commit 2

Author: vbhv14

guide/14-deep-learning/point_cloud_classification_using_sqn.ipynb

@@ -167,8 +167,8 @@
     "```python\n",
     "output_path=r'C:/project/training_data.pctd'\n",
     "data = prepare_data(output_path, dataset_type='PointCloud', batch_size=2)\n",
-    "sg = SQNSeg(data)\n",
-    "sg.fit(20)\n",
+    "sq = SQNSeg(data)\n",
+    "sq.fit(20)\n",
     "```\n",
     "After training the SQN model, `compute_precision_recall()` method can be used to compute, per-class metrics (precision, recall, and f1-score) with respect to validation data. And `save()` method can be used to save the model."
    ]
@@ -234,7 +234,7 @@
     "A typical usage with respect to API looks like:\n",
     "\n",
     "```python\n",
-    "sg = SQNSeg(data=data, \n",
+    "sq = SQNSeg(data=data, \n",
     "               encoder_params={'out_channels':[16, 64, 128, 256],\n",
     "                               'sub_sampling_ratio':[4, 4, 4, 4],\n",
     "                               'k_n':16,\n",