -7.49204338e-01, 6.73096001e-01]])
     sunrgbd_results['gt_boxes'] = np.array([[
@@ -20,14 +19,14 @@ def test_indoor_flip_data():
                                                 -1.58242359
                                             ]])
     sunrgbd_results = sunrgbd_flip_data(sunrgbd_results)
-    sunrgbd_points = sunrgbd_results.get('points', None)
+    sunrgbd_point_cloud = sunrgbd_results.get('point_cloud', None)
     sunrgbd_gt_boxes = sunrgbd_results.get('gt_boxes', None)
-    assert sunrgbd_points.shape == (2, 4)
+    assert sunrgbd_point_cloud.shape == (2, 4)
     assert sunrgbd_gt_boxes.shape == (2, 7)
 
     scannet_flip_data = IndoorFlipData('scannet')
     scannet_results = dict()
-    scannet_results['points'] = np.array(
+    scannet_results['point_cloud'] = np.array(
         [[1.6110241e+00, -1.6903955e-01, 5.8115810e-01, 5.9897250e-01],
          [1.3978075e+00, 4.2035791e-01, 3.8729519e-01, 4.0510958e-01]])
     scannet_results['gt_boxes'] = np.array([[
@@ -36,9 +35,9 @@ def test_indoor_flip_data():
         -0.03226406, 1.70392646, 0.60348618, 0.65165804, 0.72084366, 0.64667457
     ]])
     scannet_results = scannet_flip_data(scannet_results)
-    scannet_points = scannet_results.get('points', None)
+    scannet_point_cloud = scannet_results.get('point_cloud', None)
     scannet_gt_boxes = scannet_results.get('gt_boxes', None)
-    assert scannet_points.shape == (2, 4)
+    assert scannet_point_cloud.shape == (2, 4)
     assert scannet_gt_boxes.shape == (2, 6)
 
 
@@ -46,7 +45,7 @@ def test_indoor_rotate_data():
     sunrgbd_indoor_rotate_data = IndoorRotateData('sunrgbd')
 
     sunrgbd_results = dict()
-    sunrgbd_results['points'] = np.array(
+    sunrgbd_results['point_cloud'] = np.array(
         [[1.02828765e+00, 3.65790772e+00, 1.97294697e-01, 1.61959505e+00],
          [-3.95979017e-01, 1.05465031e+00, -7.49204338e-01, 6.73096001e-01]])
     sunrgbd_results['gt_boxes'] = np.array([[
@@ -58,14 +57,14 @@ def test_indoor_rotate_data():
                                                 -1.58242359
                                             ]])
     sunrgbd_results = sunrgbd_indoor_rotate_data(sunrgbd_results)
-    sunrgbd_points = sunrgbd_results.get('points', None)
+    sunrgbd_point_cloud = sunrgbd_results.get('point_cloud', None)
     sunrgbd_gt_boxes = sunrgbd_results.get('gt_boxes', None)
-    assert sunrgbd_points.shape == (2, 4)
+    assert sunrgbd_point_cloud.shape == (2, 4)
     assert sunrgbd_gt_boxes.shape == (2, 7)
 
     scannet_indoor_rotate_data = IndoorRotateData('scannet')
     scannet_results = dict()
-    scannet_results['points'] = np.array(
+    scannet_results['point_cloud'] = np.array(
         [[1.6110241e+00, -1.6903955e-01, 5.8115810e-01, 5.9897250e-01],
          [1.3978075e+00, 4.2035791e-01, 3.8729519e-01, 4.0510958e-01]])
     scannet_results['gt_boxes'] = np.array([[
@@ -74,18 +73,7 @@ def test_indoor_rotate_data():
         -0.03226406, 1.70392646, 0.60348618, 0.65165804, 0.72084366, 0.64667457
     ]])
     scannet_results = scannet_indoor_rotate_data(scannet_results)
-    scannet_points = scannet_results.get('points', None)
+    scannet_point_cloud = scannet_results.get('point_cloud', None)
     scannet_gt_boxes = scannet_results.get('gt_boxes', None)
-    assert scannet_points.shape == (2, 4)
+    assert scannet_point_cloud.shape == (2, 4)
     assert scannet_gt_boxes.shape == (2, 6)
-
-
-def test_point_shuffle():
-    point_shuffle = PointShuffle()
-    results = dict()
-    results['points'] = np.array(
-        [[1.02828765e+00, 3.65790772e+00, 1.97294697e-01, 1.61959505e+00],
-         [-3.95979017e-01, 1.05465031e+00, -7.49204338e-01, 6.73096001e-01]])
-    results = point_shuffle(results)
-    points = results.get('points')
-    assert points.shape == (2, 4)

tests/test_indoor_loading.py

@@ -4,17 +4,97 @@ from mmdet3d.datasets.pipelines.indoor_loading import IndoorLoadData
 
 
 def test_indoor_load_data():
-    train_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'] = train_info[0]
-    sunrgbd_results = sunrgbd_load_data(sunrgbd_results)
-    point_cloud = sunrgbd_results.get('point_cloud', None)
-    gt_boxes = sunrgbd_results.get('gt_boxes', None)
-    gt_classes = sunrgbd_results.get('gt_classes', None)
-    gt_boxes_mask = sunrgbd_results.get('gt_boxes_mask', None)
-    assert point_cloud.shape == (50000, 4)
-    assert gt_boxes.shape == (3, 7)
-    assert gt_classes.shape == (3, 1)
-    assert 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/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[
+        '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)