finish indoor_flip and test unit

mmdet3d/datasets/pipelines/indoor_augment.py

+import numpy as np
+
+from mmdet.datasets.registry import PIPELINES
+
+
+@PIPELINES.register_module()
+class IndoorFlipData(object):
+    """Indoor Flip Data
+
+    Flip the points and groundtruth boxes.
+
+    Args:
+        name (str): name of the dataset.
+    """
+
+    def __init__(self, name):
+        assert name in ['scannet', 'sunrgbd']
+        self.name = name
+
+    def __call__(self, results):
+        point_cloud = results.get('point_cloud', None)
+        gt_boxes = results.get('gt_boxes', None)
+        if np.random.random() > 0.5:
+            # Flipping along the YZ plane
+            point_cloud[:, 0] = -1 * point_cloud[:, 0]
+            gt_boxes[:, 0] = -1 * gt_boxes[:, 0]
+            if self.name == 'sunrgbd':
+                gt_boxes[:, 6] = np.pi - gt_boxes[:, 6]
+            results['gt_boxes'] = gt_boxes
+        if self.name == 'scannet' and np.random.random() > 0.5:
+            # Flipping along the XZ plane
+            point_cloud[:, 1] = -1 * point_cloud[:, 1]
+            gt_boxes[:, 1] = -1 * gt_boxes[:, 1]
+            results['gt_boxes'] = gt_boxes
+        results['point_cloud'] = point_cloud
+
+        return results
+
+    def __repr__(self):
+        repr_str = self.__class__.__name__
+        repr_str += '(dataset_name={})'.format(self.name)
+        return repr_str

mmdet3d/datasets/pipelines/indoor_loading.py

@@ -70,6 +70,10 @@ class IndoorLoadData(object):
 
     def __repr__(self):
         repr_str = self.__class__.__name__
+        repr_str += '(dataset_name={})'.format(self.name)
+        repr_str += '(use_height={})'.format(self.use_height)
+        repr_str += '(use_color={}'.format(self.use_color)
+        repr_str += '(mean_color={})'.format(self.mean_color)
         return repr_str
 
     def _get_lidar(self, scan_name, data_path):

tests/test_indoor_augment.py

+import numpy as np
+
+from mmdet3d.datasets.pipelines.indoor_augment import IndoorFlipData
+
+
+def test_indoor_flip_data():
+    sunrgbd_flip_data = IndoorFlipData('sunrgbd')
+    sunrgbd_results = dict()
+    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([[
+        0.213684, 1.036364, -0.982323, 0.61541, 0.572574, 0.872728, 3.07028526
+    ],
+                                            [
+                                                -0.449953, 1.395455, -1.027778,
+                                                1.500956, 1.637298, 0.636364,
+                                                -1.58242359
+                                            ]])
+    sunrgbd_results = sunrgbd_flip_data(sunrgbd_results)
+    sunrgbd_point_cloud = sunrgbd_results.get('point_cloud', None)
+    sunrgbd_gt_boxes = sunrgbd_results.get('gt_boxes', None)
+    assert sunrgbd_point_cloud.shape == (2, 4)
+    assert sunrgbd_gt_boxes.shape == (2, 7)
+    scannet_flip_data = IndoorFlipData('scannet')
+    scannet_results = dict()
+    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([[
+        0.55903838, 0.48201692, 0.65688646, 0.65370704, 0.60029864, 0.5163464
+    ], [
+        -0.03226406, 1.70392646, 0.60348618, 0.65165804, 0.72084366, 0.64667457
+    ]])
+    scannet_results = scannet_flip_data(scannet_results)
+    scannet_point_cloud = scannet_results.get('point_cloud', None)
+    scannet_gt_boxes = scannet_results.get('gt_boxes', None)
+    assert scannet_point_cloud.shape == (2, 4)
+    assert scannet_gt_boxes.shape == (2, 6)